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Testing inhabitant agency in interactive architecture : a user-centered design and research approach Costa Maia, Sara 2016

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ii  This thesis assembled, tested and demonstrated an inhabitant-centered approach for research and design in Interactive Architecture (IA). It takes an initial step in addressing a critical gap in the field concerning the lack of  empirical evidence to support IA’s fundamental claims, especially regarding inhabitant experience. The approach focused on investigating the question of  whether inhabitant experience of  interactive architecture (IA), presumably dependent on different models of  interaction, could support one of  the primordial rationales for the social relevance of  IA. The rationale states that IA holds the potential to empower inhabitants in participating in the continuous formation of  their environment. However, there is no published evidence to date to corroborate the statement’s validity. In fact, very little research has been done to date on inhabitant experience of  interactive spaces in general, hindering our ability to justify its use or to properly ground design decisions. Therefore, this thesis presents an exploratory investigation, set to form the basis for the study of  agency and empowerment in IA, and aiming to demonstrate an approach to tackle the problem of  user-centered design and research in the field. An extensive literature review is thus conducted, from the concept of  agency in the social sciences to an overview of  the pertinent literature on interaction. Finally, an approach is demonstrated to generate empirical evidences regarding agency in IA. For that, an IA space is designed (comprehending four different models of  interaction), assembled and tested, grounded on two user-centered design studies. The first study was an anticipated experience diary study, where 17 participants reported their imagined daily experience with an IA concept. The second study was a user experience survey where 30 participants inhabited and experienced the assembled IA space. This thesis successfully demonstrated a user centered approach for evaluating interaction in IA design concepts, especially with regard to the possibility of  fulfilling one of  IA’s many untested claims, making explicit the problems and opportunities observed along the process.     iii  This dissertation is original, unpublished, independent work by the author, Sara Costa Maia. The anticipate experience diary study reported in Chapter 8 was covered under the approval of  UBC Behavioural Research Ethics Board, certificate number H15-02936. The user experience study reported in Chapter 10 was covered under the approval of  UBC Behavioural Research Ethics Board, certificate number H16-00621.                iv    .............................................................................................................................................................................. ii  ............................................................................................................................................................................... iii  ........................................................................................................................................................... iv  .................................................................................................................................................................. viii  ................................................................................................................................................................... ix  .................................................................................................................................................... xiv ....................................................................................................................................................................... xiv   .......................................................................................................... 1  .................................................................................................................................................................. 2 1.1 The research problem ............................................................................................................................................. 2 1.2 Why inhabitant agency? .......................................................................................................................................... 4 1.3 Thesis structure ........................................................................................................................................................ 8  .......................................................................................................................................... 12 2.1 What I mean by interactive architecture in this thesis? .................................................................................... 12 2.2 Cybernetics and the basis of  interactive architecture theory .......................................................................... 16 2.3 A portrait of  the old new territory of  interactive environments ................................................................... 20 2.4 Under all the enthusiasm: a critique of  interactive architecture ..................................................................... 29 2.5 But is interactive architecture a good solution for increasing inhabitant agency and participation, after all? ................................................................................................................................................................................... 32  ............................................................................................................ 35 3.1 What is agency? ...................................................................................................................................................... 35 3.2 Introduction to the theories of  human agency and empowerment .............................................................. 37 3.3 Distinguishing agency from other concepts ...................................................................................................... 42 3.4 Is the concept of  human agency applicable to architecture? .......................................................................... 43 3.5 Further considerations about agency and architecture .................................................................................... 46  ............................................................................................................................................................................... 50 4.1 Introduction ............................................................................................................................................................ 50 4.2 A historical overview: including the inhabitant in the loop of  architectural design ................................... 50 v  4.3 Technology mediated participation ..................................................................................................................... 55 4.4 Main approaches for sharing control with inhabitants .................................................................................... 59 4.4.1 Levels of  control ............................................................................................................................................ 59 4.4.2 Early computers and user empowerment through design ....................................................................... 62 4.4.3 Some of  recent proposals and the non-interactive architecture ............................................................. 65 4.4.4 Metadesign....................................................................................................................................................... 66 4.4.5 Smart homes, context-aware applications and end-user development .................................................. 70 4.5 Inhabitant agency in contemporary interactive architecture ........................................................................... 75  ........................................................................................................................................... 81 5.1 Building around interaction .................................................................................................................................. 81 5.2 Interaction design background and other considerations ............................................................................... 82 5.2.1 IA and interaction design .............................................................................................................................. 82 5.2.2 Goal-oriented frameworks ............................................................................................................................ 82 5.2.3 Mental models................................................................................................................................................. 86 5.2.4 Metaphors for empowerment ...................................................................................................................... 88 5.2.5 Embodiment ................................................................................................................................................... 91 5.2.6 Other variables: more aspects of  relevance for understanding IA interaction .................................... 94 5.3 Introduction to the problem of  interaction in IA ............................................................................................ 96 5.4 One more interaction for inhabitant agency ..................................................................................................... 99 5.5 Consolidating interaction models of  interactive architecture for inhabitant agency ................................ 102 5.6 A record of  important interaction concepts on inhabitant’s perception of  IA ........................................ 108  .................................................................................................................... 113  ....................................................... 114 6.1 Research problem ................................................................................................................................................ 114 6.2 Research question ................................................................................................................................................ 114 6.3 Research overview ............................................................................................................................................... 115  .................................................................................... 116 7.1 Overview ............................................................................................................................................................... 116 7.2 Initial requirements .............................................................................................................................................. 116 7.3 An inexpensive IA system that is about core architectural components .................................................... 117 7.3.1 An argument for soft architecture ............................................................................................................. 117 7.3.2 Changing architectural spaces one layer at a time ................................................................................... 118 vi  7.3.3 Exploring a medium for interactive infill ................................................................................................. 119 7.3.4 How 2D projections may create interior 3D spaces ............................................................................... 123 7.3.5 Initial explorations on representing 3D space via 2D images .............................................................. 124 7.4. Exploring design alternatives for floor projections ....................................................................................... 128 7.5. Describing interaction in two opposite design alternatives .......................................................................... 130 7.6 A design proposal on interactive architecture ................................................................................................. 134  ................................................................................................................... 137 8.1 Introduction .......................................................................................................................................................... 137 8.2. Research question ............................................................................................................................................... 138 8.3. Methodology ........................................................................................................................................................ 138 8.3.1 Research design ............................................................................................................................................ 138 8.3.2 Sampling ........................................................................................................................................................ 140 8.3.3 Monetary benefits or compensations ........................................................................................................ 141 8.3.4 Instrumentation ............................................................................................................................................ 141 8.3.5 Data collection and analysis ........................................................................................................................ 142 8.3.6 Protection of  Human Rights ..................................................................................................................... 142 8.4 Results and discussion ......................................................................................................................................... 142 8.5 Conclusion and limitations ................................................................................................................................. 151  .......................................................................................................................................... 152 9.1 Introduction .......................................................................................................................................................... 152 9.2 System overview ................................................................................................................................................... 152 9.3 System behaviour and operation ....................................................................................................................... 158 9.4 Self-adjusting interaction model ........................................................................................................................ 161 9.5 Direct manipulation interaction model ............................................................................................................ 164 9.6 Human-like interaction model ........................................................................................................................... 167 9.7 Emergent behaviour interaction model............................................................................................................ 169 ............................................................................................................................................................................................ 174 10.1 Introduction ........................................................................................................................................................ 174 10.2 Research question .............................................................................................................................................. 174 10.3 Methodology ...................................................................................................................................................... 174 10.3.1 Research design .......................................................................................................................................... 174 10.3.2 The interactive architecture setting ......................................................................................................... 176 vii  10.3.3 Sampling and recruitment ......................................................................................................................... 176 10.3.4 Monetary benefits or compensations ..................................................................................................... 177 10.3.5 Instrumentation and data collection ....................................................................................................... 177 10.3.5 Protection of  human rights ...................................................................................................................... 177 10.4 Results and discussion on the data collected ................................................................................................. 178  .............................................................................................................................................................. 193 11.1 Main contributions ............................................................................................................................................ 193 11.2 Lessons learned .................................................................................................................................................. 196 11.3 Future research ................................................................................................................................................... 201  .................................................................................................................................................................. 203  ................................................................................................................................................................... 216 Appendix A: Diary entry protocol .......................................................................................................................... 216 Appendix B: Final diary survey protocol ................................................................................................................ 217 Appendix C: Initial questionnaire for the Interactive Room study .................................................................... 218 Appendix D: User experience questionnaire for the Interactive Room study ................................................. 219 Appendix E: Observation notes protocol for the Interactive Room study ...................................................... 222            viii  Table 1 - Comparison of  conventional methods of  Participatory Design and Interactive Architecture in incorporating the inhabitant in the formation of  their environment ....................................................................... 33 Table 2 - Comparative description of  behaviour in different projection-based interactive infill concepts ..... 130 Table 3 - Comparative of  length and number of  interactions per interaction mode .......................................... 179                ix  Figure 1- Types of  systems in different cybernetic systems. Adapted from Dubberly et al. (2009). .................. 19 Figure 2 - Types of  interaction in different cybernetic systems. Adapted from Dubberly et al. (2009). ............ 19 Figure 3 - Fun Palace, by Cedric Price. Source: Price (1961). .................................................................................... 23 Figure 4 - Matrix of  justifications found in publications addressing Interactive Architecture or Responsive Architecture (exact term). Adapted from Costa Maia and Meyboom (2015). ........................................................ 25 Figure 5 - two different “spatializations” of  activities in classrooms: lecture (left) and discussion (right). ....... 46 Figure 6 - The landscape of  user involvement approaches in design research. Adapted from Sanders and Stappers (2008). ................................................................................................................................................................. 53 Figure 7 - Shearing Layers of  Change. Adapted from Brand (1995). ...................................................................... 59 Figure 8 - A Diagram of  the Principle of  Environmental Levels. Adapted from Habraken & Teicher (1998)............................................................................................................................................................................................... 60 Figure 9 – Illustration of  the Quinta Monroy social housing project by Elemental. On the left, the original design as it was build and delivered and, on the right, the building after modifications and extensions executed by inhabitants. .................................................................................................................................................................... 69 Figure 10 - Hybridized control model for responsive architecture. Source: Sterk (2005). Used with permission............................................................................................................................................................................................... 76 Figure 11 - Framework of  responsive network. Source: Sterk (2005). Used with permission. ............................ 78 Figure 12 - Examples of  interactive spatial projects addressing user participation. .............................................. 79 Figure 13 - Layered model by Norman (1986). Adapted by the author. .................................................................. 83 Figure 14 - Layered model adapted to basic IA system. ............................................................................................. 84 Figure 15 – Intended mental model for the self-adjusting interaction model. ..................................................... 104 Figure 16 - Intended mental model for the direct manipulation interaction model. ........................................... 105 Figure 17 - Intended mental model for the human-like intelligence interaction model. ..................................... 106 Figure 18 - Intended mental model for the emergent behaviour interaction model ........................................... 107 Figure 19 - Comparison of  different strategies for the development of  an interactive infill system. ............... 120 Figure 20 - An interactive building in VR developed to test the media’s suitability towards IA user experience x  research. ............................................................................................................................................................................ 122 Figure 21 - BIG’s entry for the Audi Urban Future Award. ©Audi Urban Future Initiative. Used with permission. Retrieved from: http://audi-urban-future-initiative.com/facts/big-bjarke-ingels-group ............. 124 Figure 22 - Scenes from the movie “Dogville”, directed by Lars Von Trier. Source: Von Trier (2003). © Zentropa. Used with permission. ................................................................................................................................. 124 Figure 23- Example of  Philippe Rahm’s work with heat and radiation as generative elements. Source: Rahm (n.d.). © Philippe Rahm. Used with permission. ....................................................................................................... 125 Figure 24 - First design concept proposal for projection-based infill spatiality. ................................................... 126 Figure 25 - Illustration of  vibration layer in the initial design concept. ................................................................. 126 Figure 26 - Prototype test of  first design concept. ................................................................................................... 127 Figure 27 - Relation between spatiality and interaction in two-dimensional infill patterns. ............................... 128 Figure 28 - Design propositions in the spatiality/interaction continuum. ............................................................ 129 Figure 29 – Interactive infill based on projected “virtual walls” and “virtual rooms” ........................................ 135 Figure 30 - Advertisements posted on Facebook ...................................................................................................... 141 Figure 31 - Frequency distribution of  responses to initial survey .......................................................................... 143 Figure 32 - Distribution of  diary entries per architectural program, proximity to core concept and need/features ................................................................................................................................................................... 146 Figure 33 - Frequency distribution of  needs, as inferred from diary entry data .................................................. 148 Figure 34 - Use of  system intelligence or automation .............................................................................................. 149 Figure 35 - Overview of  the interactive room ........................................................................................................... 153 Figure 36 - The interactive room apparatus. Photos by Rohini Nair. ..................................................................... 154 Figure 37 - Projectors' mount. Photo by Rohini Nair. .............................................................................................. 154 Figure 38 – Apparatus of  the Interactive room. Cameras (right) and the control room (left). Photos by Rohini Nair. ................................................................................................................................................................................... 155 Figure 39 - Casters on furniture ensure they are easy to re-locate. ......................................................................... 155 Figure 41 - Example of  an initial setting without partitions (left) and example of  user organized space with interactive partitions and color (right). ........................................................................................................................ 156 xi  Figure 41 - The interactive room. Photo by Rohini Nair. ........................................................................................ 157 Figure 42 - The interactive room. Photo by Rohini Nair. ........................................................................................ 157 Figure 43 – Control system overview .......................................................................................................................... 159 Figure 44 - Tracking system overview ......................................................................................................................... 161 Figure 45 - Instructions for interacting with the interactive room, under a self-adjusting interaction model . 162 Figure 46 - Example of  inhabitant-room interaction under the self-adjusting interaction model. Photos by Rohini Nair....................................................................................................................................................................... 163 Figure 47 - Instructions for interacting with the interactive room, under a direct manipulation interaction model ................................................................................................................................................................................ 165 Figure 48 - Example of  inhabitant-room interaction under the direct manipulation interaction model. Photos by Rohini Nair ................................................................................................................................................................. 166 Figure 49 - Example of  feedback instructing users of  potentially problematic layout ....................................... 167 Figure 50 - Instructions for interacting with the interactive room, under a human-like intelligence interaction model ................................................................................................................................................................................ 168 Figure 51 - Example of  inhabitant-room interaction under the human-like intelligence interaction model. .. 169 Figure 52 - The underlying logic of  the emergent behaviour interaction instance .............................................. 170 Figure 53 - Instructions for interacting with the interactive room, under an emergent behaviour interaction model ................................................................................................................................................................................ 172 Figure 54 - Example of  inhabitant-room interaction under the emergent behaviour interaction model. ....... 173 Figure 55 - Frequency distribution of  the answers to the Likert scale items in the Initial Survey. ................... 179 Figure 56 - Legend to be used to interpret Figures 55 to 75 ................................................................................... 181 Figure 57 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 1 of  the user experience survey. ................................................................................................................................... 181 Figure 58 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 2 of  the user experience survey .................................................................................................................................... 181 Figure 59 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 3 of  the user experience survey .................................................................................................................................... 182 Figure 60 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 4 of  the user experience survey .................................................................................................................................... 182 xii  Figure 61 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 5 of  the user experience survey .................................................................................................................................... 182 Figure 62 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 6 of  the user experience survey .................................................................................................................................... 183 Figure 63 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 7 of  the user experience survey .................................................................................................................................... 183 Figure 64 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 8 of  the user experience survey .................................................................................................................................... 183 Figure 65 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 9 of  the user experience survey .................................................................................................................................... 184 Figure 66 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 10 of  the user experience survey .................................................................................................................................. 184 Figure 67 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 11 of  the user experience survey .................................................................................................................................. 184 Figure 68 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 12 of  the user experience survey .................................................................................................................................. 185 Figure 69 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 13 of  the user experience survey .................................................................................................................................. 185 Figure 70 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 14 of  the user experience survey .................................................................................................................................. 185 Figure 71 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 15 of  the user experience survey .................................................................................................................................. 186 Figure 72 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 16 of  the user experience survey .................................................................................................................................. 186 Figure 73 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 17 of  the user experience survey .................................................................................................................................. 186 Figure 74 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 18 of  the user experience survey .................................................................................................................................. 187 Figure 75 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 19 of  the user experience survey .................................................................................................................................. 187 Figure 76 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 20 of  the user experience survey .................................................................................................................................. 187 xiii  Figure 77 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 21 of  the user experience survey .................................................................................................................................. 188 Figure 78 - Comparative of  measures of  basic agency, autonomy, competence and empowerment ............... 188 Figure 79 - Comparative of  measures of  meaning, place identity, attachment, authorship and ownership .... 189 Figure 80 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 15 of  the user experience survey .................................................................................................................................. 191                       xiv  I offer my sincere gratitude to Prof. AnnaLisa Meyboom, for her enthusiasm, encouragement, and support throughout the development of  this work. I would also like to thank Prof. Blair Satterfield and Dr. Sidney Fels for their helpful suggestions and for serving on my thesis committee. Thanks as well to my fellow MASA students, who have offered invaluable assistance along the way. Thanks to Hina Aman for all the many feedbacks, discussions, debuggings, de-stressings, and encouragements. Thanks to my friends in Brazil who have continued to cheer for me and to assist in the success of  my little adventure beyond the Equator. Special thanks are owed to my family, who have been unwavering in their commitment to help me be the best I can be. For all the love, all the inspiration, all the selfless support. Nothing could ever have been accomplished without you.             xv            To my parents.          1                   2  1.1 The research problem Interactive Architecture (IA) is a provocative field of  investigation, with potentially disruptive impacts on the built environment. Nevertheless, the examination of  its social relevance in literature is still incipient and ill-supported. In order to contribute towards an improvement of  this scenario, I explore in my thesis one of  the first sociopolitical arguments around the relevance of  IA, namely inhabitant empowerment and agency, and test an approach to assess the argument’s plausibility. Interactive Architecture (IA) can be broadly defined as an architectural setting computationally enabled to sense its environment and respond accordingly, in a dynamic feedback system. It is still a field that relates more closely to science fiction than to the mainstream production of  architecture. Yet, its study spans over several decades and it appears to be gaining substantial momentum in the last few years, possibly due to the increasing availability of  inexpensive and easy-to-use electronic components. In a previous study (Costa Maia & Meyboom, 2015) I have argued that most recent research in IA are explained by a typical trend in technology development: they are a solution looking for a problem. That is, it seems suggestive that IA has not been fundamentally developed as a direct response to previously identified architectural or social problems and demands. Most investigations are instead rooted on new technology availability, with ad hoc discussion in the context of  the built environment. Cedric Price (1966), whose projects are often regarded as precursory of  IA explorations, comes to enquire: “technology is the answer... but what was the question?”. Fifty years later, the question is still undefined. The precedence of  technology availability over an established demand in architecture has caused the field of  IA to develop disjointedly, with branches spreading towards a number of  possible relevant concerns. In fact, the literature on IA abounds with arguments regarding the social importance of  data-driven adaptable environments; but they are mostly speculative, unverified, and, above all, hardly convergent. In the recent survey I conducted on peer-reviewed publications in the field, I found 27 completely distinct rationales for the importance of  IA (Costa Maia & Meyboom 2015). They ranged from improving inhabitant’s experience of  architecture or optimizing spatial organization (Jaskiewicz 2013); 3  to performing better environmentally and assisting us in better addressing an increasing shortage of  resources, including space availability in urban cores (Kroner 1997); to giving autonomy to populations currently under-addressed by standard architectural settings, such as the elderly or people with disabilities1 (Meyboom et al. 2011).  As Jaskiewicz (2013) points out, however, the potential extent of  such societal impacts of  IA is still undetermined. The reason for this indeterminacy is, most saliently, the limited real-world application that IA has attained in time. But also, perhaps in an egg-or-chicken deadlock, it results from the lack of  research to further understand and validate those assumptions on IA's social benefits2. In fact, the research deficiency in IA goes beyond the lack of  evidence to justify the extra investment represented by interactive features. Very few publications in the field report any empirical evidence at all against their hypotheses, and the vast majority of  arguments around IA, especially the ones relating to inhabitants, is widely unsupported (Costa Maia & Meyboom 2015). This is particularly problematic when considering IA’s intrinsic relation to interaction, use processes and user experience. Only in very rare occasions have IA researchers attempted to study users’ relationship with interactive systems empirically (e.g. Oh et al., 2014). Arguments for the adoption of  evidence-based, user centered design and research in IA exist, and are often referenced. Achten and Kopřiva (2010) highlight the inexistence of  comprehensive design methods available that can support the design of  interactive architecture. The authors then present a framework that incorporates user centered design elements from fields such as interaction design. However, the application of  extraneous methods to design and research in IA can reveal difficulties and complexities that must be addressed. This thesis took an important first step in assembling, testing and demonstrating an inhabitant-centered approach for research and design in the field.                                                       1“Disabilities” are defined in comparison with a shared convention of  what the standard human set of  abilities are; terms such as “functional diversity” are better descriptors of  the intended idea, yet they might not be immediately recognized by the reader. 2 A remarkable asynchrony between IA discourse and prototypical IA projects (Costa Maia & Meyboom 2015) also prevents the rationales presented in discourse to be put to empirical test, on top of  the direct lack of  academic research. 4  The use of  established user-centered techniques from interaction design could provide us with the necessary empirical knowledge on IA’s functioning and social relevance. However, the application of  these techniques needed to be first tested in the context of  IA for a number of  reasons. For one, each available technique is usually only applicable to a narrow range of  situations and must be employed accordingly (Vredenburg 2001). IA also presents its own challenges regarding inhabitant interaction and experience that were yet to be explored in a functional IA setup. Moreover, perhaps even more importantly, the particular development state that the field of  IA finds itself  in must be taken into account, for it determinates which are the most important questions that presently ask for answers.  This thesis studied how existing methods can be employed within the frameworks of  IA, considering the specific challenges and purposes of  architecture, and thus defining an appropriate approach for the field.  More specifically, the present work 1) employed a user-centered design approach to develop an IA apparatus, and 2) conducted a user-centered experience research to test empirically the plausibility of  IA’s claim regarding inhabitant agency. The goal of  this thesis was to test and demonstrate a user centered approach for evaluating interaction in IA design concepts, especially with regard to the possibility of  fulfilling one of  IA’s many untested claims. This goal was accomplished, making explicit the problems and opportunities in the process, and setting the basis for this kind of  exploration in the field of  IA.   1.2 Why inhabitant agency? Each of  the several rationales for IA presented in literature require further scrutiny. They address important topics, but they do not demonstrate, successfully or even tentatively, that IA is an adequate answer for them. Even environmental sustainability, which is the most explored and tested IA rationale to date (Costa Maia & Meyboom 2015), has had the validity of  its arguments repeatedly challenged (Meagher 2010). The critiques focus on IA's need for machine-like maintenance3 as well as its machine-like lifespan, energy consumption and specialized operation, which may hinder the goal of  sustainability in its very pursuit.                                                      3 The mechanical failure of  some of  the irises in the Institut du Monde Arabe is a favourite example of  critics. 5  In my master’s thesis, I wish to explore a less prevalent rationale but one I deem highly pertinent to the domain of  IA, i.e. inhabitant empowerment and agency, as it has been already declared. Its selection among others is justified by: 1) its critical participation in early debates in the field, 2) its conceptual relation with fundamental notions of  IA, 3) a recent upsurge of  interest in (architectural) production democratization, and 4) a personal interest in the political implications of  the topic. Before proceeding to explain each of  these justifications, however, it is important to clarify the problem of  inhabitant agency in IA, as it presents nuances that must be acknowledged. First, the reader must not confuse inhabitant agency with architectural agency. Several authors have directly or indirectly discussed an idea of  agency in IA that refers to architectural agency primarily (Calderon 2009, Adi & Roberts 2010, Jaskiewicz 2013): that is, the possibility of  the architectural setting itself  to actively provoke change in the world. In such instances, IA is typically approached as intelligent and/or autonomous machines. This is not the main concern of  my research. What I refer to as inhabitant agency is related to the inhabitant capabilities only: how the environment enables people to accomplish goals of  their interest, especially regarding the conformation of  the built environment itself. IA systems are thus the facilitators of  inhabitant agency. Negroponte (1975) is one of  the main advocates for inhabitant agency in IA. Interestingly, his proposition is marked by architectural agency as well. For Negroponte (1975), the IA building is an intelligent agent which mediates inhabitant agency. Even when isolating the concept of  inhabitant agency from that of  architectural agency, however, the concept can still be ambiguous. It is so because, as it will be later discussed, agency points towards something else, not itself. It is a value-based approach which depends on inhabitants' capability of  achieving goals and high functioning, rather than relating to specific resources or methods (Johnstone 2007). By definition, human agency is the underlying motif  of  any technology. We create technologies to achieve things we aim to do but that we couldn't achieve otherwise: we can't lift 10-ton weight alone, so we've built machines to do it for us; we can't add up a million numbers without making mistakes, so we've built a computer for that too (Minsky & Riecken 1994); furthermore, we can't comfortably inhabit certain locations due to environmental conditions, so we've built dwellings that protect us from environmental exposure. In IA, the discourse of  inhabitant agency often loses focus amidst such 6  fundamental purposes of  any technology. Jeng (2012), for instance, claims that IA, as well as other fields concerned with technology augmented environments, carry the expansion of  human capabilities as a common objective. Such hardly particular obviousness might be a reason why, despite comprising a rationale for IA, “expanding human capabilities” as a general feature has not been addressed to depth in any publication I have come across. The relevance of  the subject only begins to appear when the problem is framed sufficiently specifically or in a contextual situation. For instance, in computer sciences, user empowerment has mostly been addressed in relation to the environments that allow everyone to take advantage of  technology (e.g. Clement, 1990), promoting democratization of  access to technological capabilities (Blackwell, 2006). In the field of  IA, the broad critique of  empowerment rests in how IA systems can limit rather than expand people's capabilities through hard encoded definitions (Cetkovic, 2012). Thus the discussion of  empowerment becomes relevant in the perspective of  assuring IA systems provide the capabilities that people are interested in. At a more conceptual level, I argue that IA relates to inhabitant empowerment exactly in the fluidity of  people's goals and needs (Costa Maia, Lima and Barros Neto., 2016), which is framed by the idea of  agency as a value-based concept. As it will be later examined, IA discourse has long been centrally concerned with the possibility of  IA to adapt to changing conditions (e.g. Eastman, 1971; Negroponte, 1975; Achten & Kopřiva 2010; Salim et al., 2012; Jaskiewicz, 2013). Thus, inhabitant empowerment in IA is not limited to the generic empowering component of  any tool or technology. While these offer support to only a specific set of  goals, IA would be able to adapt indefinitely, and continuously provide best spatial support to inhabitants' goals. This perspective on inhabitant empowerment through IA, however, is still not explored overtly in terms of  agency. The instance in which the idea of  agency in architecture becomes a central and extensively studied subject is when a system intends to extend human capabilities towards influencing and participating in the formation of  the built environment itself, rather than addressing external goals. That is, when the architecture is able to accommodate in itself  the intention of  inhabitants to influence its configuration. IA literature in this domain of  agency is considerably more specific (e.g. Negroponte 1975), although still minuscule, and it is supported by a rich and vast debate in fields such as 7  participatory design and related areas. Thus, this agency of  inhabitants towards their environment, towards having a say on the shaping of  spaces that concern them, is the central subject of  this thesis. It was the idea of  agency towards one's environment, specifically, that has marked the advent of  IA as a field of  study. IA is inexorably connected to matters of  inhabitant agency and empowerment in architecture due to the context it originally bloomed from. This context, situated in the 1960s and 1970s, is characterized by two main processes: 1) the post-modern critique of  design methods and mass housing, and 2) the development of  cybernetics, which formed the basis of  IA theory. Habraken (1961) explains how well-intentioned modernist4 propositions for the problem of  housing shortage was met with opposition by “the very quarters in whose interest the proposals were made”. People wanted to have freedom and autonomy regarding their dwellings, Habraken (1961) notes, they wanted to have a say. When the iconic Design Participation conference was held in 1971, it accommodated well the initial debates regarding IA. Contributions from some of  the most important pioneers of  IA, such as Charles Eastman and Nicholas Negroponte, demonstrated the early connection between design participation and Interactive Architecture. The easy match between the two fields is explained, to large extent, by IA's foundation in cybernetics. Gordon Pask, a main proponent of  the second generation of  cyberneticians, introduced the relevance of  feedback, systems design and underspecification in architecture. Through systems thinking, IA would allow for buildings to become components of  empowering environments, by integrating the human user as part of  a larger control loop. Pask explicitly claimed that, in IA, “the designer is no longer conceived as the authoritative controller of  the final product”; instead, “an environment should allow users to take a bottom up role in configuring their surroundings in a malleable way”. Haque (2007) also argued that applying Pask's ideas to architecture “is about designing tools that people themselves may use to construct – in the widest sense of  the word – their environments and as a result build their own sense of  agency”.                                                      4 Habraken (1961) reports the conflict around mass housing in the Netherlands in 1918. It is a mistake to assume that Modernist ideas were undisputed throughout its decades of  hegemony. What actually occurs in the post-modern surge is that the criticism becomes central to the discourse of  architecture, although resistance had always been present. 8  Further developments concerning the idea of  interactive participation in media studies also cemented the central concept of  IA – interactivity – as intrinsically concerned with a shift in power towards the users and consumers of  a content. Andrejevic (2009) explains the early advocacy for interactivity and co-creation in the discipline: “[w]hy were scholars so critical of  top-down, one-way, centralized media industries? [...] The concern was not directed solely toward a particular set of  media structures (top-down, one-way, etc.) so much as it was with the way in which these structures helped reproduce power and social relations”. The same political perspective can be drawn for artifacts and buildings. In a well-known argument, Langdon Winner (1986) claimed that artifacts do have politics, as they are “ways of  building order in our world”. Vardouli (2015) complements that “[h]ow artifacts order our world, and who controls, or should control, this ordering, are moral and political questions”. It is therefore crucial to understand IA from its inherent potential of  including the inhabitant in the definition of  the forms they inhabit. As already argued, this was a main constituent topic of  first debates around IA. However, interest in the problem faded after the 1970s. With the resurgence of  IA in the 1990s due to the popularization of  personal computers (Fox 2010), different rationales had occupied the central focus of  the discipline. In my literature survey, no recent paper directly addresses inhabitant agency towards architecture in the context of  IA. The concern only figures more centrally in related fields, such as open source architecture5 and technology mediated participatory design. This thesis will shed new light on this rationale for the social relevance of  IA and will demonstrate an approach to test its plausibility.  1.3 Thesis structure This research intends to bring back the idea of  an IA for inhabitant agency and empowerment, to make the bridge between existing but fragmented research, and to propose an approach to test empirically whether Interactive Architecture can indeed foster agency in inhabitants. However, it can be anticipated that there is an exceptional lack of  base research available to readily support my intents. This issue will be further discussed in chapter two, but it must be alluded to in                                                      5 Open Source Architecture refers to an architectural analogy for Free/Libre Open Source Software. 9  advance because the state-of-art of  IA research and its many gaps has greatly shaped the overall approach to this thesis’ research problem. Firstly and importantly, the research here presented must be considered widely exploratory. Additionally, due to little available information on inhabitants’ overall experience of  IA, first hand research must be conducted to understand the broader scenario of  user experience, before moving towards understanding the experience of  agency specifically. Finally, due to the scarcity of  built IA projects, this research will also need to design, develop and implement an instance of  IA to enable the observation of  inhabitant-IA interaction. The research question guiding the entire process can be stated as follows: Is it possible to apply established methodologies from Interaction Design to Interactive Architecture in order to support evidence-based propositions in lieu of  untested rationales? What are the appropriate ways to do that? Considering the specific interest on the rationale of  inhabitant agency, the objectives of  this study are the following: 1. To review existing research pertinent to the problem of  inhabitant agency in IA, and to organize an appropriate background for the advancement of  knowledge on the topic; 3. To propose and design an instance of  IA and to ensure, through user-centered design processes, the suitability of  the final design. 4. To prototype the interaction components of  the IA instance, based on common IA descriptions, in order to enable empirical explorations of  inhabitant experience. 5. To study and collect empirical evidence on inhabitant’s experience of  the implemented IA project, with a focus on inhabitant agency and empowerment.  6. To report on the research approach, identifying main problems and opportunities, in order to compose a reference for future research.  The approach presented in thesis is not intended to arrive at new ways for fostering inhabitant empowerment through IA, although it will review existing strategies. Instead, it aims at investigating how well the existing conceptual body of  IA, as is, affords one of  its primordial arguments, namely inhabitant agency.  10  In order to ensure an unambiguous understanding of  the discussion, I start by presenting definitions and overviews of  critical concepts that define this study. Chapter 2 covers a thorough appreciation of  the field of  IA, by clarifying main concepts, presenting a condensed literature review, and discussing the relevant connections to the problem of  inhabitant empowerment. Next, chapter 3 covers an overview of  the concepts of  human agency and empowerment from key theories to explore the subject: Capability theory, Self-determinacy theory and Self-efficacy theory. Related concepts are also explored. After an understanding is established of  the basic fields comprehended by this study, chapter 4 will concatenate existing research in neighbouring fields to IA which I believe are highly relevant to the problem at hand. Although the field of  IA itself  presents few related precedents, this can be found in areas such as participatory design, technological mediation, metadesign and end-user programming, apart from the early contributions of  IA authors themselves. This chapter focuses on projects and open problems, reviewing a plethora of  different ideas, rather than providing a structured examination of  concepts. In chapter 5, I explore the different components of  interaction design and perception that might compete to foster inhabitant agency in IA. This chapter is a complementary counterpoint to the previous one. While chapter 4 is comprehensive, chapter 5 makes an argument for placing IA behaviour and interaction models in a central position in this research. Chapter 5 also builds upon examples presented in chapter 4, but with an instrumental interest. It elects, connects and explores the main concepts that will fundament the development of  the IA apparatus design. Chapters 1 to 5 compose the part one of  this thesis, referred to as the theoretical foundation. The next chapters build upon the theoretical foundation to present a contextual approach to user-centered design and research in IA. Chapter 6 defines the research problem to be addressed by the user-centred approach, and lists the specific research questions to frame the empirical study of  inhabitant agency and experience of  IA. Chapter 7 describes the initial stages of  a design exploration process for defining an interactive space concept. Chapter 8 describes an anticipated experience diary study to explore the IA concept proposed in real-world scenarios. This user-centered design study revealed interesting information regarding the 11  potential user needs and user experience of  IA inhabitants, as well as provided information to further develop the IA concept. Chapter 9 presents the finished design of  the interactive space and its implementation inside Lasserre Building, at UBC Vancouver campus. It also describes the process of  prototyping interaction in an IA setup. Finally, chapter 10 describes the IA user experiment, where participants could try an actual interactive space and report their overall experiences and their perceptions of  agency. All the next chapters are presented as described, building a trajectory from general background, to the exploration of  specific supporting knowledge for addressing the research problem, to the culminating user-centered development and testing of  an IA apparatus.            12  2.1 What I mean by interactive architecture in this thesis? Interactive. Architecture. Each of  these words are individually decisive in the definition of  the concept of  IA, and it seems difficult to escape the fate of  introducing them one at a time. Every architecture is interactive, because interactivity is a considerably broad concept. Waugh and Taylor (1995) explain that communication and interaction comprise wide variances, and that they can occur on a scale from reactive to proactive. Thus, simple artifacts, such as buildings, can passively6 react to a proactive human – the building having no internal goals or reference levels of  its own – and still be considered in interaction with that human. However, unsurprisingly, the field of  interactive architecture refers to a very specific form of  interaction and influence. Negroponte (1975) argues that for an environment to be considered responsive (or interactive, in the context of  this research), it must take an active role and it must initiate, to a greater or lesser degree, changes “as a result and function of  complex or simple computations”. Thus, as a first approximation, IA may be defined in the following broad terms: architectural spaces that, enabled with computational technology, are able to understand in varying degrees their environment and occupants, and to provide context appropriate responses actively. Such enabling technologies provide IA systems with three distinct abilities, which are highly dependent on ongoing, interrelated and yet distinct technological developments.  Such abilities are the ones that enable architecture to “read” the environment, including its own state, and its use (through sensors); to process the data and formulate a response (through processors); and to execute a response (through effectors). Between each of  these operations, there is a need for transfer of  information (through wired or wireless communication).                                                      6 In their historic paper from 1943, with substantial repercussion in cybernetic thinking, Rosenblueth, Wiener and Bigelow had already separated active behaviour from passive behaviour, and subdivided active behaviour in purposeful (directed to a goal) and non-purposeful. This paper goes on in its categorization endeavour to describe a long hierarchy of  behaviours, moving on to encompass complex, self-organizing and evolutionary systems, among others. For each system, a potentially different form of  interaction is conceivable. 13  The forms of  interaction in these systems vary, as well as the type of  electronics adopted or the foci of  examination. Different purposes are also explored, which has given rise to a sizeable “terminological inflation” (Glanville, 2001) around the field and the number of  projects that fulfil the descriptions provided so far in this manuscript. Apart from the term Interactive Architecture, some of  the many domains tackling similar subjects in architecture are: Intelligent buildings, Automated Architecture, Reactive Architecture, Responsive Architecture, Transactive Architecture, Smart Architecture, Kinetic Architecture, Robotecture, Architectronics, Hybrid Spaces, among many others. These are by no means mutually exclusive domains. They not only overlap in large extent, as they also often lack clear limit of  scope. Even in the case of  Responsive and Interactive Architecture, the most recurrent terms among these mentioned, definitions were also found to be used inconsistently (Sara Maia & Meyboom 2015) Given the aforementioned obstacle, it is unfeasible to rely on a consensual literature definition to establish a clear perimeter for the field of  IA. Other researchers have come across this difficulty, often opting to coin their own terms as a solution (Lee 2012), and thus worsening the overall lack of  terminological cohesion. Some authors, however, especially the contemporary ones building upon cybernetics tradition (e.g. Park 2013), have adopted distinctions for IA that are well accepted in some circles consistently. Such distinctions focus mostly on the terms “Reactive Architecture”, “Responsive Architecture” and “Interactive Architecture”, and thus on the forms that communication occur. These terms are related to Sheizaf  Rafaeli’s (1988) concepts of  two way communication, reactive communication and full interactivity, respectively.  A responsive system is here defined as a system that responds to an environmental stimulus according to its nature and/or other available data. It distinguishes itself  from purely reactive systems – such as a motion detector light switch – by the ability of  responding not only to a trigger stimulus but also in accordance to context or other trigger-related information. As Negroponte (1975) would argue, the responses are a function of  internal computations. Interactive systems differ from responsive systems in the ability of  the system to learn and/or build upon previous interactions.  Therefore, as argued by Fox and Kemp (2009), Interactive Architecture 14  is defined as architecture in which the communication between the architectural components and the users is a dialogue with new messages being related to the previous ones. In practice, it is not rare to see authors adopting these terms interchangeably. Jaskiewicz (2008) critique the lack of  rigour: “The notion of  Interactive architecture is being commonly oversimplified, by being used to refer to buildings and built spaces which are capable of  simple responsive adaptations and spatial customizations of  various kinds. [...] only consequent replacement of  linear logics that guide their behaviour with an ability to reason and learn [will result] in achieving true interactivity – creation of  spaces which are able to maintain a dialogue with their users, not only responding to their demands, but pro-actively engaging themselves in all kinds of  featured spatial activities”. It makes sense that in order to meet IA requirements of  adaptation to (unforeseen) changing contexts, as posed by many authors, IA needs to have intelligence, learn and adapt, and be part of  the larger ecology, actively negotiating demands and – why not – resources. But importantly, this level of  interactivity has not been achieved yet. Therefore, no IA exists to date to satisfy such requirements. It is not immediately clear to me if  an adherence to such terminological rigour would be beneficial to the exploration of  the topic of  inhabitant agency in IA. I argue that it would be rather counterproductive, for excluding from the debate a large number of  projects and possibilities, without justified benefits. Thus, for the sole purpose of  this research, I will consider herein the term “Interactive Architecture” as an umbrella for both responsive and interactive systems. Relevant publications that chose to frame their research with different terms, such as Eastman's (1971) “Adaptive-Conditional Architecture”, will also be considered as long as they fit the general understanding I propose for IA in this study. So far, I expect to have provided an unambiguous understanding for what I mean by “interactive” (also conceived as the behavioural, techno-centric or procedural aspect of  IA): environments that can change one or more of  its features (i.e. provide physical responses), as a result of  internal computations based on real-time data collected/entered from its inhabitants and environment. The “architecture” part of  the term “interactive architecture”, however, has still not been addressed. It is intriguing that IA authors are remarkably more concerned with the definition of  “interactive” than 15  of  “architecture” in the term, despite the fact that the latter definition is equally important for the configuration of  the field. It is, however, somewhat common that authors separate the two spheres of  the problem, i.e. interaction and architecture, exploring them individually (e.g. Henri Achten 2013, and Mikael Wiberg 2010). If  we look outside the field of  Architecture, the definition of  what the “architecture” in “interactive architecture” stands for becomes even more important. The IA domain falls on the border of  different disciplines and, just across these borders, similar domains have emerged. For this reason, Yiannoudes (2010) proposes the understanding of  these subjects (IA specifically) as ‘Marginal’ objects or, in other words, objects with no clear place, on the lines between categories. From the side of  Human-Computer Interaction (HCI), several studies that fit well inside our definition of  “interactive” in IA exist in areas such as Ambient Intelligence (AmI), Ubiquitous Computing (UbiComp), Tangible Bits, and Smart Homes. Their fundamental difference from IA rests exactly on the definition of  the “architecture” in the Interactive Architecture term. For instance, it must be pointed out that research in AmI and related fields are often interested in the “incorporation of  the physical world into the interaction between human being and computing devices” (Aarts & Encarnaçao 2006). IA, on the other hand, is interested in the incorporation of  computing devices into the interaction between human being and built environment. This is a very fundamental difference, which has excluded several projects from this review. For IA, the architecture, or more broadly the physical environment, is not primarily the medium for other technologies; it is the end in itself. Additionally, the “layers” of  the built environment which fields such as smart homes are concerned with tend to be far more limited in quantity than the “layers” of  interest to IA. Smart homes typically deal with a service layer that includes appliances, lighting and similar add-on systems. IA, on the other hand, may deal with a building's structure, skin, location, plan partition and layout, etc, apart from services and furniture. IA is concerned with the architectural space, rather than specific, detached elements. But what is architecture after all? My argument so far is based upon the cognizance of  concerns intrinsic to the field of  architecture, although these concerns refer to no standard knowledge in 16  architectural theory. I present one broad definition for the reader who is unfamiliar with what might constitute the problem of  architecture. William Mitchel (1990) defines architecture as “the art of  distinctions within the continuum of  space”, a definition remarkably recurrent in post-modern theory. Hillier and Hanson (1984) explain that “buildings are not just objects, but transformations of  space through objects”. According to the authors, architecture constitutes the spatial organization of  everyday life, but it also represents social organization and culture through the physical configuration of  forms. So, after all, what do I mean by Interactive Architecture in this research? I mean environments that can change one or more of  its features, the objective of  which relates to the re-definition of architectural space, as a result of  internal computations based on real-time data.  2.2 Cybernetics and the basis of  interactive architecture theory As it was already introduced, the discussions around IA are not new. They were born in the 1960s and were strongly grounded on a few critical concepts. It is argued that the development of  Interactive Architecture originated from the introduction of  cybernetics in architectural thinking during this period. A main proponent of  this movement was Gordon Pask, who claimed that “architects design systems, not just buildings” (Pask 1969).  With cybernetics, architecture is considered as part of  a dynamic feedback system with users (Sterk 2006a), an idea that continues to offer the basis for our current understanding of  IA. Contemporary cybernetics began in the 1940s, despite its much older roots. Wiener (1961) define cybernetics as “the study of  control and communication in the machine or in the animal”. In fact, the idea of  cybernetics far surpasses the domain of  artificial control systems in machines, with which it is most commonly associated presently. Humberto Maturana, for instance, along with Francisco Varela, were biologists with lasting influence in architecture. They are well known for creating the term "autopoiesis", which originally refers to the nature of  self-maintaining feedback mechanisms in living systems. 17  The concept of  feedback is a central notion to cybernetics. From a Control Systems theory perspective, Goyal (2008, p. 8) defines feedback as follows: “feedback is a property of  the system by which it permits the output to be compared with the reference input so that appropriate controlling action can be decided”. The cybernetics notion of  feedback is to this day the main theory behind a few human motor behaviours (Schomaker 1995) and other general goal-oriented behaviours. In psychology, for instance, theories such as the Feedback Intervention Theory (Kluger & DeNisi 1996), the goal setting theory (Latham & Locke 1991), and the control theory (Carver & Scheier 1981), argue that behaviour is regulated by comparisons to preexisting or intervention-provided goals or standards. As Karlin et al. (2004) explain: [These theories] assert that behaviour is generally goal directed and that people use feedback to evaluate their behaviour in relation to their goals. When behaviour differs from the standard, this creates what they call a feedback-standard gap, and it is the desire to decrease this feedback-standard gap that mediates the effectiveness of  feedback”. For such a description, it becomes evident that feedback, and consequently cybernetics, are highly goal-oriented. An output cannot be fruitfully compared with a reference input for decision making if  no internal goal or reference exists. This understanding is very relevant to our discussion of  inhabitant agency and empowerment in IA. As it will be later explained, agency can only be discussed in relation to a subject's goals as well as matters of  high level functioning. When we talk about machines in cybernetic systems, however, the machine themselves are typically conceived with goals of  their own, and the users are not the only party with goals. Thus, if  IA is realized as a cybernetic system, the ways in which the inhabitants' goals will influence and converge with IA's goals must be the thing to determinate possible levels of  empowerment. This idea will be further explored later on. Pask (as quoted in Bateson 1991 and Haque 2007) explains the notion of  goal-oriented machines: “It seems to me that the notion of  machine that was current in the course of  the Industrial Revolution – and which we might have inherited – is a notion, essentially, of  a machine without goal, it had no goal ‘of ’, it had a goal ‘for’. And this gradually 18  developed into the notion of  machines with goals ‘of ’, like thermostats, which I might begin to object to because they might compete with me. Now we’ve got the notion of  a machine with an underspecified goal, the system that evolves. This is a new notion, nothing like the notion of  machines that was current in the Industrial Revolution, absolutely nothing like it. It is, if  you like, a much more biological notion, maybe I’m wrong to call such a thing a machine; I gave that label to it because I like to realise things as artifacts, but you might not call the system a machine, you might call it something else.” In the field of  Interactive Architecture, different authors will conceive IA as different systems. IA may be conceived as a system with defined goals, or with user configurable/influenceable goals (e.g. Eastman 1971), which configures first-order cybernetic systems. IA may also be conceived with undefined and evolving goals (e.g. Sterk 2006). These systems comprise a learning system which nests the first, self-regulating it. They therefore configure second-order cybernetic systems. Higher-order systems, demonstrating characteristics such as autonomy and intelligence, are also part of  the IA repertory (e.g. Negroponte 1975). Authors with explicit “Paskian” references will most often base their explorations on the use of  underspecified goals and second-order7 systems (e.g.  Haque 2007, Jaskiewicz 2008). In fact, the common IA and cybernetic reference to “conversation” can only be addressed by machines capable of  learning. The following images (Figure 1 and Figure 2), produced by Dubberly et al. (2009), describe the functioning of  different systems based on cybernetic concepts.                                                       7 The term “second-order system” also refers to any higher-order system, regardless of  the number of  nested levels in the system. 19      Cybernetics is not the only influence on IA development, but it is most certainly the primordial one.  Yet, several recent authors will completely disregard cybernetics and cybernetic concepts in their approach to the field. For this reason, I did not include the notions discussed in this section as integral Figure 1- Types of  systems in different cybernetic systems. Adapted from Dubberly et al. (2009). Figure 2 - Types of  interaction in different cybernetic systems. Adapted from Dubberly et al. (2009). 20  part of  IA definition, choosing instead to accept a broader understanding for what is being currently studied under the umbrella of  interactive or responsive environments. The following section will provide an overview of  the field. It is my expectation that such an overview will assist in clarifying the trajectory of  IA, the domains it has explored, the kind of  research being developed and the challenges being approached. In sum, a definition for IA that goes beyond a demarcating statement or an aggregate of  concepts.  2.3 A portrait of  the old new territory of  interactive environments The very first explorations of  technology-enhanced environments were speculative descriptions and representations. As early as 1914, Italian futurist Antonio Sant’Elia wrote of  buildings “similar to a gigantic machine”, a vivid manifestation later curated by Conrads (1970) and others. The actual assembling of  environments with embedded computing also precede the formation of  IA as a body of  exploration, and it might date back to Le Corbusier’s Phillips Pavilion for the 1958 Expo (Mayboom et al. 2011). As already argued, however, it was only with the introduction of  cybernetics in architecture that IA starts to emerge from a broader machine analogy. In 1967, for instance, Warren Brodey makes use of  cybernetic concepts to explore a notion of  intelligent environments. In 1969, Andrew Rabeneck wrote in the Architectural Design magazine about the use of  cybernetic devices in automated architecture (Sterk 2006a). Rabeneck advocated for building technologies that were flexible, an agenda that was gaining particular strength in the period. Two years later (1971), Charles Eastman published his Adaptive-Conditional Architecture model, which reinforced the proposal that “feedback could be used to control an architecture that self-adjusts to fit the needs of  users” (Sterk 2006a). Importantly, this concept of  adaptability to users’ needs is perhaps the first social purpose explicitly justified by IA potentialities, a rationale that continues to permeate a significant number of  IA arguments. Around the same period, Nicholas Negroponte (1970) coins the term responsive architecture. Negroponte is concerned with the legitimacy of  top-down design, and focuses his discourse around this critique. Negroponte's work have a great influence from Pask, which is manifested in both his writings and his projects with The Architecture Machine Group (Negroponte 1975). 21  I believe that Eastman and Negroponte represent the two different foci that emerged in the field of  architecture from the incorporation of  systems theory and computing developments during the late 1960’s and early 1970’s, with similar yet slightly contrasting approaches.  The first focus is illustrated by the writings of  Charles Eastman. In 1971, when Eastman published his Adaptive-Conditional Architecture model, he presented schemes demonstrating that feedback could be used to control an architecture that self-adjusts to fit the needs of  users. He argues that “the form of  a well-designed physical environment reflects in detail the structure of  the activities carried out within it”. Thus, he advocates for an architecture embedded with feedback mechanisms8 that allows for optimized environment-activity “fit”. For Eastman, “fit” is understood as the relative amount of  effort required (in physical, psychological, social or economic terms) to carry out certain patterns of  human activities in a particular environment. Thus it can be argued that Eastman’s approach is mostly concerned with the resulting configuration of  a space and how well adapted it is for the needs and requirements of  a certain user, engaged in a certain activity, in a certain moment of  time. Eastman (1971) was already concerned with the morality of  designers imposing their values on the configuration of  “fitness”, thus he stressed the importance of  the inhabitant’s inputs in the calibration of  the architectural machine. He had also considered the political aspects of  spaces, by acknowledging that the activities and interests of  different actors in space can be conflicting: Because the level of  support for different activities can change, the fit to be provided for controversial activities becomes a political issue and can be settled by political processes; the same issue may be revaluated and changed many times and the architect need not become the arbiter of  social conflicts (Eastman, 1971). In either case, however, his ultimate concern was with achieving the best possible fitness for the human inhabitant. The second focus around cybernetics in architecture can be represented by Nicholas Negroponte. In his highly influential work, Negroponte had a more explicit political positioning than Eastman, and                                                      8The general steps necessary to construct the mechanisms described by Eastman  are: (a) develop the input mechanism by which the user communicates his preference; (b) identify the critical variables that vary according to individual preference; (c) develop the appropriate control algorithm that alters outputs so as to reflect the inputs of  the user. 22  was a great deal more concerned with processes and political structures than the objective qualities of  a resulting space. In Soft Architecture Machine, from 1975, he consistently reaffirms the value of  designing environments that are responsive to their inhabitants, in a process that increasingly removes the architect as a middleman. “The theory”, he says, addressing the use of  computers in participatory design, “is that I can be the best architect for my needs, and I do not need a paternalistic human or mechanical architect to dictate my decisions” (Negroponte 1975)9. Negroponte's approach might be diametrically opposite to a performative approach to architecture, which later became a common area of  investigation in IA. Negroponte is concerned with architecture as a language, as meaning, a very different perspective that is highly dependent on context rather than objective parameters. “Rather than viewing the built environment as an efficient corpus of  concrete, steel, and wood, let us consider it to be a language”, he suggests. “This would imply that my behavior within the built environment and the meaning I attach that environment are as important as (I really believe more important than) the physical thing itself ” (Negroponte, 1975). The work of  Eastman, and especially the work of  Negroponte, are important references for the present research. They will be continually evoked throughout this manuscript. However, these authors are far from the only ones discussing IA in its early days. Nor are their theoretical work the only significant type of  work being conducted.  Notably, design speculation (or visionary architecture, as it may be called) became a very strong front in early IA development, since a practical exploration of  IA could not be fully realized in built projects. With the Archigram group, speculative projects such as the Fun Palace, designed by Cedric Price (Figure 3) and assisted by Gordon Pask (Haque 2007), or the intriguing New Babylon by Constant Nieuwenhuys (1972), became icons of  Interactive Architecture. In fact, it can be argued that some of  the most relevant early IA works were speculative in nature. Currently, still, speculation is very lively in IA’s discussions (e.g. Fox's 2010 description of  the possible impact of  future nanotechnology in IA).                                                      9 As it will be later analyzed, the removal of  the “middleman” in the configuration of  spaces starts to become less coherent when Negroponte starts to address intelligent architecture. In his proposals and considerations, Negroponte contradicts some of  his previous arguments. 23   Cedric Price’s Generator is an example of  an early practical project attempt, in opposition to the Fun Palace proposition, which had a more speculative nature. It is described in detail regarding hardware and software, and was designed to be the world's first intelligent building (Santo 2012). However the project was never built. According to Sterk (2006b), in the mid 1970’s “architects struggled to build the computational and structural systems needed to implement their new architectures”, which led to an early hibernation of  the field. It can also be argued that the upsurge of  an anti-technological postmodern thinking was an important contributor to this discontinuation (Jaskiewicz 2013). It is only in the 1990s that research around interactive spaces regains strength. This fact is due to the unfolding of  personal computers, as well as the technological and economic feasibility to implement wireless networks, embedded computation, sensors and effectors (Fox 2010). Given the technological accessibility, the most relevant research in the field turned largely practical. Kas Oosterhuis (2003), for instance, opposed speculative approaches to IA, advocating that research should be “based on immediate practical possibilities”. His group, the Hyperbody, has produced a considerable amount of  projects and research in the field, possibly more than any other contemporary group. As already mentioned, this resurgence of  IA was more diverse and less grounded on cybernetic concepts than it once was. It surfaced from a different context, with some researchers seeking to keep roots in the explorations from the 1960s/1970s, and some researchers describing brand new backgrounds. Figure 3 - Fun Palace, by Cedric Price. Source: Price (1961). 24  In a recent survey I conducted on peer-reviewed publications in the field, I found 27 distinct rationales for IA (Costa Maia & Meyboom 2015), which start to describe the spectrum of  IA research. The following list reproduces the micro-groups of  rationales as identified by the aforementioned survey: 1. To provide assistance/support for inhabitants in performing activities. 2. To improve comfort/quality of  living of  inhabitants. 3. To adapt to changing needs of  inhabitants. 4. To increase flexibility of  architectural spaces. 5.  To adapt to different people, or to maximize person-environmental fit. 6. To promote sustainability (ample). 7. To adapt to changing environmental conditions, or to improve environmental performance. 8. To minimize use or maximize rationalization of  resources. 9. Energy efficiency. 10. Spatial efficiency. 11. To deliver intended functionality/performance under varying conditions. 12. To improve performance (unspecific) 13. To find best fit formal solutions for both user activities and environmental changes. 14. To mediate the environment. 15. To adapt to changing social conditions. 16. To facilitate social connections. 17. To promote connection or engagement with the environment. 18. To promote new kinds of  interaction between people and environment. 19. To promote new sensory/spatial/aesthetic experiences. 20. To fulfill possibilities and demands posed by technology. 21. To use architecture as an interface for digital information and virtual embodiment. 22. To promote inhabitant participation in construction/behaviour of  environment. 23. To expand human capabilities. 25  24. To continue parametric modeling qualities into the built environment. 25. Paradigmatic shift towards performative architecture. 26. Paradigmatic shift towards ecological integration. 27. Potentially solve several contemporary problems (open).  The use of  the rationales under the term “Interactive Architecture” and “Responsive Architecture” is illustrated in the figure below (Figure 4), adapted from Costa Maia and Meyboom (2015). It demonstrates that the rationales listed above present scattered use, without clear trends or strong prevalence.  Figure 4 - Matrix of  justifications found in publications addressing Interactive Architecture or Responsive Architecture (exact term). Adapted from Costa Maia and Meyboom (2015).  Figure 4 illustrates objectively the lack of  a unified stream responding for the title of  “interactive architecture”, which has been repeatedly observed by others. Schnädelbach (2010), for instance, 26  concerning design projects, notes that IA “ranges from designs for media facades to eco buildings, from responsive art installations to stage design”. Apart from cheer rationales, several of  these applied works and projects seem to provide an informing sample of  what has been driving recent research in IA. A significant branch of  experimental studies, for instance, is engaged in exploring formal capabilities of  new materials, anticipating their large-scale application to buildings, but without clear architectural demand (e.g. Biloria, 2012; Parlac, 2013). This kind of  research focuses on the “ways” possible for different “means”, as these terms are defined by Fox and Kemp (2009)10. Other efforts resort in the proposition of  intelligent and autonomous self-assembling components. Taro Narahara (2010) is one of  these researchers, as he investigates and advocates for the design of  “universal components that can tolerate technological, environmental, and circumstantial changes over time”. In this line of  thought, “emergence” becomes one popular concept within IA. In the theoretical background domain, researchers like Davis and colleagues (2011) intend to situate responsive architecture in the wider continuum of  digital architecture by approaching responsive systems as an extension of  parametric architecture. Parametric models, they argue, can adjust geometric models in response to real-time data, but must be “frozen” at a given configuration in order to be physically constructed. Responsive systems, in contrast, would allow a building to maintain its flexibility in face of  changing data and parameters.11 Researchers and designers are also trying to explore new areas in the intersection of  architecture and digital technology. Wiberg (2010) is one of  these researchers concerned with the concept of  media spaces, which “stretch and connect places”, in the “ongoing integration of  digital technologies in our built environment”. Entertainment and art have also started sharing new borders with media and IA domains (e.g. Bongers 2002), often dissolving these distinctions.                                                      10 According to the authors, the “ways” are the kinetic methods by which the system performs, including spatial actions such as folding, sliding, expanding, shrinking, and transforming. The “means” are “the impetus for actuation” and uses pneumatics, chemicals, magnetism, or electrical systems, among others. 11 Limitations that both parametric design and interactive architecture share can be quickly realized. Responsive and even Interactive systems can only perform the procedures that have been predicted by system designers, limiting their capability of  adapting to unforeseen conditions. Kilian (2006) points out the same issue with parametric models, which can only accommodate change when it is described within the current problem definition. A need for drastic problem reformulation that requires the algorithm to be altered might cause the parametric model to collapse. 27  Intelligence and animacy continue to be important topics within IA, which Santo (2012) explains as a “culturally-defined human tendency to challenge the boundaries between the animate and the inanimate or the human and machine”. It is, however, around sustainability issues that recent developments in IA tend to gravitate. The most established area within IA application is that of  systems designed for responding to environmental conditions and for ensuring energy efficiency. It is also perhaps the most demand-oriented niche in IA, nested in environmental sustainability requirements and pushed forward by a “green building” agenda. IA appears as an extra layer in the larger sustainable buildings scenario, by adding to energy intelligent systems the contribution of  morphological adjustment and adaptive façade elements. After "Sustainability and Environmental Conservation", a slight prevalence of  "User-Centered Architecture" rationales can also be observed in the survey by Costa Maia and Meyboom (2015). As already discussed, this was a very fundamental concern that structured the emergence of  IA as a field in the 1960s. The impossibility of  conventional buildings to adapt to changing conditions, especially users' needs, is still very central to IA discourse (e.g. Achten & Kopřiva 2010, Salim et al. 2012, Jaskiewicz 2013). However, these authors do not address this mismatch between inhabitants' changing goals and conventional unresponsive architecture in terms of  empowerment. Furthermore, despite the popular adoption of  user-centred rationales for IA, the need for an actual understanding of  the inhabitant-environment relation in IA spaces is significantly neglected. This is reflected in the types of  research design found in the field. Several of  the published works in the recent years, specifically 41.6% of  the peer-reviewed ones (Costa Maia & Meyboom 2015), are project-based research that strictly present IA prototypes and describe their behaviour (e.g. Goulthorpe et al., 2001; Narahara, 2010; Pan & Jeng, 2010; Biloria, 2012; Parlac, 2013). Their logic follows the architectural projects tradition of  documenting formation process and final products. However, they are not typically concerned with providing rigorous performance results of  such projects, especially regarding how users interact with and respond to the prototypes. Only 5.2% of  the publications present any form of  experimental research designs intended to support either theoretical propositions or design practices in the field (Costa Maia & Meyboom 2015). 28  This is an interesting gap, once observed the theoretical basis of  IA, both old and new. For instance, Jaskiewicz (2013) attempts to translate the different worldviews of  IA and traditional architecture in the following terms, among others: Users are in the centre of  the development and operation of  any IA process, in opposition to traditional architecture where mostly designers, developers, engineers and stakeholders determine the spatial organization and qualities of  the built environment. However, contrary to this statement, users are commonly left out of  the typical research in the field, being only referred to in IA’s conceptual discourse. Case studies of  a few prototypical installations and buildings also exist, but even these lack the focus on user experience. Achten and Kopřiva (2010) denounce this very problem, and propose the incorporation of  HCI design methodologies as a solution. As demonstrated by the current section of  this manuscript, however, the topics addressed by IA are many and it is not the purpose of  this thesis to explore each of  them individually. Nevertheless, it is important to point out the weak figuration of  agency among the rationales found in peer-reviewed publications. Even for the few authors that mention the issue, their advocacy is timid and their contributions towards the problem of  agency in IA are barely significant. The content of  the few publications that seem to support the idea of  inhabitant agency will be discussed in later chapters. Lastly, it must be mentioned that the survey by Costa Maia and Meyboom (2015) shows a steady increase in the number of  publications addressing IA in the last decade. The expansion of  the field is also illustrated by the main Computer Assisted Architectural Design (CAAD) conferences around the world: ACADIA 2013 had responsive, intelligent, interactive, and reconfigurable architecture as its main conference topic; and CAADRIA, eCAADe, SIGraDi and CAAD Futures have also consistently kept the topic of  Interactive Architecture among their covered themes. As the field gains more weight, and as we’re once again faced with the enthusiasm of  an imminent shift to the way architecture is conceived, the question remains: what is the real social relevance of  IA? To what extent can we robustly support them with existing research? The answer will inevitably point to the urgent need of  a better understanding of  the potential social impacts of  interactive environments. This thesis will endeavour to contribute to an improved understanding of  at least one of  IA’s core rationales: that of  inhabitant agency. 29   2.4 Under all the enthusiasm: a critique of  interactive architecture Since very early in the development of  IA as a field, the description of  a new world where buildings have evolved alongside a futuristic society to assume new functional and social roles has populated the imagination of  architects. This expectation is justified by two reasons: first, because it is known that technology has the potential to catalyse profound cultural transformations; second, because IA carries the potential to cause unprecedented shift to buildings’ capabilities, which have otherwise evolved at a very conservative pace. Several authors and researchers (e.g. Nieuwenhuys, 1972; Novak, 1996; Calderon, 2009) have focused on the understanding that IA (and digitally-driven architecture, more broadly) will further support the development of  a new information age society, pushing forward new demands and requirements for architecture. It is an anticipatory view, given buildings have changed little since the introduction of  those concepts. The experience of  Kas Oosterhuis sheds an interesting light on this topic. Oosterhuis has been a pioneer in the design of  IA and, more specifically, in the development of  intelligent, sentient spaces. In an interview with Greg Lynn (2014), Oosterhuis discusses the repercussion of  his famous project Muscle NSA: “We did many of  those prototypes […]. In those days, we were still hoping for clients, but in the world outside the university, they didn’t come. That was against my expectations. I actually thought that three to five years after you launched such concept, they would come. That didn’t happen […]. It’s sort of  disappointing, but it’s also a reality check. You have to work with the world around you”. It does not take much to realize that IA has struggled to find its way from extravagant speculations and lab prototypes into the real world. We only need to look around to find that IA, after all these years, is not yet here. Perhaps, as already argued, the only niche where IA concepts may have had some taste of  realization is that of  climate-responsive architectures. It is possible that computer-enabled actuation of  form has found in green buildings a significant real world demand and, most saliently, market application. 30  Energy efficiency is certainly a huge demand challenging architecture presently (although no robust evidence suggest IA to be a competitive response to it), but it is not the only one.  Sustainability itself  has been expanding to include a number of  social, economic and technical aspects beyond energy and material optimization. In urban centres, which continue to attract ever-larger shares of  the world population, living spaces are becoming increasingly limited resources. Permeable soil is reduced to a minimum. Public spaces and different urban zones continue to stage the struggle of  contested spatialities. Architecture’s mandate to maximize well-being and efficiency often conflicts with needs for identity preservation and values of  affective nature. Moreover, the critique of  the paternalistic designer still finds its place in contemporary disputes, strengthened by new research findings (Vardouli 2015), and continues to call for further integration of  the inhabitant in the formation of  their environment. These, among many others, are already existing demands to the built environment whose solutions rest inconclusive. They are just some of  the endeavours that have become part of  architecture’s continued debates. Most importantly, they are current demands and endeavours that could potentially benefit from IA capabilities. However, despite the decades old academic investment on IA, they do not. As already discussed, IA as a field initiated with the promise to promote buildings’ adaptability to users’ needs. This argument was continued in discourse, for it finds resonance with contemporary problems in architecture. However, it is a discussion that goes on feeding on wild declarations and no empirical evidence. Additionally, theoretical formulations and prototypical projects often resort to anticipatory demands altogether. Perhaps given an apparent failure to bring IA to mainstream building construction, research often chooses to focus on a future scenario where the necessary technology has become sufficiently mature and inexpensive to be ubiquitous. I argue, however, that there exists a significant distance between the future world we speculate on and the present trajectory of  architecture. The example of  automation is rampant. Although autonomous systems started being introduced to architecture as early as the 19th century (e.g. elevators), they remained add-on systems that only influenced architecture collaterally. So far, it is reasonable to assume that interactive systems might follow a similar trajectory. The current hype on smart environments, ubiquitous computing and the internet of  things is satisfied by add-on ambient intelligence systems, not justifying the active (and expensive) participation of  31  spatial forms, which persists static. The popularity of  interactive art has also mostly remained restricted to installations; and when applied to buildings, they hardly challenge the solidity of  architecture, as they typically are composed of  façade displays. The trajectory so far thus suggests little integration: robotic tasks might be carried out by independent robotic components, digital information might be conveyed by increasingly sophisticated displays (including the possibility to register information onto real environments), intelligent assistance to daily life might be carried out by independent appliances and equipment, and architecture will remain the static enclosure within which all these activities and systems are organized socially and spatially. The reason for this might be that all these systems’ purposes are not intrinsic to the main problems of  architecture. Meanwhile, given the scale of  architecture, comprehensive actuation of  a building might remain uncompetitive and comparatively expensive. Add-on systems, with their own agendas, are typically the most logical and economical alternatives. I argue that IA will be most relevant when dealing with intrinsic architectural problems. I stress on the need to focus on existing architectural demands, instead of  searching for anticipatory demands that may well be fulfilled by other systems. It is possible that societal transformations, as well as the degree of  technology integration, will fundamentally shift the role and concerns of  architecture. It is possible that matters such as sentience will become intrinsic to the problem of  buildings and spaces in future. However, currently, architecture is faced with challenges much more familiar to architects and to the configuration of  the built environment, which IA must be confronted with. So what is keeping IA from addressing these immediate demands? For once, outstanding research gaps in the field have been systematically neglected. There are very limited efforts put towards addressing specific current demands in architecture and generating evidences regarding the adequacy of  specific strategies towards specific problems. I argue that academic work to provide support for decision-making in the design of  such systems will become increasingly relevant and potentially determinant on the success of  early projects. The lack of  such supporting information might be a key reason for why IA is largely still limited to speculative manifestations, even several decades after the enthusiastic reception of  the concept. 32  Therefore, in this research, I intend to establish a firm understanding of  IA with regard to one specific problem, and test the adequacy of  IA as a solution for that problem. Only through proper scrutiny and support through empirical evidence may we begin to understand the relevance of  IA towards inhabitant agency, or any other rationale of  interest. The next section provides some initial questions regarding the suitability of  IA to address the problem of  inhabitant agency. The entire remainder of  this manuscript is dedicated to the exploration of  inhabitant agency as an existing, latent demand for architecture, as well as the ways in which IA may support such demand.  2.5 But is interactive architecture a good solution for increasing inhabitant agency and participation, after all? In the introduction of  this manuscript, I have already presented the main arguments for why Interactive Architecture is closely related to the problem of  inhabitant agency. Else, although I argue that the demand for inhabitant agency in architecture exists, this is not commonly addressed in IA literature extensively. It is necessary to go to fields such as participatory design to find a well-laid basis of  the problem and a rich research literature to build upon. Chapter 4 will explore this background in more detail. It can be argued, however, that by considering IA as a tool that give inhabitants the chance to participate in the formation of  the architectural spaces they occupy, IA can be included in the broader discussion of  participatory design itself. As so, it inherits the pressing real-world demand that already exists for participatory design. In this section, I do not intend to be overly redundant. I wish only to point the reader towards the existence of  such demand, and synthesize the ways in which IA provides a compelling alternative to conventional participatory design methods. I also wish to highlight some current limitations of  what is known and what has been done. The following table (Table 1) compares IA settings as a new form of  participatory design against conventional participatory design in architecture. It illustrates potential benefits of  IA in addressing a 33  problem that conventional architecture has been trying to deal with for over five decades (e.g. Arnstein 1969), with varying levels of  success.  Table 1 - Comparison of  conventional methods of  Participatory Design and Interactive Architecture in incorporating the inhabitant in the formation of  their environment Conventional participatory design Interactive Architecture Temporally constrained participation events Continuous interaction and participation events Addresses inhabitants' requirements in a specific moment in time Addresses evolving requirements continuously Direct mediation of designer Indirect mediation of designer Limited to initial users Continual integration of new users People participating in the process might not be the party most affected by the design outcomes Necessary exclusive responsiveness to the people occupying a space Difficulty of anticipation of results Real-time & real-world feedback Promotes sense of authorship and participation for people involved (e.g. head of family) Promotes sense of authorship and participation to all inhabitants  Apart from these, it has been argued that the notion of  interactivity in itself  may enclose strong connection to questions of  agency and empowerment. However, all of  these arguments are based on conceptual definitions and theoretical speculations.  Despite the long review of  IA in this chapter, it is hard to arrive at a technical description of  IA behaviour and interaction because true IA systems, at a full architectural scale, are almost non-existent. IA can be prolifically described in terms of  what it is can to accomplish (speculatively), but not how exactly it can accomplish, for lack of  examples. Thus, at this point, any arguments put forth for IA are based on nothing more than conjecture. In fact, it can be argued that IA, in itself, is still little more than conjecture, or than an idea in very early development. An IA system must be defined still to 34  viable details, beyond what is typically available in IA literature, before any judgement can be made concerning its suitability as a response to participation demands. This thesis will define and develop four possible IA systems, based on four models of  interaction loosely described in IA literature (chapter 5). The designs (chapter 7), and especially the functional prototype of  the interaction models (chapter 9), will allow for better-informed discussions on the systems’ suitability. However, in order to carry one any form of  assessment, a proper understanding of  inhabitant agency, as well as of  any links between IA and agency, empowerment, interaction and mediation must be first discussed. The next chapter will provide a better conceptual understanding of  the terms agency and empowerment, which I have been repeatedly employing in my discourse so far. Only after this critical clarification, this thesis will move on to discuss related work and to establish specific interaction models for IA. Ultimately, the question of  whether Interactive Architecture is a good solution for increasing inhabitant agency and participation can only be answered by inhabitants who have truly experienced interactive spaces. This research will foster such opportunity and describe the approach to generate evidence-grounded responses to the matter.          35  3.1 What is agency? The concept of  agency can take very different connotations through different disciplines. There are also a number of  fields and theories devoted primarily to the problem of  agency, such as the Action theory in philosophy and the Capability theory in social sciences. In this thesis, I will adopt the notion developed by Capability theory and related approaches as the basis for my investigation. Before explaining the concepts of  interest to this research in the context I intend to use them, it is important to first explore some of  the different definitions that are recurrent and relevant. They provide context and even assistance in clarifying the concept of  agency we will later build upon. In its most fundamental meaning, agency can be broadly defined as the capacity of  an actor to act on the world. According to Bruno Latour (2005), “anything that does modify a state of  affairs by making a difference is an actor”. Thus, his criterion for identifying an agent is simply the detection of  any difference that this agent may have caused in the course of  some other agent’s action. Such difference does not need to be intentional nor meaningful. Based on this definition, it is clear that agency, in its broad conception, is not limited to humans or even to living beings. Jaskiewicz (2013) follows this logic to argue that agency can be found in any type and any part of  architecture: Once humans erect and begin to inhabit buildings (or any other architectural spaces), these buildings simultaneously begin to have a lasting effect on humans. [...] Consequently, it may be concluded that any kind of  an architectural component [...] can be treated as an agent. To further clarify his argument, Jaskiewicz (2013) indicates that an agent's action may be extrinsic or intrinsic: To give an example, agency of  a human being is normally considered to be a product of  interactions between brain neurons intrinsic to that particular human. An agency of  a chair that this human decides to sit on is extrinsic to that chair, as the chair 36  “makes” the human sit on it not through the processes occurring within the boundary of  a “chair system”, but because of  the human’s awareness of  chair’s affordance and suggestion implied in that awareness that the chair is expected to be sat on. What Jaskiewicz (2013) suggests next in his work, similarly to a few other authors, is that Interactive Architecture may also manifest intrinsic agency, hence creating a system of  multi-agent interaction with inhabitants and possibly other buildings. As it has been already discussed, this kind of  architectural (intrinsic) agency is not a rare focus in IA (e.g. Calderon 2009, Adi & Roberts 2010). Since Negroponte (1975) and before, the perspective of  autonomous, intelligent and acting buildings has been captivating the imaginary of  architects.  When adopting a cybernetic perspective, the idea of  architectural agency can be appreciated even more comprehensively. Assuming every IA system is expected to have some sort of  internal goal, without which feedback structures are not conceivable, then every single IA system will also display some degree of  intrinsic agency, even if  it does not involve complete autonomy or intelligence. Thus, if  every architecture or architectural element can manifest extrinsic agency (in Bruno Latour’s conception of  the term), equivalently every IA setting (as understood for the purposes of  the manuscript12) can also manifest intrinsic agency. The concept of  agency continues to gain specific and distinct characteristics as it moves across fields and theories. In artificial intelligence, agency has continued to acquire considerably specific understandings in time, e.g. in Marvin Minsky’s (1988) work in the Society of  Mind.  However, this thesis' focus is centred on human agency as explored by a defined set of  theories. More particularly, I am interested in the social sciences' use of  the term, which transcends a subject's basic capability of  action on the world and studies it with regard to the social-political structures in which it is inserted. How an IA apparatus may provide the spatial/environmental support to improve an inhabitant's agency with regard to the processes that shape his/her built environment? This is the kind of  question central to my research problem, although it might be influenced by other notions of  agency that have been discussed so far. It is therefore a reasonably complex problem.                                                      12 See chapter 2. 37  It should be noticed, for instance, that even when considering human agency as simply the ability of  a person to modify a state of  affairs in the world, the subject is by no means a simple or well understood one. Metcalfe and colleagues (2010) present a number of  factors known to affect a person's metacognition of  their agency, suggesting that our perception and appropriation of  our own actions is rather inferential. When the problem of  human agency is posed in a social sciences perspective, more convoluted concepts also come into play, such as free will, autonomy, independence, values, moral. Note the presence of  some of  these concepts in Wikipedia’s page13 definition for agency in the social sciences: “agency is the capacity of  individuals to act independently and to make their own free choices, i.e. ability to act on one's will”. In the social sciences context, agency has become a core issue in several social movements, from feminism (e.g. Gill, 2007) to critical pedagogy (Freire, 1970). It has also permeated the discourse from several post-modern art movements to literary theory. The multiplicity and complexity of  the concept prevent me from providing a review of  agency that in any way approximate completeness. This is not the purpose of  this chapter. Instead, I only seek to provide an idea of  the vastness of  current intellectual production that revolves around the concept of  agency. The next section will discuss the concept of  human agency in the specific terms I intend to adopt it throughout this research.  3.2 Introduction to the theories of  human agency and empowerment In this thesis, I will adopt the concept of  agency as it is proposed by the Capability theory. I will also follow Alkire's (2005) suggestion of  making use of  the Self-Efficacy theory and the Self-Determination theory as instrumental approaches to the concept of  agency. In my reference to the Capability theory, I refer most centrally to the work of  the Nobel-prizewinning economist Amartya Sen. Sen’s definition of  “human agency” stands for people’s freedom to act in pursuit of  whatever goals or values they regard as important (Alkire 2005).                                                      13 Wikipedia is an interesting reference in the context of  this thesis, as it allows for a democratization of  how knowledge is structured, presented and disseminated. 38  Johnstone (2007) explain that the capability approach regards agency as a person's “systematic ability to achieve high levels of  functioning (which may or may not be realised in practice)”. He stresses that well-being, subjective satisfaction and access to resources should not be considered primarily in the understanding of  agency, for “we do not value resources for their own sake, but always for some other reason, some type of  activity or state that they enable us to achieve”. Thus, utility and resources are instrumental rather than constitutive to human agency. People's ability to reach their goals though such resources is what constitutes agency in the Capability theory. Johnstone (2007) argues that, by focusing on the means and abilities to achieve goals, we can understand agency and capability irrespective of  the conditions that individuals find themselves in: Consider for instance, two women who both stay at home to raise their children, in one case having voluntarily left a job she enjoyed and in the other case having had no alternative owing to social norms. In terms of  wellbeing alone, there may be no reason to conclude that one woman is better-off  than the other (assuming they value their lives and their time with their children equally, and other factors being equal). A capability analysis looks very different, however, since one woman was able to make and act on a reasoned choice between two valued ‘doings' while the other pursued the only available course of  action and only accidentally ended up with a life that she valued. From a capability perspective, the former state is greatly to be preferred to the latter. Partly there is an underlying functionalism at work here: capability reflects systematic rather than accidental access to wellbeing, and therefore wellbeing is more likely to be sustainable and robust across time and context. (Johnstone 2007) The example mentioned above not only clarifies the term, as it provides an argument for why agency is such an important quality, independently of  other concepts such as wellbeing. Sen specifically asserts that “persons should enter the moral accounting by others not only as people whose well-being demands concern, but also as people whose responsible agency must be recognised” (Sen 1985). This kind of  argument also brings to question the architect's often paternalist role in designing environments and spatial configurations they deem best for the inhabitant. It also draws an immediate connection with IA, in IA's ability to offer inhabitants a sustained say in the design of  space, thus potentially allowing systematic access to environmental wellbeing, rather than to a fixed solution. 39  The description of  agency provided so far, however, is not an operational definition; in my research, I could not find operational definitions or measuring instruments to assess agency directly. Alkire (2005) suggests using autonomy (from Self-Determination Theory) or empowerment as a proxy for agency. Empowerment, according to Alkire (2005), is an increase in certain kinds of  agency that are deemed particularly instrumental to the situation at hand. According to the author, increases in empowerment would be reflected in increased agency (but not necessarily vice versa). Johnstone (2007) argues that the concept of  capabilities is equivalent to empowerment, since “they represent the power of  the individual (or group) to avoid harms and pursue valued forms of  functioning, including crucially the ability to make reasoned determinations of  what is to be valued”. Competence may also be considered an equivalent concept to capability and empowerment, describing a person’s perception that they can do something. The Self-Efficacy theory provides the basis to explore capability and competence operationally. This theory, often referred to as a theory of  human agency (Bandura 2001), is concerned with “people’s belief  in their capabilities to mobilise the motivation, cognitive resources, and courses of  action needed to exercise control over given events.’’ (Alkire 2005).  However, it is argued that a self-perception of  capability or competence may be, as already stated, rather equivalent to empowerment than to agency itself. Autonomy, on its turn, is a construct that greatly approximates Sen’s concept of  agency integrally (Alkire 2005). Autonomy is a concept from the Self-Determination Theory, and it measures people’s perception of  their behaviour, condition and opportunities regarding how aligned these are with their own goals and values. Thus, autonomy is not equivalent to independency: a person can be autonomously dependent or autonomously independent, as these categories are orthogonal to one another. It must be noted that Self-Determination Theory is not focused only in the concept of  autonomy. Alkire (2005) explains that it describes three basic psychological needs that are pre-requisites to well-being: autonomy, competence, and relatedness. Furthermore, Self-Determination Theory intends to be predictive regarding the likelihood of  a person to engage in a given activity. 40  Importantly, none of  these concepts can be directly observed. They must be treated as latent variables, and instruments must be defined to assess the corresponding observable variables, e.g. self-reported levels. A literature survey could not identify validated instruments pertinent to agency and related concepts in the context of  architecture. It is very important that future research will refine and validate survey instruments for assessing human agency in Interactive Architecture. Due to time and other resources availability, it was not possible for the present research to validate the instruments it used in its assessments. This is not a critical problem in this thesis, since its main goal is to demonstrate a user-entered approach to IA. All studies presented here are pilot studies, meant to scrutinize their process and application. However, before these processes are applied to generate valid results, it will be necessary to first validate the instruments to assess human agency and related latent variables. For reference, a few examples are listed below of  questionnaire items intended to assess autonomy in different contexts, using Likert scales for levels of  agreement to expressed statements. These contexts are (A) physical activity classes (Standage et al., 2005), (B) job satisfaction (Broeck et al., 2010), and (C) a virtual reality environment (Jung, 2011). These contexts are unrelated to architecture, but they provide a reference as to how to construct autonomy scales. A1: I can decide which activities I want to practice. A2: I have a say regarding what skills I want to practice A3: I feel that I do physical exercises because I want to. A4: I have to force myself  to do the activities. B1: I feel free to express my ideas and opinions in this job. B2: I feel like I can be myself  at my job. B3: If  I could choose, I would do things at work differently (R). B4: The tasks I have to do at work are in line with what I really want to do. B5: I feel free to do my job the way I think it could best be done. C1: While I was in Second Life, I could choose freely what I wanted to do. 41  C2: I felt that I had a lot of  control over my visiting experiences in Second Life. Based on these references, we can propose the following items in the context of  Interactive Architecture (IA): IA1: I influenced changes to this interactive space because these changes interested me. IA2: I felt restrained in this space to be a certain way or to do certain things (reversed). IA3: If  I could choose, I would have this space organized differently (reversed)  IA4: In this space, I often feel like I have to adapt to the designer’s own ideas on how to conduct certain activities (reverse)  IA5: The things I can do in/to this space are in line with what I really want to do here IA6: I feel free to do my tasks in this space the way I think they could best be done. IA7: I felt strong limitations to my decisions on how to do what I wanted/needed to do in the space (reversed). As for the concept of  competence or capability derived from the self-efficacy theory, a guide is available to instruct on the construction of  adequate scales (Bandura 2006). Some of  the instructions provided by Bandura (2006) are: - Find a specific domain and list all contributing aspects. - Challenges may be graded in different levels; provide sufficient gradations of  difficulties built into the efficacy items to avoid ceiling effects. - Don’t title the scale; the self-efficacy scale is identified by code number rather than by name. Based on the instructions provided and on reference examples, we can then propose a set of  items to measure perceived capability in interactive architecture. The scale below illustrates an example in the domain of  adapting a space to one’s needs.  IA8-a: I can change the space to fit at least one of  my needs IA8-b: I can change the space to fit most of  my needs 42  IA8-c: I can change the space to fit all of  my needs Having the adequate scales to assess human agency – or inhabitant agency, as it refers to the domain of  architecture – and its proxies is a critical and necessary step in order to test the plausibility of  the claim that IA can foster agency. The final construction, application and analysis of  a few scales will be demonstrated in later chapters of  this thesis. However, as already declared, these scales will need to be validated in future research. Due to their proximity, the terms “agency”, “autonomy”, “empowerment” and “capability” might be used interchangeably in part one of  this manuscript, as they will be adopted operationally in complement to one another. Other concepts, however, need to be differentiated. The following section will define important concepts that are not to be considered equivalent to agency.  3.3 Distinguishing agency from other concepts Control is perhaps the most important concept to discuss in relation to IA. That is because an IA system may allow for a space or element to be controllable by inhabitants, to a greater or lesser extent, however this does not translate immediately to an increase of  agency in the terms of  Capability theory. If  a person has control over things that are not meaningful to him/her, control may not reflect in increased agency. Yet, even if  the control provided is not related to any purpose at hand, it may still promote inhabitant agency if  it offers the inhabitant a state s/he values, e.g. the perception of  being in control of  something. Thus, the connection between control and agency will always be mediated by a person's goals and values. Authorship is another relevant related concept. It can be broadly defined as a feeling of  being credited for the qualities of  a resulting outcome. It can be direct or indirect and, interestingly, it can be shared with other people. Authorship also differentiates itself  from control as “I can feel some sense of  authorship for the eventual effects of  some of  my actions, even when my actions are not the proximal causes of  those effects” (Nahmias 2005). Control, even if  indirect, should assume actions to be strict causes of  effects. 43  Each of  these terms is sufficiently complex to generate discussions over a number of  papers, as they have. In the interest of  brevity, I have only quickly introduced key concepts to facilitate their reference throughout this document. In the next section, the relevance of  agency and agency-related concepts in the realm of  architecture will be concisely discussed.  3.4 Is the concept of  human agency applicable to architecture? The Capability theory, among others of  the sort, is primarily concerned with social environments and issues. Sen's work, particularly, is developed around the problem of  poverty and inequality in the world. Naturally, the question emerges: is it pertinent to carry this same discussion and concepts to the field of  architecture? Notably, a concern for agency and empowerment has not been limited in the literature to broad social problems. It has also been approached in relation to more specific processes, such as in the work by Füller and colleagues (2009) on internet-based co-creation activities. However, I have not come across any direct application of  the theories discussed thus far (capabilities, self-determinacy and self-efficacy theories) in the context of  architecture, although empowerment has been discussed more loosely in many opportunities (e.g. Comerio 1987). Therefore, I must make an argument that these theories, and specifically the problem of  agency, are highly pertinent to architecture. As already presented, Hillier and Hanson's (1984) definition of  architecture states that architecture represents social organization and culture through the physical configuration of  forms, thus introducing the close connection between social and architectural environments. However, while in informal or vernacular settlements the incorporation of  cultural and social organization into spatial structures is carried out as a collective enterprise, conducted by the very people in whose interest construction is made, in “modern” cities this process is often governed by gatekeepers. This is not to say that the gatekeepers are not part of  the society, but they are hardly representative of  the collective. 44  This kind of  critique to traditional gatekeepers has been historically illustrated by the 20th century subversion of  the so called high art or erudite art. It is also beautifully crafted in Terry Eagleton's (1996) arguments against the presumptuous activities of  intellectuals and academics who elects which works are to be considered proper literature and which are not. Regarding the formation of  the built environment, gatekeepers may or may not be architects. However, if  we analyze the architect-society relation specifically, research has been generating intriguing findings. For instance, Brown and Gifford (2001, p.93) found that “architects as a group cannot predict the public’s aesthetic evaluations of  architecture”. This reinforces the argument that architects are not representative of  the broader community. In contemporary cities, architecture still translates the modus operandi of  an organization and/or society. However, as already argued, this translation is often not made by the same people who will inhabit the artifacts they compose. Nevertheless, these artifacts are embedded with control frameworks that regulate their use and occupation (Akrich 1992), building order into the world (Winner 1986). In sum, architecture embeds the social structures that agency theorists are mostly concerned with. However, it typically reproduces these social structures through the mediation of  designers. Thus, through this dynamics of  incorporating and reproducing, architecture is a rich field to discuss agency in its social and political implications. Without evoking agency specifically, Sean Wellesley-Miller (1971) describes the difference between vernacular and professionally designed environments, by considering them online and offline systems respectively. He explains:  A crucial feature of  an on-line process is the importance of  the time parameter, that requires all events to take place in real time. The formation of  a socially-evoked environment is a time-dependent or ‘historical’ process, with all that this signifies in terms of  involvement and meaning. This is something that tends to be completely absent from professionally designed environments as far as its future occupants are concerned. Consequently, even if  the structure of  the environment arrived at by each design process proved to be identical, the on-line process would almost certainly invest the environment with more ‘meaning’, simply because of  the mode of  its formation. 45  Wellesley-Miller’s (1971) description reaches a conclusion that is remarkably similar to the example presented by Johnstone (2007) on the two mothers, cited in section 3.2 of  this manuscript. Agency is the mediator of  how people perceive the outcomes of  online and offline formation processes in Wellesley-Miller’s argument. Furthermore, I will also present an example to support the argument that the architectural space is an arena of  socio-political arrangements and conflicts, which greatly call for the pertinence of  inhabitant agency. This example, by Malard (2002), is placed in a classroom environment, which Self-Determinacy academics have repeatedly explored, although not in an architectural context. Malard (2002, p. 248) expose what she refers to as the physical-spatial manifestation of  an event in the following instance (free translation): For example, a lecture is the social form, the manner in which a group transmits knowledge institutionally; the room with student desks turned towards the person who will lecture is the physical form meaning "lecture hall" to the subjects that belong to such a culture. The spatialization of  "lecture" is not only a layout. It has some meanings imprinted in it: all student desks are turned to the same side, suggesting that the attention of  these people will be directed to that point; on the wall on that side there's a chalkboard, showing that written and graphic components are part of  the activity; in front of  the student desks and beside the chalkboard there's a desk where will sit the person to which all should be attentive; this desk is greater than the student desks and also occupies a greater relative area, which means that the person occupying it will be outstanding in that context; if  there is someone in whom all others pay attention, that person is definitely more important than the others, in that group. Finally, a spatialization reveals not only the organizational structure of  an activity but also the community power structure. As we have seen, in the spatial arrangement of  the furniture and equipment we can "read" the lecture activity, with all its implications of  pedagogy of  the one who knows and the ones who learn. The following image (Figure 5) illustrates two different “spatializations” of  activities in classrooms. In the left one, the layout translates and endorses a dynamics where a lecturer knows and transmits his/her knowledge. In the right one, the layout translates and endorses a dynamics where everyone has something to add, and knowledge is shared collectively. 46   Of  course, these symbolic relationships in space are culturally dependent and fluid. Regardless, however, the spatial manifestation of  events is typically imposed in a top-down manner. In the classroom example, the students, who are the ones to benefit from the activities taking place, often do not find physical environments responsive to their goals and values. The teachers are also not typically involved in the architectural definition of  the classroom either. The pedagogy imprinted in the space through design is someone else's: the school board, the architect, the gatekeepers. This discussion will continue when relevant. In this section, it was my intention to present the arguments for why agency, as approached by the social sciences, is also very pertinent to architecture and design. I have also argued, in the previous chapter, that I believe IA to be an adequate field to explore the problem of  inhabitant agency. Although it is by no means the only one, I anticipate that it does provide a number of  advantages and potentialities when compared to conventional alternatives. In the next chapter, I will discuss agency in the specific context of  Interactive Architecture, presenting an initial framework to the approach of  the topic.  3.5 Further considerations about agency and architecture From a pragmatic standpoint, architecture is an infrastructure to support human activity. Thus, architecture provides the supporting environmental apparatus to allow people to perform their activities and pursue their needs and goals. Figure 5 - two different “spatializations” of  activities in classrooms: lecture (left) and discussion (right). 47  As such, architectural elements and space may be considered as resources in Capability theory. Johnstone (2007) makes a similar suggestion for technology in general and computers in particular. Although resources are not an end in themselves, they allow us to achieve goals and desired levels of  functioning. When considering IA, however, resources may be of  two different kinds. They might be (1) related to space itself  and what that space allows inhabitants to do in it, either physically or psychologically, or (2) related to the computational technology embedded in the space and how that technology might expand inhabitant's abilities. The first kind being more architectonical, whereas the second kind first requires an expansion of  the role and scope of  architecture as it is currently defined. Johnstone (2007) builds upon philosophers of  cognitive sciences to suggest that “technology is identified with tools and techniques by which we use the world to extend our powers”. These external powers, he argues, can work as important resources in achieving valued forms of  functioning. The idea of  empowerment through computers have been repeatedly discussed (e.g. Weller & Hartson 1993), although without a strong theoretical basis around agency. In architecture related fields, this perspective seems to be the main focus of  AmI and smart home systems. That is, to expand users capabilities in ways that the environment couldn't support before, through embedded technology. As suggested, IA may also be able to perform similar assistance (e.g. Adi & Roberts 2010). If  we focus on Eastman's notion of  IA, however, the discussion of  agency regarding this pragmatic view of  architecture will be grounded in the capabilities related to more typical architecture scope. We can explore this by using the example of  a person in a wheelchair. Considering movement and circulation to be a critical activity to be supported by any space, wheelchair users may feel debilitated where space is constantly inaccessible and/or dangerous for them. On the contrary, they may feel empowered in a space with leveled accesses, wide doorways and adapted fixtures, where they can freely carry out their activities and approach their goals. This example is not only about physical support, but it is also symbolical in its segregation. In that regard, our environment is designed to fit the needs and abilities of  a majority group, while 48  compromising the needs and abilities of  functional minority groups14. Furthermore, architecture can be designed to support or demotivate a number of  activities, both generally or for specific groups. These examples falls inside the implications of  space configuration itself, their effect on people, and how they support or repress agency with regard to people's valued goals and states. Although this discussion applies to architecture more broadly, it still supports a case for IA in increasing human agency. It is so because, in all cases mentioned, interactive architecture may allow for systematic rather than accidental access to wellbeing. This discussion can be continued by integrating Negroponte’s (1975) discourse as a means of  approach. He considered the access to responsive and meaningful built environments “as important as the right to good education”. By focusing on processes and their political implications, this approach shares grounds with the “Free/Libre, Open Source Software” movement in computer sciences. This movement exemplifies “both a new model of  production and a social vision, building on the emancipatory potential of  non-hierarchical and egalitarian production where individuals and collectives can access, modify and distribute the technologies they use” (Vardouli & Buechley 2014). This approach is also more openly against the paternalistic role of  architects and of  architecture. It aligns with the already cited argument by Amartya Sen’s where he claims that ‘‘persons should enter the moral accounting by others not only as people whose well-being demands concern, but also as people whose responsible agency must be recognised’’ (Sen 1985). Agency towards architecture, as advocated by Negroponte and many others, has been linked to several benefits that exceed the benefits of  straightforward environmental fit. It is related to the development of  place attachment, which in turn encourages use, promotes safety and boosts pro-environmental behaviour (Scannell & Gifford 2010). There are evidences it might result in higher satisfaction and valuation (Franke, Schreier and Kaiser, 2010). It might even lead to higher perceived group cohesiveness and job satisfaction in the workplace (Lee and Brand, 2005), as well as better                                                      14 architecture can also be deliberately designed for subjugation, such as the Panopticon (Bentham 1843) and settlements in occupied territories (Segal and Weizman 2003), with mechanisms that go beyond physical constraints. 49  performance and favourable job attitudes (Gagné and Deci 2005). Finally, agency15 towards environmental conditions may reduce people’s discomfort with pain (Geer, Davison & Gatchel 1970), noise (Corah & Boffa 1970) and thermic levels (Paciuk, 1990) when compared to situations with identical levels of  these stimuli but where no option of  control is perceived. Some of  these benefits might be considered an indirect consequence of  agency, intermediated by the role of  authorship and control. I could not find any research accounting for the possible confluence of  agency, control and authorship as confounding factors, or measuring their specific roles, in the results I refer to in this section. In the next chapter, I discuss a number of  precedents related to agency in architecture. They do not directly provide an improved understanding of  the concept of  agency because they were not directly developed around such concept. However they do bring about relevant, although fragmented, considerations, which will assist in a more complete understanding on the problem of  human agency in Interactive Architecture.                                                               15These studies address perception of  control, not agency; however, I am considering control towards discomforting situations to be a valued asset by people in general, so that increase in control would – in such situations – also determinate increase in agency. 50  4.1 Introduction It is not possible to construct a helpful literature review focused solely on the problem of  agency in Interactive Architecture. Most of  the relevant background information that proceeds this discussion in the field, and approximates it in their concerns, have been already at least introduced. Despite a constant flirtation with the topic, an actual in depth exploration of  the concept of  agency in IA simply does not exist. However, previous discussions related to the problem at hand abound in a variety of  domains. They do not address agency in IA integrally, but they address some specific aspects pertinent to the topic, which can add valuable considerations to the overall discussion. Some specific applications in IA can also be explored in the light of  agency, also adding to the topic. This chapter will try to cover an extensive ground of  fragmented investigations. I try to trace a thread connecting the different topics, but deviations should be expected. After this fragmented research is presented and important concepts highlighted, this manuscript will retake a more organized sequential construction towards the definition of  applicable models of  IA that can be experimentally tested with regard to human experience and human agency.  4.2 A historical overview: including the inhabitant in the loop of  architectural design In the discipline of  Architecture, a discussion around any form of  inhabitant agency can be most immediately retrieved in the field of  participatory design. Several reviews exist of  participatory design efforts that hold a fundamental concern for empowerment (e.g. Comerio 1987, Granath et al. 1996, Marschall 1998). It is therefore natural to start our broad exploration of  inhabitant agency in in this area. As Comerio (1987) puts it, 51  The first principle of  community [participatory] design is to recognize the rights of  all citizens to have a voice in decisions that affect the places they inhabit, work, and linger in. Whatever the method, the goal has been to enable people to participate in their environment. Participatory design is, in fact, the foremost field not only in architecture, but also in product, community and urban design to encompass and articulate a direct interest for including the inhabitant, user or citizen in the “loop” of  space formation. It can be argued that Interactive Architecture, when conceived as an inhabitant-responsive space, may also be a form of  participatory design. In fact, just like for Interactive Architecture, the 1960's mark the debut of  participatory design in mainstream debates, emerging from the same milieu of  concerns and aspirations, as will be presented in this section. Paul Davidoff's “Advocacy and Pluralism in Planning”, from 1965, is one of  the first works to introduce the concept of  user participation in contemporary architecture and planning. The discussion in situated in a context of  collapse of  modernist utopias16, a few years prior to the emblematic demolition of  the Pruitt–Igoe housing complex. Modernist project tradition is fiercely confronted in the 1960s’ and 1970’s.  Empirical methods had their legitimacy questioned and refused (e.g. Friedman 1971), leading, initially, to a search for systematic rationalization of  the design process. The most influential publication of  the period was Christopher Alexander’s famous “Notes on the Synthesis of  Form” (1964), which proposed a less arbitrary and more logical design process. His approach was known as design by science (Lawson 2005), however his methods were then, and are to this day, largely contested. Criticism on the reductive positivist character of  the movement reoriented it towards a “systematic understanding of  the elusive particularities of  the human subject” (Vardouli 2014). Consequently, user participation becomes a central part of  the design methods debate during the 1970s'. It is also in this context that cybernetics is well received to influence the understanding of  the relation between buildings and people. In 1971, the Design Research Society organized its first major international conference, titled “Design Participation”. The conference counted with the works of  some of  the most important precursors of  IA, such as Eastman and Negroponte. In the conference proceedings, Nigel Cross argued for the                                                      16 For a broader analysis of  the role of  modernism and postmodernism in the discourse of  consumer emancipation, refer to Firat and Venkatesh (1995). 52  blurring of  the lines between “designer” and “user” as a potential pathway toward urban sustainability and a more democratic social order (Cross 1972 apud Vardouli 2014). It is important to note, however, that despite the enthusiasm of  its advocates, design participation has been a contradictory practice from its beginning: Some architects view participation as a form of  giving up, capitulating on the individual who knows less than the expert but is willing to live in his own mess. Others see it as the most promising and sensible, if  not the only, approach to ensuring responsive physical environments. (Negroponte 1975) After the two decades of  post-modern reaction and design methods criticism, the topic of  participatory design in architecture faded significantly17, moving to become a relatively marginal research topic. Several of  the participatory design’s questionings in architecture were incorporated into contemporary thinking, but user involvement itself  was mostly reduced to a form of  user-centered design. It became a truism that we, as architects, design for people and we must understand the users' specific demands and needs, instead of  aiming for universal principles. However, at least in conventional practice, the line between the “designer” and the “user” remained as rigid as ever, and the designer remained the expert entitled of  making benevolent decisions based on users' best interest.  This same form of  user-centered design became the central approach in fields like HCI (see Norman 1988), although in a more systematic and scientifically grounded form than what is observed in mainstream architecture. The following diagram, by Sanders and Stappers (2008) illustrates the landscape of  user involvement approaches in design research (Figure 6).                                                      17 Despite its loss of  significance in architectural design, participatory design methods and discourses kept considerable continual relevance in community design and planning. 53   In recent years, however, the discussion of  participatory or “democratic” design has been regaining prevalence across design fields. In architecture, this has been happening under the support of  market considerations18, new decision-making legitimacy debates, and cyber-cultural utopias of                                                       18Vardouli (2015) points out “that research in open source and mass customization practices links user participation in design with better product development (von Hippel 2005 [apud Vardouli 2015]; Schacchi 2003 [apud Vardouli 2015]) and higher consumer satisfaction (Franke et al. 2010 [apud Vardouli 2015]; Anwar et al. 2011 [apud Vardouli 2015])”. Figure 6 - The landscape of  user involvement approaches in design research. Adapted from Sanders and Stappers (2008). 54  creative individualism (Vardouli 2015), apart from the influence of  alien successful projects accomplished through collaborative participation and digital technologies, such as Wikipedia. In a 2013 TED Talk, Alastair Parvin presents the WikiHouse project19 and talks about the shift from democratization of  consumption towards democratization of  production (Parvin 2013). Other researchers have also explored how emerging digital technology is changing supply driven architecture markets into more democratic demand driven ones (McMeel and Amor 2013). As Vardouli (2015) puts it, the central hero of  this liberation mythology associated with information technologies is the figure of  the “empowered user,” portrayed as a “prosumer” (Toffler 1989), “designer-user” (Mackay et al. 2000), “innovation user” (von Hippel and Katz 2002), “produser” (Bruns 2008), or “maker” (Anderson 2012), to mention a few. Sanders and Stappers (2008) explain how the terminology “participatory design” in architecture has been obsessively replaced by “co-creation” and “co-design”. Just as these terms might not mean the same thing for the same people, however, the idea of  participatory design comprises, from its beginning, very different methods and views. Before continuing to discuss what it means for IA to be a form of  co-creation, or exploring fundamental aspects regarding the issue, it is important to flag a main criticism regarding different approaches to participation. User participation, especially when advocating for “democratization” or “empowerment”, is to be studied with advised criticism and even skepticism. In the apex of  participatory design debates, Sherry Arnstein (1969) voiced one such criticism of  the “participation” rhetoric in her widely cited article “A Ladder of  Citizen Participation”. In the article, she devises typologies of  citizen participation, with methods ranging from “non participation”, where experts make decisions on behalf  of  people and legitimize their choices with good intentions; through “tokenism”, where citizens’ voices are heard, but the final decisions are still made by experts; to “citizen power,” where participation or even control by citizens are effective, and true citizen participation may actually occur (Vardouli 2015).                                                      19The WikiHouse project is an open-source project in timber housing. Just like open-source software, however, the actual production and modification of  WikiHouse components require an expertise inaccessible to the lay public. The public can only consume what experts create and develop. 55  The debate on whether it is possible, or to what extent it is possible, to have users taking part in the construction of  their environments in a way that completely preserves their autonomy is a complex one. The debate can focus on a critique on methods (e.g. Arnstein 1969), or go all the way to questioning the concepts of  autonomy or agency in themselves (Nahmias 2005). As Vardouli (2015) puts it: “Who designs? Τhe “empowered” user? Τhe tools and techniques that mediate the process? Τhe designer of  the tools and techniques?” In the case of  IA, the replacement of  the human expert or the human intermediary for a non-human system does not invalidate the problem. In fact, the problem becomes more evident in the context of  technology mediation. Section 4.2 will briefly review some perspectives regarding technology mediated participation. Next, section 4.3 will review a number of  approaches, methods and systems for user empowerment in architectural design and IA-related fields, providing a critical analysis of  these propositions. Lastly, section 4.4 presents considerations in the context of  Interactive Architecture.  4.3 Technology mediated participation Computers are often regarded as empowering tools not only for the expanded capabilities the technology brings about (e.g. Solomon, 1992, Mann 1998), but also for the significant ways that technology allows for social interaction, cooperation and political participation in the broader sense of  the term (Clement 1990). The idea of  computers comprising the ultimate medium for participatory design was already present in early debates of  the field. As Negroponte (1975) viewed it: “Ironically, the computer sciences, generally associated with the elite and often oppressive authorities, can provide to everyone a quality of  architecture most closely approximated in indigenous architecture (architecture without architects).” However, as Vardouli (2015) observes it, by replacing the human intermediary with a technological mediator, the early advocates for computer aided participatory design found themselves confronted with the question of  technological intentionality. “To claim that artifacts have intentions is not to 56  animate them or cast them determinant, but to view them as active participants in mediating human perception and action” (Vardouli 2015). Marshall Mcluhan, one of  the most prominent contributors of  the Toronto School of  communication theory, claimed that every medium presents an inherent bias, a sort of  “pre-information” that exists independently of  what is being communicated (Mcluhan & Fiore 1967). As the title of  his bestseller book prescribes, he argues “The Medium Is the Message”.  Later, Mcluhan would extend the concept of  bias to all and every technology, indicating that through a process of  familiarization the bias ceases to be perceived, becoming an integral part of  the environment; present but unnoticed (Vassão 2008). Don Ihde (1979) and later Verbeek (2011) propose to classify technological mediation in two different types. The “hermeneutic” or “experience-oriented” type refers to the ways that technologies transform human perception of  the world (through amplification and reduction). The “pragmatic” or “praxis-oriented” type refers to the ways in which humans act in the world (through invitation and inhibition) (Vardouli 2015). These “hermeneutic” and “pragmatic” views of  technological mediation suggest interesting relations to the ways in which agency or empowerment may be manifested in Interactive Architecture. These relations will be further explored in later chapters. For the time being, the main objective of  this section is to present the argument that no mediating technology will ever be neutral. This is an extensively studied topic, and I only intend to cover a few fundamental ideas that illuminate the current discussion. The interested reader can refer to the authors cited in this section for further information. With regard to user interfaces, Weller & Hartson (1993) explains that there are constraints intrinsic to the human-tool interaction that limit what the user is likely to think of  doing when manipulating the tool. Thus, the use of  the technology transforms the user's problem-solving experience. Another important author, lhde (1979, p. 56), suggests that “experienced use of  technologies brings with it a simultaneous amplification of  certain possibilities of  experience while at the same time reducing others”. For Akrich (1992), designers inscribe their visions of  the world, or “scripts”, in the technological artifact in the form of  action and control frameworks: thus, the artifact affords amplification and reduction, invitation and inhibition according to the designer's explicit intentions or underlying assumptions of  the world. 57  More recently, interaction designers have started to capitalize on the inherent bias of  technological artifacts. In the book “Persuasive technology: using computers to change what we think and do “, B. J. Fogg (2003) lays the basis for an expanding research area that by 2015 has already hold its 10th international conference. Persuasive technology, as the name suggests, investigates ways in which the design of  technological artifacts can influence our perception of  the world or of  an entity in the world (hermeneutic type of  mediation), as well as influence the decisions and actions we may take (pragmatic type of  mediation). Beyond technological mediation per se, we can start to explore the validity of  empowering mechanisms that are necessarily biased. If  a given Interactive Architecture will always be connected to the original designer's visions through control frameworks, would all sequent discussions on inhabitant empowerment be automatically inconsistent? To answer this question, we must first go back to our definition of  empowerment20. Empowerment (or agency), as we have suggested, is related to one's ability to determine and achieve desired outcomes. From a Self-Determination Theory perspective, agency and empowerment may be viewed as how aligned a person's behaviour, condition and opportunities are with this person's own goals and values21. Thus, complete control or complete independence are not necessary conditions to empowerment, unless a person deems such level of  control or independence as a valued state. With regard to the biases or control frameworks embedded in the technological artifact, these may or may not be impediments to empowerment, dependent on how the user relate these limitations or augmentations with what he/she values and aspires. Some authors have, in fact, argued that extraneous control mechanisms are important components of  empowering systems (Duane & Finnegan 2003). The argument is based on the idea that control assists in the accomplishment of  goals, helping users organize and manage their actions in an orderly fashion. Orlikowski (1991), in a moderate view, argues that control mechanisms are both enabling and constraining: “enabling in that they facilitate the coordinated action of  individuals in the production process [...], and constraining as they restrict the manner and outcomes of  individuals’ actions”.                                                      20 Different definitions of  empowerment or even different epistemological stands would result in different answers. 21 This statement assumes (and this assumption has been made in chapter 2) that agency is equivalent to the Self-Determination Theory's notion of  autonomy. 58  Simons (1995) comes to affirm that control and empowerment must be balanced, so that one doesn't lead to the failure of  the other. In the study of  workplaces, he identifies seven types of  controls that must be in place to allow for effective user empowerment. In a case study, Duane & Finnegan (2003) found that employees believe that control activities are significant empowering factors in the early stages of  an intranet development process. In another case study, however, Orlikowski (1991) found relation between mechanisms of  control, reinforcement of  established forms of  organization and centralized power in the implementation of  a given information technology. It must be mentioned that these studies use a construct of  empowerment that might be distinct from the one I have adopted in my research. Lastly, it is also useful to confront the idea of  interactivity as inherently empowering, following the same principle. The argument in favour of  interactive technologies for empowerment certainly exists. Coleman (2003, apud Andrejevic 2009), for instance, states that “interactivity is political: it shifts control towards the receivers of  messages and makes all representations of  reality vulnerable to public challenge and disbelief ”. Furthermore, interactivity presupposes user participation, even if  to a small degree; it also presupposes that user becomes a key component of  any outcome. But authors like Andrejevic (2009) articulate an important critic of  such view: Claims that interactivity is inherently political or empowering, or that changes in social relations necessarily follow from the fact that audiences have become more active participants, are not cutting edge, avant-garde claims; instead they are relics of  an outdated binary [...] To make an automatic association between interactive participation and democratic empowerment is intellectually complacent in the worst sense: by clinging to an outmoded set of  associations it bypasses the conceptual work that might help imagine ways in which media practices could live up to the promise of  democratic empowerment. Such critiques of  participation, responsiveness and interactivity must always be present when discussing empowerment in IA settings. For my review of  existing approaches for sharing control with inhabitants, I will provide a critical appreciation of  mediation issues whenever appropriate.  59  4.4 Main approaches for sharing control with inhabitants As already suggested, user participation and empowerment in building or urban design/behaviour can take many forms. In this section, I will review several relevant works that have appeared to me as important to the discussion of  Interactive Architecture.  4.4.1 Levels of  control The first of  the relevant works that deserves note is the approach introduced by Nicholas J. Habraken (1961), which laid the basis for the concept of  Open Building. In his early work, Habraken (1961) presented the problem of  housing in the Netherlands and suggested the introduction of  different levels of  decision making concerning the built environment, each level with a different public. He initially defined three main decision-making levels: tissue, support and infill, respectively referring to the urban fabric, the base buildings and their fit-outs. Habraken is not the only one to identify “levels” or “layers” concerning the composition of  the built environment. Stewart Brand (1995), for instance, identifies layers specific to the problem of  evolution and modification of  buildings (Figure 7). The six S’s that compose his “Shearing Layers of  Change” are: Site (eternal), Structure (30 to 300 years), Skin (20 years), Services (7-15 years), Space Plan (3 years), and Stuff  (daily).  Figure 7 - Shearing Layers of  Change. Adapted from Brand (1995). 60  The relevance of  Habraken's work for the discussion of  empowerment in Interactive Architecture, however, lies in the acknowledgement that the built environment, and its different levels, serves different groups of  people in different scales and situations. Thus, empowerment in IA or any other form of  architecture cannot be considered one-dimensionally. Despite the great repercussion of  Habaken's early publication, the clear formulation of  his principle of  levels was elaborated only more recently, in the book The Structure of  The Ordinary: Form and Control in the Built Environment (Habraken & Teicher 1998). The image below presents an illustrative diagram extracted from that book (Figure 8).  Habraken and Teicher (1998) explain that the different levels of  the built environment share asymmetrical relationships, with links of  dominance and dependence. For instance, houses within a city block can be changed without any reorganization of  the street network, but the inverse is not possible. Thus, “the higher-level configuration dominates the lower level; and the letter is dependent Figure 8 - A Diagram of  the Principle of  Environmental Levels. Adapted from Habraken & Teicher (1998). 61  on the former” (Habraken & Teicher 1998)22. In the case of  same-level spaces, the environment is organized and subdivided by territory and its markers. Importantly, Habraken and Teicher (2000) also introduce the idea of  different levels of  control. According to the authors, control distribution does not necessarily follows the distinction of  environmental levels. An actor or group of  actors may keep control of  different environmental levels, while other actors might not have control over levels of  which they are the primary users. It is also possible that some elements of  the built environment belong to two different environmental and control levels. It has been suggested that by aligning control levels and environmental levels, buildings can create conditions for responsibility and care (Cuperus 2001), fostering sentiments of  belonging, ownership and tendance. This might be particularly achievable through IA. The Open Building approach seeks to minimize the mutual interference of  environmental elements, “combining the freedom of  choice and dignity of  individuals in their work places, dwellings and communities, with the ecological coherence and stability of  culturally appropriate buildings and neighborhoods”23 (italic not original). As suggested by the diagram, the approach focuses on long term changes and stable configurations, which doesn't reflect IA's penchants towards fluidity and real-time responses. Open Building also does not incorporate in its core the potentialities of  computing technologies as mediators. Computers, however, have been present since the early years of  participatory design discussions, given the great enthusiasm stirred by computers development concomitant to the post-modern interest in the “user” of  architecture. Some of  these techno-centric proposals are discussed next.                                                       22 It must be noticed that higher-level configurations are devised based on preconceptions of  lower-level configurations, thous a relation of  influence exist in this opposite direction. Furthermore, oftentimes, e.g. in case of  informal settlements, the creation of  higher-level settings are defined in a bottom-up approach through the organization of  lower-level settings. However, it can be argued that the different possibilities of  formation in the built environment does not challenge the relevance of  the hierarchical structure. 23 http://open-building.org 62  4.4.2 Early computers and user empowerment through design Negroponte (1975) presents one of  the first examples of  computer programs intended to engage with the lay user to generate an architectural design: ARCHIT, a system proposed by Rorick in 1971. Negroponte (1975), however, criticizes the program for centralizing the design process. In ARCHIT, the computer leads the conversation, asking questions and suggesting answers (“I would suggest this... don't you agree?”). Despite having the final word, the user is still highly conducted by the machine, cast by the format of  interaction. In the Speedwritter project, Yona Friedman denies this approach and intends to create a neutral machine, which allows for the user to freely express his/her own values and interests.  Friedman (1975) explains the two ways in which he believes the problem of  computer mediated participatory design can be considered: The first one (which is the one designers today generally use) would be the one I label the “paternalist”. In the paternalist organization, it is the translator (designer, expert or computer) who establishes his own preferences and judgements, in the interest of  a particular future user, after a learning period during which the translator learns the peculiar particularities of  this future user. Thus the translator (in our specific case, the computer) would make some decisions for the future user, “with paternal benevolence”, leaving the entire risk of  potential errors for this future user to cope with himself. (Friedman, 1975) The second way I call “nonpaternalist”. In this case the translator makes no judgements or decisions and thus needs no learning period. It functions only as a sort of  “speedwriter” denoting the tentative decisions of  the future user and emitting a “warning” about expectable reactions of  the real world upon each decision. In this case the learning period exists as well, but the learning is done by the future user, and it concerns the structural characteristics of  the real world alone. (Friedman, 1975) Friedman’s (1975) “nonpaternalist” proposal, the flatwriter, allowed users to select from a comprehensive repertoire of  spatial configurations in order to modify a space. A warning system would provide feedback to inform users of  the impact of  their choices (Sterk 2006a). Thus, for Friedman, all control belonged to the user, who makes free and informed choices through a relatively sophisticated computer interface. 63  Vardouli (2015) argues that Friedman's use of  technology as a neutral and disinterested support for design does not negate technological mediation. Instead, she claims that the apparatus “exhibited full awareness of  the mediating role of  technologies in human perception and action and aspired to create a protocol that will preserve the human as prime mover of  a growing technological universe”. How well the flatwriter preserved the human as the “prime mover” or as a free agent, however, was left untested. The nature of  the system also indicates that Friedman did not intend a continual adaptation or negotiation of  space. The system negates learning and makes no decisions for the user, which implies a cognitive demand each time a space modification is required. In fact, Friedman was not concerned with all the possibilities of  intelligent or interactive buildings as continuously adapting spaces, but rather with a tool to allow lay users to become the architects of  their own needs. Negroponte (1975) worked on a machine with similar purposes as the flatwriter, which he called the “design amplifier”. However, Negroponte also went further and speculated on the possibility of  intelligent buildings that could adapt themselves. In both propositions, Negroponte adopted a significantly opposite approach than Friedman's. For Negroponte (1975), the computer is a surrogate self, and communication between human and machine would require the computer to build the necessary models of  the user and apply them in context. The cybernetic concept of  conversation permeated his propositions, as well as the growing body of  machine intelligence literature at the time. The machine, in order to provide environmental responsiveness, would need to be imbued of  intelligence and manifest understanding.  Furthermore, Negroponte refused the use of  regulatory control systems and believed that “absolute adaptivity would lead to terrible complacency.” By conceiving the machine as a “good friend”, as a surrogate that contributes technical expertise to the user's design intentions, however, Negroponte (1975) acknowledged an inherent paradox. He questioned: “the machine intelligence necessary to support richness of  dialogue will in fact be counterproductive to the participation because this same intelligence, like that of  the human architect, would fall pray to the ills of  translation ascribing meaning of  its own? In other words, does the intelligence required to communicate contradict the notion of  informed amplification?”. The author suggests that the computer should act as a good teacher who fosters an intellectual environment. However his considerations do not come to solve his paradox. In fact, by attempting to approximate 64  his machines to the human architect, Negroponte fails to present a compelling argument as to why he believes the machine could do a better job than a human architect interested in fostering the same ideal of  user empowerment. Negroponte (1975) acknowledges that the figure of  the architect brings about important contributions during the design process which are not limited to designing, such as providing comfort and confidence to the user, or generating goals that the user could not think of  himself. Could a computer provide that?, he asks. Both Negroponte and Friedman work on the assumption that the architect possesses a set of  important knowledge and information; this can be extended to the possession of  a critical architectural literacy, and the ability to question established ideas with regard to the production of  the built environment. These are qualities that Negroponte's machines intend to also possess, along with biases and preconceptions that allow for understanding and conversation24. When discussing intelligent environments that adapt themselves, he even gets to suggest that “maybe a house is a home only once it can appreciate your jokes”. In the end, the conflict between the arguments in favour of  human-like intelligence and the arguments against the human architect in Negroponte's discourse is left unsolved25. Thus it is questionable to what extent, after criticizing the interference of  human architects, Negroponte's propositions offer opportunities for increased responsiveness and empowerment.  Vardouli (2015) suggests that responsiveness, in Negroponte's proposal, would emerge from a reflective process: “the user designed the environment that designed the user”. We can also argue that, just as was discussed in the previous section, the lack of  complete control on the hand of  the users does not negate empowerment. Negroponte's speculations of  intelligent, self-adapting buildings form a compelling set of  possibilities that have greatly influenced the fields of  Interactive and Responsive Architecture. However they are simply speculations, unlike the flatwriter or the design amplifier projects, which could be implemented                                                      24 In a recent study, a team of  researchers have found that even machine-learning algorithms intended for objective triage can present human-like unintentional bias, given how intelligence technology often seeks to mimic human learning (Feldman et al. 2015). In the case of  Negroponte's propositions, however, preconceptions are not a problem to be eliminated, but it's rather an important component of  conversation. 25 Although it would be easy to make an argument for the advantages of  machine intelligence, including the constant availability required in self-adapting buildings, the conflict I point out does not refer to that. Instead, the conflict refers to the critique Negroponte presents of  the human intelligence architect and how s/he interprets the users needs through hers/his own translation mechanisms. 65  and discussed to further detail. Sequent projects that aspired to empower the inhabitant towards the construction of  their environment have also been closer to the flatwriter or design amplifier propositions, largely distancing from IA debates. In the next sections I will explore what has been done in architectural research towards technology mediated participatory design, followed by an attempt of  re-approximation to the problem of  Interactive Architecture.  4.4.3 Some of  recent proposals and the non-interactive architecture Theodora Vardouli, who I have repeatedly cited in this chapter, has also proposed an apparatus for technology mediated participatory design. Vardouli and colleagues (2012) draw upon Friedman's flatwritter to propose the system called commonSense. The systems acquires real time data from a network of  sensors, “while an online design engine visualizes the data, provides design recommendations in response to user habits or declared needs and desires, or allows users to develop their own design solutions through interfaces for different levels of  design 'expertise'” (Vardouli et al 2012). The project is theoretical and has not been implemented nor tested. However it presents two interesting contributions: first, the possibility of  offering a varying number of  design interfaces for varying levels of  design expertise (a response to a problem that will be later discussed); and second, the conception of  a platform where the public of  a certain common space can negotiate it's configuration (a concern that has been largely explored by Habraken). Other recent proposals of  technology mediated participatory design exist. Lo and colleagues (2015), for instance, devised a computational platform to integrate occupants in the design process. Their system, instead of  embedding built-in constrains to secure feasibility of  the resulting design, chose to maintain the architects in the process, controlling the outcome. “The controls”, they say, “have to be optimized so that the collaboration of  the occupants will not dictate the design too much, which might cause the design to lose control, yet will not be too constrained to the extent that participation is meaningless” (Lo et al. 2015). The system they propose uses both a bottom up and a top down approach at the same time; architects define the framework within which users can operate, so the 66  constraints aren't fixed but are pertinent to the situation at hand. Thus, instead of  trying to neutralize the role of  the mediator,  Lo et al. (2015) embraces the need of  a “control”. The proposals by Vardouli et al. (2012),  Lo et al. (2015) and many other recent works do not refer to the possibilities of  Interactive Architecture. In the commonSense project, although data is collected in real-time, response and adaptation do not occur in real time. The data just feeds into a collaborative design dashboard, which can generate virtual proposals. In principle, the system does not execute them. In the realm of  installations, one particular work stands out for potentially addressing the interest of  Interactive Architecture. The Reconfigurable House, by Adam Somlai-Fischer, Ai Hasegawa, Usman Haque and others, is a DIY,  low tech, “open source” pavilion. It allows participants to wire new low-tech devices (e.g. cheap toys) and manipulate the source code. Although its transferability to the broader domain of  architecture might be questioned, this project provides a rare investigation into the idea of  an “open source” interactive space. Nevertheless, the discussions of  participatory (empowering) design, and self-adapting (intelligent) architecture seems to have diverged a long time ago. While the work of  Negroponte and early cyberneticists seemed to connect the two ends, sequent developments of  Interactive Architecture and technology mediated participatory design have been largely disassociated. In order to study recent specific propositions and applications in the realm of  interactive systems with an interest in user contribution, we need to look at neighbouring fields to Interactive Architecture, such as Interactive Arts and Smart Homes. I'll start by discussing a design approach that has been discussed with regard to continuous end-user software development as well as interactive arts: metadesign.  4.4.4 Metadesign Metadesign was originally conceived in the field of  Architecture, referring to a mechanism26 that articulates abstract design principles and parameters (van Onck 1965). The term was later employed                                                      26 The mechanism sets the universe of  possible configurations of  a given object of  design, from which the best variation can be selected. The Metadesign of  van Onck (1965) greatly approximates some discussions of  67  as a social-cultural critique (Virilio 1995); as a framework for software design, in symbiosis with interactive arts (Fischer et al. 2006); and again in architecture in reference to the software design framework (Giaccardi 2005). In this section, I will review Metadesign as the framework studied by Fischer, Giaccardi and others from the Center for LifeLong Learning and Design, because I believe this approach is the one that explicitly suggests a bridge with Interactive Architecture, as it does with Interactive Arts. Meta-design, in this sense, is a conceptual framework which defines and creates the means for users to become co-designers of  a system throughout the whole existence of  the system. Thus, Metadesign is a step forward towards interactive architecture and away from conventional participatory strategies, since it is intended as a continual process and not limited to a one-off  stage of  design. The idea is that even if  the system is adequately designed at the design stage, it still needs to be evolvable in order to fit unanticipated needs, new subjects and emergent contexts. Metadesign proposes the creation of  open systems which allow for modifications whenever required, providing the users with opportunities, tools, and social reward structures to extend the system to fit their needs (Fischer & Giaccardi 2006). Fischer and Giaccardi (2006) warns, however, that “the goal of  making systems modifiable and evolvable by users does not imply transferring the responsibility of  good system design to the user”. It only implies that the system must be designed for evolution, and that this evolution, to a certain extent, will be carried out by users without requiring the assistance of  the designer. In this sense, the authors seem to acknowledge that the original system designer retains certain control over what the end-user may do or perceive, through control frameworks inscribed in the system infrastructure (see Akrich 1992) However, the extent to which Fischer or Giaccardi consciously recognize the relation between what end-users will later develop and the original system infrastructure is unclear. Giaccardi (2005) claims that, in Metadesign, content and context are separated, and that context alone is to be dealt by Metadesign. Vassão (2008) critiques that this immiscibility between form and content appears to be sine qua non condition to Giaccardi's approach, rendering it contradictory.                                                      what is currently referred to as parametric design. It must be noted, however, van Onck's critique of  style as a main driver of  design, a frequent characteristic of  contemporary parametric design. 68  Regardless of  their understanding of  the relations between the system infrastructure (or context) and future user design, Fischer and Giaccardi (2006) explicitly mention concerns for user empowerment and advocates for users to contribute towards the evolution of  a system with their own visions and objectives. However, the authors do not develop this argument further, rather focusing on technical aspects of  the framework. Fischer and Giaccardi (2006) propose that Metadesing must be undertaken through what they call “underdesign”: the practice of  designing environments that allow the “owners of  problems” to create their own solutions at use time, instead of  offering a complete set of  solutions for use. The method they suggest for the development of  the underdesigned system is the seeding, evolutionary growth, and reseeding (SER) model. The model is based on the postulate that “systems that evolve over a sustained time span must continually alternate between periods of  activity and unplanned evolutions and periods of  deliberate (re)structuring and enhancement” (Fischer & Giaccardi 2006). One of  the main technical problem observed by the authors in the process refers to the inverse relation of  a design tool's flexibility and its learning difficulty for the “owner of  problems”. For instance, general-purpose programming languages (e.g. C++) offer great flexibility and can represent any problem that computers may be employed to solve; however they are largely inaccessible to the typical architectural occupant, because they provide the incorrect level of  representation for most problems (Shaw 1989 apud Fischer & Giaccardi 2006).  On the other hand, domain-specific systems, such as The Sims' Construction Mode (Electronic-Arts), provide accessible support for certain problems, but the user is limited by the defined boundaries of  the tool as a closed system. This is an issue that Vardouli et al. (2012) have addressed in their proposition, as already presented. They suggest offering the user a range of  different interfaces for different levels of  expertise or interest.  Not Fischer nor Giaccardi, in any of  the publications I have read, come to suggest a fluid use of  different expertise interfaces. However, they acknowledge that a same user will assume different roles during the use and development stages of  a system, depending on the situation at hand, these roles being “passive user”, “power user”, “domain designer”, etc, even if  the user is an expert developer. Furthermore, Metadesign implies a process of  co-adaptivity: both the software artifact and the human subject evolve and move beyond their original states. Therefore, Metadesign sustains an interactive 69  feedback of  information between technological and human systems (Fischer & Giaccardi 2006), resembling the dynamics discussed by cybernetics and Interactive Architecture. In fact, several of  the issues discussed so far regarding Metadesign are relevant to IA. Underdesign, for instance, is a strategy that has been applied to architecture with similar interests to its employment in Metadesign, such as in the famous Quinta Monroy social housing project, in Chile, by Elemental.   When an IA system is designed to encourage users to articulate their own spaces, underdesign might also be a pertinent strategy. However, in adopting underdesign, IA must also deal with its questions, such as the way in which the provided infrastructure (context) defines a design space and indirectly influences what will be considered by users. The SER model, on the other hand, establishes an explicit control framework. It anticipates the need of  deliberate structuring or organization of  contributions, which might be assured by a group of  experts responsible for the stability of  the overall project. It also describes a linear trajectory of  evolution to the system, which might be appropriate to an open source software project, but not as much to all the universe of  possibilities of  Interactive Architecture. In IA, while a linear evolution might be possible, it is expected that complete deconstruction and reconfiguration of  spaces and behaviours should also be supported in different strategies, as well as regressions and isolated settings. The flexibility versus difficulty issue of  the communication medium is also of  great interest to IA. However, the importance of  the subject requires it to be discussed separately in its own chapter, Figure 9 – Illustration of  the Quinta Monroy social housing project by Elemental. On the left, the original design as it was build and delivered and, on the right, the building after modifications and extensions executed by inhabitants.  70  alongside a broader discussion on the matter of  interaction. The following chapter will address interaction more centrally. To finalize the review of  existing approaches in occupant participation, I will present implemented projects in fields that most closely approximate the technical problems of  Interactive Architecture, such as Ambient Intelligence.  4.4.5 Smart homes, context-aware applications and end-user development When moving closer to the technical problem of  IA, in domains such as smart homes, intelligent environments, Ambient Intelligence (AmI) and Ubiquitous Computing (UbiComp), the matter of  user participation tends to have a more pragmatic approach, focused on the design and implementation of  specific systems. I refer to a shared technical problem because I believe these fields hold significant broader distinctions among themselves that must be acknowledged. In identifying the distinctions, it becomes easier to understand the potential difficulties of  transposing findings and concepts between fields. The reader must refer to section 2.1 for clarification. In this section, I focus mostly on studies of  context-aware applications and end-user programming from domains external to IA. Noteworthy, although the word “user empowerment” is mentioned in the papers I reviewed from these fields, the matter of  empowerment itself  is not discussed. Usually, these papers include the user in the loop for a matter of  usability, because other methods in context-aware applications are not sufficient to assure satisfactory performances. Context awareness is an important technical problem in spatial responsive systems for self-evident reasons: these systems respond or adapt to contexts of  use, and no unstructured need, requirement or activity emerge detached from context. Most, if  not all, of  IA descriptions in literature underlie the need for an IA system to be context-aware. For instance, Biloria (2010) talks about the optimal augmentation of  morphologies in accordance with contextual variations. In discussing the possibilities for IA, Fox and Kemp (2009) state that “[t]here is great potential for dynamic architecture that arises from understanding what a space or object is currently doing and how it can aid in promoting or accommodating a specific task”. 71  The discourse of  a spontaneous adaptation of  IA to changing personal, social and environmental demands is notably recurrent (e.g. Achten & Kopřiva 2010, Cetkovic 2012, Salim et al. 2012), presupposing the IA system can understand and adequately interpret these changing demands. However, the exploration of  these possibilities in IA remain highly speculative or limited to simplistic systems. Therefore, authors in IA do not usually deal with the technical problems of  context-awareness. These are problems that are much more often addressed in HCI, AmI, UbiComp and smart homes literature. Dey et al. (2004) assert that developers currently have two options for developing a context-aware application. The first one is to build a rule-based system, thus predefining specific sets of  behaviours dependent on certain data readings. The second option is to build a recognition-based system (Dey et al. 2004), also referred to as an inference engine (Zhang & Brügge 2004), which uses machine learning and intelligence to interpret data and infer the context. As Zhang and Brügge (2004) point out, the problem with the rule-based system is that the designer cannot anticipate all situations of  use, and the system cannot handle complex or unpredictable situations that could not be described with well-specified rules. On the other hand, recognition-based system tend to be cumbersome. Dey et al. (2004) explain that recognizers often need to be handcrafted over a period of  days, weeks or even months in an attempt to optimize recognition performance. Zhang and Brügge (2004) also argues that, to date, there is no ascertained way for a system to infer a correct contextual state just by collecting sensor information. Davidoff  et al. (2006) explain the difficulties in mapping people' activities and routines to such systems. More recent research demonstrate that inferring context remains a challenging problem (Shafti et al. 2013). In both cases, rule-based and recognition-based systems, the approaches fail to achieve short or long term compatibility with the end-users’ expectations (Greenberg 2001). Zhang and Brügge (2004) argue that the only feasible alternative to date for a system to agree with the users’ expectations is to have the user program the system behaviour him/herself. Therefore, the matter of  user control, if  not user empowerment, comes into play as a pragmatic response to the current insufficiency of  context-recognition systems. In this sense, end user development (EUD) becomes a relevant field of  study in spatial responsive systems, including Interactive Architecture. EUD, which in a broad definition may comprise end-user 72  programming, end-user software development, customization of  digital technologies, among others, has been an important research issue in HCI since the early 1990s (e.g. Henderson & Kyng, 1992), and possibly going back even further over a decade (Tetteroo & Markopoulos 2015). One interesting EUD system in the field of  Intelligent Environments is part of  the Intelligent Room Project (Gajos et al. 2002). This project uses a rule-based strategy for context awareness and behaviour, allowing users to create and feed their own rules and goals into the system. The Intelligent Room Project is composed of  three distinct systems:  Rascal, ReBa and Alfred. Rascal is a framework for goal-directed self-adaptivity. The system works with a varying list of  goals which it plans for achieving, considering the resources needed to implement the plans and the known user preferences. Since each goal may be satisfied by multiple plans (e.g. a room can be made brighter by either turning on the lights or opening the window blinds), Rascal can adapt the system behaviour to varying circumstances by selecting a plan that best accommodates other goals in the system, thus being appropriate to context. ReBa, the next system, is the reactive component of  the Intelligent Room Project. It responds to events, or triggers, by posting a new goal for Rascal to achieve. Finally, Alfred, the end user interface, allows people to program the Room by telling it the name of  a new goal, demonstrating triggers and plans for achieving that goal, and informing the system of  the conditions under which they would prefer one plan over another (i.e. the user records response “macros”). The entire communication is done by simple verbal commands or other natural forms of  interaction (Gajos et al. 2002). In this case, the authors explicitly claim that a system properly structured for self-adaptivity and reactivity to the environment, such as the Intelligent Room Project, provides an appropriate framework for end user empowerment. It must be noted that the Alfred system records macros for outputs (goals and behaviours), not as much for inputs, so the system is not robust in recognizing contexts. Instead, the system understands simple triggers, but it presents a sophisticated solution for handling different possible responses in relation to each goals in its plate and to other user-specified goals. Thus, despite its complexity, the Intelligent Room Project is still a rule-based system. Simpler rule-based EUD systems exist and are becoming increasingly common, such as the IFTTT (If  This Than That) mobile application, a widely popular free app that allow users to easily create conditional rules among other apps and smart appliances. 73  Adopting another approach, the project named a CAPpella develops a machine learning strategy to identify contexts (Dey et al. 2004). In order to ensure a satisfactory context-aware application, the authors focus on an end user development strategy of  programming by demonstration. In a CAPpella, the users access an on-screen interface for indicating to the system the time-frames and the relevant recorded data of  a contextual event, so the system knows what to look for when identifying contexts. In their research paper, Dey et al. (2004) present the process of  training the system to distinguish when a group of  people or an individual in a room is having a meeting from when they are not. The system required exposure to a number of  events (min. 5), followed by an end-user indicating the event, before it could distinguish a meeting from a non-meeting with a satisfactory percentage of  errors (as low as 6.7% for 1-person meeting and 20% for 2-persons meeting). A rule-based application would not be able to identify complex events in context the way a CAPpella does. Without machine learning, a system would require very specific, well-defined triggers to understand an event. In case of  a meeting, perhaps someone would have to ask the system to set “meeting mode”, or else every time a group of  people were present in certain rooms, “meeting mode” would be activated, even if  the group did not intend a meeting. The problem with a CAPpella system, however, has already been explored when mentioning the issues with inference engines. The training period required for a context to be identified can be cumbersome and frustrating, especially if  new activities and contexts arise often. Additionally, errors in identifying context become more significant when considering the use of  such applications in people's daily routine. All the examples of  EUD systems in smart homes and similar context-aware applications are concerned with the adaptive settings of  home appliances and services (e.g. when to turn on the lights, when to start the coffee machine). In interactive architecture, authors are typically more interested in the adaptation of  entire buildings' morphology (or specific layers of  it), making previous research not immediately translatable to the problem of  IA. However, the debates being conducted in those fields are the ones that more closely approximate, pragmatically, the problem of  user empowerment in IA. Addressing end-user development is only one dimension of  the user control problem as it is approached in AmI and UbiComp. Especially if  the system is expected to exhibit autonomous 74  behaviour, thus not being completely dependent on user input, strategies must be in place to allow the user an appropriate level of  agency over their environment. Bellotti and Edwards (2001) argue that the more we try to get systems to act on our behalf, the more we have to watch every move they make.  The authors developed a few design principles that stirred great attention and repercussion in AmI. Apart from control, intelligibility is a central issue of  their discourse. An intelligible context-aware system is a system that is able to represent to its users what it knows, how it knows what it knows, and what it is doing about what is knows (Bellotti & Edwards (2001). Vermeulen et al. (2013) explains that many systems around us provide subtle intelligibility and control. Recommender systems such as Netflix, Amazon, App Store, or Youtube, which work by providing recommendations of  related content to their users, are an example. In some of  them, users can ask the system why a certain item was recommended to them and give feedback on that behaviour (Vermeulen et al. 2013). Several studies exist in exploring ways to improve intelligibility and control. Vermeulen et al. (2013) introduce a design space consisting of  six dimensions that play a role when developing interfaces for intelligibility and control: Timing: Intelligibility and control can be supported at different times during the interaction: before, during and after events take place. Generality:  User interfaces and interaction techniques for intelligibility and control can be general or domain-specific (e.g., techniques for visualising location errors in navigation systems). Degree of  co-location: Support for intelligibility or control might be embedded or integrated with the rest of  the user interface versus external, when users are required to switch to a separate interface. Initiative:  Users may need to explicitly request intelligibility information or invoke control techniques manually  (user),  or might automatically be presented with these features when necessary (system). Modality: Several modalities can be used to help users to understand or control the system  (e.g. visual, auditory, haptic). 75  Level of  control: The level of  control end-users can exert over the system varies from intelligibility, where no additional control is added beyond intelligibility, over counteract, where users can perform the opposite action (e.g., undo), to configuration, where users can tweak predefined system parameters, and programmability where users can themselves (re-)define how the system works. The aspects discussed in this section will be yet further explored with regard to interaction design when pertinent, in chapter 5.  4.5 Inhabitant agency in contemporary interactive architecture It has been already argued that there is little recent research in IA exploring the problem of  inhabitant agency. This section will review some of  the works that I believe contribute to an understanding of  the topic. Cetkovic (2012) is one of  the few authors to attempt to re-open the debate of  user empowerment in IA, especially regarding the new breadth of  freedom and possibilities that IA is expected to foster. As he puts it: “one would think that the greatest asset of  interactive architecture is that it provides more options and freedom for the user. Instead, in reality users receive totally controlled spaces and movements – a misinterpretation of  the term flexibility”. He believes the problem arises from the architects' perception of  the user and of  the user's role in the spaces. Cetkovic (2012) believes that by focusing the interaction and communication strategies of  IA on the concept of  affordances, architects could avoid the risks of  deterministic design. This would be so because, as Norman (1988) explains, the perception of  any possible actions afforded by an object is mediated by the actor's own goals, plans, values, beliefs and past experiences. The expectation that this understanding would result in open systems and non-deterministic design, however, is very questionable, as the author himself  implicitly admits. Jeng (2012) also tries to define IA in relation to empowerment, by presenting the extension of  human capabilities as one of  IA's main objective; and the idea of  inhabitant agency, as it has been discussed throughout this manuscript, seem to permeate Takeuchi’s (2012) description of  his conception of  IA. He refers to the term “Synthetic Spaces”, which he claims to exhibit the following two traits: 1) an 76  awareness of  the power of  physical architecture to influence human behaviors and psychology, and 2) an intent to let users neutralize, or take control of, that power of  architecture. A few other recent authors have come to address the role of  the user in control systems in IA, but without a noticeable interest in empowerment. Again, they use pragmatic arguments for increasing inhabitants' control. Compared to what has been produced in AmI regarding user control and programming, these debates in IA are clearly behind in maturity. However, being native to the field of  IA, these authors address layers of  the environment which are not considered in neighbouring fields. Sterk (2005, 2006a) is one of  the few authors to discuss in detail how user input influences the overall behaviour of  the architectural system. He proposes a simple model which is comprised of  user input, spaces (the serviced spaces that we occupy), and structures (the external shells that shelter us). Together, spaces and structures form the resulting architecture. The task of  the control framework Sterk (2005) describes is to “coordinate the activities of  each building element to achieve a state that reflects user needs”. The figure below illustrates his framework (Figure 10).  Figure 10 - Hybridized control model for responsive architecture. Source: Sterk (2005). Used with permission. 77  The system control is conceived as a hybridized model that allows separate reasoning processes of  a reactive (or low-level) and deliberative (or high-level intelligence) nature to coexist. User input functions in the higher level, despite the fact that the user only interacts with the system in the lower level. Sterk (2006a) explains that “one may conceive of  users’ interactions as being corrective”. For example, a user may adjust the behaviour of  a thermostat to meet perceived changes in comfort. “Corrective actions are instances of  direct manipulation that help simpler, automated systems perform well” (Sterk 2006a). Another part of  the “user input” component in Sterk's framework is the User-Model. The User-Model uses inference engines to provide responsiveness. It uses environmental data as well as data captured by watching an occupant interact with a space (including his/hers corrective actions), thus generating a contextual model that is capable of  contextual responses (Sterk 2006a). How well the inference engine would provide context sensitive responses in an architectural setting is not discussed, given the fact that Sterk's framework is theoretical. In Sterk's framework, it must be noted that the user is not allowed to interfere with the system with regard to its high-level decision making. Thus, in Vermeulen's et al. (2013) six dimensions of  design space, Sterk's model presents a low level of  control (“counteract”) and a user-sided initiative towards control. It is also apparent that in Sterk's framework, the responsive environment is designed with preconceived “logical” responses to a group of  conditions, with limited support for expansion apart from the system's own learning capabilities. Apart from the issue of  the user, it is also interesting to note the way Sterk's system handles the interaction between structures and spaces. The system first attempts to solve a problem locally, using lower level responses. If  that is not possible, an exception is issued to be handled by the centralized, higher-level control. The central control then handles the exception by issuing a request to another lower-level system. This form of  internal flow can be extended to articulate the behaviour of  a community of  buildings (Figure 11). 78   Although Sterk does not mention Habraken or the concept of  environmental levels, his model seems to suggest that solutions are first to be sought locally in the lowest environmental levels. When these cannot provide appropriate answers, a centralized control system request the engagement of  higher environmental levels, in a hierarchical sequence. As will be later discussed, however, this degree of  detail in which Sterk discusses the behaviour of  the system and the forms of  user input is incredibly rare in IA. One reason may lie on the long gap of  disinterest in user agency in the field. Another, perhaps most important reason, lies on the lack of  built examples of  truly interactive architecture. For the last couple of  decades, the most common form of  addressing users as participating agents in the creation of  their environment, both in IA discourse and projects, refers to the use of  a person's behaviour as a seed in emergent aesthetic expressions. This view is well articulated by Wlaszyn (2011). She argues that “[i]nteractivity offers an explicit engagement for the user allowing anyone who interacts to become at minimum a collaborator and in some cases a co-creator of  sensitive experience”. She goes on to question, with a phenomenological view of  the world, if  the explorations of  non-linear interactive process are not just a derivation of  aesthetic experience explorations. This kind of  approach has considerable resonance with interactive arts. As I state in a previous research (Costa Maia & Meyboom 2015), it is also much easier to address the potentialities raised by Wlaszyn (2011) with current inexpensive technology than to solve, for instance, the problem of  architectural self-adaptation to unanticipated use demands. As a result, IA literature is populated with Figure 11 - Framework of  responsive network. Source: Sterk (2005). Used with permission. 79  interactive arts examples and settings of  relative small scale. However, these projects are valuable to our discussion because they address user participation and collaboration in a fashion that has not been typically discussed in architectural projects. Some of  those projects are illustrated in the figure below (Figure 12).  Figure 12 - Examples of  interactive spatial projects addressing user participation. 80  As already argued, despite the fact that the figure of  the inhabitant is very central to the discourse of  IA, the matter of  inhabitant empowerment itself  has been only addressed marginally for the past decades. Furthermore, the lack of  any framework or solid theoretical basis for the discussion of  empowerment is also patent. However, this can hardly be considered a problem only related to the discussion of  inhabitant agency and empowerment. Most of  the field of  IA lacks robust theoretical frameworks to structure its development An even more concerning difficulty relates to the very rare and very limited examples of  built IA instances. The fact that Sterk’s (2005) interaction model is one of  few that explain interaction and system behaviour to a minimally elucidative level of  detail exemplifies the problem. For the most of  the available discussion, IA only exists as a conceptual topic, which also renders it excessively vague despite best efforts.  An IA system must be defined still to viable details, beyond what is typically available in IA literature, before any judgement can be made concerning its suitability as a response to human agency. As it has been stated, it is one of  the objectives of  this thesis to conceptualize, design and develop a true IA system in order to enable further explorations on inhabitant agency in interactive spaces. The first step in the definition of  an IA concept, however, is to understand the specificities of  how such a system may behave and interact with inhabitants. The next chapter will review main concepts in interaction design literature, consolidate important interaction concepts for the discussion of  inhabitant agency, and refine interaction models that can be employed to represent the typical concepts of  IA as depicted in IA literature.        81  5.1 Building around interaction Interactivity is one of  the key concept that presupposes the connection between IA and empowerment. It is also the concept that makes IA differ from conventional architecture fundamentally. It is therefore natural that an investigation of  inhabitant empowerment in IA should focus primary on aspects of  inhabitant-environment interaction. In other words, rather than trying to understand the connection between different spatial forms and agency, it makes more sense to focus on exploring the connection between inhabitant agency and different aspects of  interaction and behaviour. Historically, discussions around the problem of  interaction from early theoretical work in IA were highly connected to the theories of  cybernetics and communication:  interactivity is a conversation. Since then, the scope of  the field has evolved dispersedly and different approaches have emerged. For instance, sustainability and environmental responsiveness started getting great attention since the 1990's (Fox & Kemp 2009), retaining prevalence to this day (Costa Maia & Meyboom 2015). These areas showed little concern for the problem of  IA interaction with inhabitants, treating environmental responsiveness as a matter of  objective performance. A few authors, however, still investigate IA from a communication theory perspective (e.g. Rizopoulos & Charitos 2011), and the idea of  interaction as a conversation marks the very definition of  the field in several of  the studies I have reviewed (e.g. Jaskiewicz 2008). The reader may refer back to chapter 2 for a revisit of  these concepts. In the current chapter, I intend to scrutinize not only further levels of  understanding of  interactivity, but also pragmatic levels that can directly inform the design of  IA systems. The objective is to define, characterize and explore in terms of  agency basic interaction models for IA. For that, I start by presenting a non-exhaustive and commented review of  relevant ideas from fields entirely devoted to the study of  interactivity between people and technological systems, such as Interaction Design and Human-Computer Interaction (HCI). Then I use those insights to carry out the exploration of  the interaction models in IA 82  Based on the current interaction approaches to be found in IA literature, I will propose basic interaction models to be explored in IA, accompanied by a discussion on how certain strategies can be used to foster empowerment.  5.2 Interaction design background and other considerations 5.2.1 IA and interaction design Several papers in IA have drawn upon research in HCI and Interaction Design (e.g. Jeng 2012). Remarkably, IA authors build more often upon HCI research than upon IA's own contributions (Costa Maia & Meyboom 2015). However, the models they reproduce do little to bridge the gap between what is done in HCI and the particularities of  IA, especially when considering the problem of  empowerment. For this reason, this chapter will review concepts from those fields directly and develop them in the context of  inhabitant agency.  5.2.2 Goal-oriented frameworks In the literature, a countless number of  studies can be found to propose models or frameworks for interaction involving complex system (e.g. Card et al. 1983, Frohlich 1992, Schomaker 1995). Among these, a few prominent models stand out to my attention for explicitly incorporating the idea of  user's goals as a central component. As it has been already said, the notions of  empowerment or agency refer exactly to the capability of  people to act in pursue of  their own goals. Thus, interaction models that are built around the intention of  facilitating people's achievement of  their goals are of  particular value to this research. Among the models surveyed, the popular “layered model” proposed by Donald Norman (1986) in his Theory of  Action may provide the best reference for the present research. Norman's approach is also closer to key concepts of  some general theories of  communication, e.g. the Layered Protocol theory (Waugh & Taylor 1995), and to the cybernetics view that form the basis of  IA. The layered model describes seven different layers of  user action. On the top layer, the user formulates a goal. The next three layers describe the stages for the execution of  the goal: planning, action specification 83  and action execution. Finally, the three bottom layers describe the feedback of  the action executed: perception, interpretation and valuation of  the system's state. The input and output flows of  information are clearly marked in the model. Norman (1986) understands that during the interaction process, users need to bridge the Gulf  of  Execution (input: planning, action specification and action execution) and the Gulf  of  Evaluation (output:  perception, interpretation and valuation). The basis of  such model is the argument that people think in terms of  goals and intentions, which are psychological variables. However, as Norman (1986) argues, “the task is to be performed on aphysical system, with physical mechanisms to be manipulated, resulting in changes to the physical variables and system state”. Thus, between the goal, a psychological variable, and the physical actions required upon the given mechanism there is a large gap, resulting from the discrepancy between psychological and physical variables. Likewise, the system's display of  its state must be interpreted in terms of  the original goal, creating a new, asymmetric gap. The following image presents a diagram of  the model (Figure 13).  Norman (1986) acknowledged that this is a simplified model of  the real-world problem. In reality, some stages of  the layered model might be skipped or repeated. Goals might be changed or generate Figure 13 - Layered model by Norman (1986). Adapted by the author. 84  child-goals. In some situations, the user is even reactive to events, as opposed to starting an interaction with defined goals and intentions. The simplification is, however, helpful in understanding the overall process. It also helps on speculating the specificities to be encountered when addressing IA systems. The illustration below presents an initial, basic diagram of  the model applied to a IA system that only performs for output physical adaptations and that is essentially responsive rather than (human-like) intelligent, a common conceptual setting for IA projects27 (Figure 14). This model application is presented here for exemplification of  how the layered model can help investigate empowerment processes in IA.                                                        27 The models represents the type of  IA interaction defined by the second group of  IA authors presented in the last sections 5.3 and 5.4. Figure 14 - Layered model adapted to basic IA system. 85  The diagram represents a model in which goals define a situation of  inhabitant agency towards architecture. That is, in such case, the goals refer directly to the architectural object. One specificity of  the diagram above refers to the fact that no output translation is required, given the IA system changes itself  and the physical transformed system is the output in its most accessible format already. Another specificity refer to a narrower Gulf  of  Evaluation that result from the lack of  necessity of  mapping output formats. While in conventional desktop computers a common strategy to reduce the Gulf  of  Evaluation it to create an illusion that the user is working directly in the problem domain, in IA the problem domain is the real world, immediately apprehensible. Additional – complementary or intermediate – forms of  output are possible in more complex systems and will be discussed briefly. Concerns with modes of  input, however, will be present in all situations, even if  the input is not deliberate. Bongers and van der Veer (2007) explore the different ways in which input and output messages can be considered in IA. These authors review HCI literature and propose a multimodal framework for interactive systems, including IA, where the interaction space occurs closer to the human space than the machine space. A modality, as they explain, refer to a communication channel, and the combination of  multiple modalities are commonly explored to achieve a higher bandwidth of  interaction. Bongers and van der Veer (2007) summarize the following dimensions of  a multimodal interaction space: • Levels: (physical), syntactic, semantic, (task), (goal); • Modes: symbolic, iconic, para-linguistic, involuntary, subconscious, continuous; • Senses/modalities: seeing, hearing, touching. The authors claim that any interaction style can be placed in this space. An interaction style is, however, “not a place in the Interaction Space but a trajectory through it, particularly described in the levels (getting from the goal to the action, and back again analyzing the results of  the action)” (Bongers & van der Veer 2007). The authors describe a process particularly similar to the layered model by Norman (1986). However, they focus on the levels, modes and senses associated with the stages of  the interaction process. 86  Despite the importance of  understanding the different modalities of  communication in an interactive process, I believe the current research will benefit further from a discussion of  general models and strategies than of  specific modalities. In this case, it might be more useful to classify IA systems with regard to the strategies behind the use of  different modalities than with regard to the specific selection of  channels. For instance: Does IA responds to inhabitants only through changes in its physical state? Does IA use different modalities as part of  its mode of  response? Does IA use different modalities as intermediary steps before physical response, such as to ask if  the user agrees with a certain behaviour? These different strategies would have an impact on how the interaction model is arranged. Another important concept present in the two previous figures and that have not been discussed yet is that of  mental models. Mental models figure as a background pane for some of  the mental activities during interaction, influencing their framing. The next section discuss this concept in further detail.  5.2.3 Mental models Mental model is a central concept to the field of  HCI. Upon exposure to a system, users can develop a mental model of  that system; that is, a conceptual understanding of  what the system is and how it works. As Norman (1986) puts it: I believe that people form internal, mental models of  themselves and of  the things and people with whom they interact. These models provide predictive and explanatory power for understanding the interaction. Mental models evolve naturally through interaction with the world and with the particular system under consideration [...]. These models are highly affected by the nature of  the interaction, coupled with the person's prior knowledge and understanding. The models are neither complete nor accurate [...],but nonetheless they function to guide much human behavior. Mental models are also important concepts in early discussions around IA (e.g. Negroponte 1975, Wellesley-Miller 1975), as they are very relevant to the artificial intelligence debates of  the time. When addressing IA as an intelligent participant in a conversation that manifests understanding, the user will have not only a mental model of  the building, but also a mental model of  himself, and a mental model of  the building's model of  himself. All of  these are important factors influencing the interaction. 87  Blackwell (2006) explains that the description of  the mental model as a user’s internal data representation was derived from several research streams in the 1970s and 1980s. It encapsulates knowledge from psychological and anthropological traditions in one “objective, formalizable, and symbolic entity” to be used by engineers, who are not familiar with mind-related sciences. The idea of  using computational descriptions of  the user’s mind in design popularized in the late 1970s, followed by a discourse of  empowerment. It was said that users would be beneficiaries of  the user model, through which the privileges of  programmers and scientists would be extended to others by via of  making computational abstractions more accessible (Blackwell 2006). It was the beginning of  the “desktop” metaphor, which is not by any means left uncriticised but which is thought to be part of  the computer democratization revolution to have occurred in past decades. Considerations of  mental models in the context of  IA raises some challenges. The first one is that people typically already have strong mental models of  what buildings are and how they behave. Also, given the fact that the built environment is composed of  different juxtaposed layers, which extend themselves in a continual fabric, it might be difficult for users to build unified mental models for IA – or for an ecosystem of  IAs. Scholtz and Consolvo (2004) point out a similar question regarding Ubiquitous Computing. They ask: “how do users know when they are in a smart room, and how will they know how to interact with such a room?”. In fact, IA can easily go from empowering to oppressive if  inhabitants of  the space cannot understand the system. Given these difficulties, I believe that metaphors provide a useful way to study different forms of  IA interaction, especially with regard to empowerment. The issue of  metaphors is directly related to that of  mental models. Metaphors are intended to encapsulate an understanding of  how a system is expected to work a priori, as part of  a deliberate design effort. That is, they seek to start with the desired mental model users should formulate, one that is familiar and pertinent to the problem domain, allowing designers to conceptualize a system design based on that information, not the other way around.  88  5.2.4 Metaphors for empowerment In this section, I do not aim to cover the UI design strategies commonly found in HCI textbooks when addressing metaphors (Blackwell 2006). I propose, instead, to discuss typical metaphors and their relation to user empowerment, as this debate is one already open for exploration. With regard to computer interfaces, Weller and Hartson (1993) argue that direct manipulation interfaces, through metaphors such as tool and model world, provide the most empowering environment28 for users. For the authors, empowerment is about one's confidence in personal knowledge and in the ability to take actions based on that personal knowledge. Weller and Hartson (1993) founded their arguments for direct manipulation metaphors in the cybernetic idea of  feedback as central to the operation of  human systems and their interactions with machines. From this perspective, closed-loop styles of  human-computer interaction speeds a person’s learning of  the system through trial-and-error exploration, thus expanding knowledge and confidence. “Rather than just being a tool that extends human capabilities”, they argue, “the computer in an empowering environment is part of  a control loop that includes the human user”. The tool metaphor is characterized by a number of  aspects, one of  them being transparency. Weller and Hartson (1993) uses Heidegger's example of  a hammer for analogy: “[t]o the person who is hammering, the hammer as such does not exist”. During use, the hammer is taken for granted without explicit recognition of  it as an object, only arising to the foreground in the event of  a breakdown. The authors explain what this concept mean for interaction design: In a proper direct manipulation interface the domains in which actions are generated and interpreted are designed so that the user is not called upon to deal with complexities that belong to other, less appropriate domains. The interface designer has created the language, indeed the world, in which the user operates so that it is not a jumble of  domains. This world has ontological simplicity, making the network of  tools seem ready-at-hand, rather than presenting situations of  nonobviousness [...].                                                      28 The empowering environment “utilizes the computer’s strengths in structured symbol manipulation to empower human accomplishment through a division of  labor: the machine handles the routine mechanics of  a task while the person is immersed in its higher-order meanings” (Dede 1987 apud Weller & Hartson 1993) 89  This ontological simplicity, however, carries with it constraints and biases that have already been discussed in section 4.2 of  this document. Another metaphor related to direct manipulation is the model world metaphor. It consists of  giving users the illusion of  acting upon the objects of  the task domain directly. The real or virtual problems are presented in the domains that users conceive them; and the interaction is designed so that user can assume the computational representations are the things they refer to (Weller & Hartson 1993). The tool and model world metaphors are in fact the basis of  current direct manipulation paradigms of  human-computer interaction. But how are they pertinent to IA? The model world metaphor is of  clear relevance to the discussion of  inhabitant agency in architecture: as already suggested, in IA the object of  manipulation is the architecture – or the world – itself. In situations of  complex behaviours and communication channels, however, extra representation layers may still be constructed on top of  the real world. Given the appropriate model world metaphor of  this additional layer, inhabitants may continue to perceive their actions as having direct effect on the world. The tool metaphor might be particularly relevant in situations where the inhabitant goal is external to the architecture or the built environment, and instead requires the use of  architectural spaces for support in achieving said external goals. We can conceive a hypothetical situation where the system setup allows for the perception of  IA as being a tool of  its own making, thus being both the tool and the world. This could create ambiguous forms of  realization, but existing examples were not found for examination. Another relevant metaphor for the discussion of  IA is that of  human-human interaction. As it will be discussed in section 5.3, a considerable number of  authors in the field of  IA conceive the problem of  interaction as one of  conversation with a human-like intelligent building. The human-human interaction metaphor takes the form of  “conversations for action”. Weller and Hartson (1993) explain that these conversations entail an interplay of  requests and commitments that are directed toward explicit cooperative action. Domains of  conversation are established where common pre-understandings allow for communication with a minimum of  words and conscious effort. Similarly to the tool metaphor, persons only become explicitly aware of  the structure of  conversation when a breakdown calls for corrective action (Weller & Hartson 1993). 90  Waugh and Taylor (1995), however, argue that independent participants in a conversation hold different values and goals, even if  similar, and that at some point these goals can be conflicting. According to the Layered Protocol theory, the authors specify three “independences” in a human-human interaction metaphor: independence of  design, independence of  sensing mechanism and independence of  action. They explain these concepts in the following terms: Independence of  design means that the processes for generating and interpreting communication are not identical in both partners; independence of  sensing mechanism means that neither partner can be certain of  what the other is actually sensing; independence of  action means that neither partner is certain as to all of  what the other partner is doing at any given moment. Given these conditions, neither partner can guarantee the reception of  a particular message by the other, regardless of  the amount of  redundancy used to encode it. (Waugh and Taylor, 1995) Waugh and Taylor (1995) warns that, because two intelligent entities cannot resort to redundancy to ensure a message was decoded without errors (the way machines do), they must resort to the notion of  feedback. Feedback is used to indicate if  a message was received correctly or if  some problem exists. This has been repeatedly discussed in the context of  intelligence and IA. Weller and Hartson (1993) observes that interactive systems “built upon the conversation metaphor enable the user to gain the 'power in the abstractions that language provides'”, however this sort of  interface denies to the user direct engagement with the objects of  his/her interest. The lack of  direct engagement might be prejudicial to the perception of  inhabitant agency in architecture, when compared to a direct manipulation condition; however, this drawback might be compensated by effective communication and performance of  the system. Many other models, interfaces and metaphors of  interaction could be discussed. However, their sources are fragmented, and little further has been found regarding possible connections between metaphors and empowerment. The last concept I address extensively in this review of  relevant HCI literature is that of  embodiment. This concept can be studied complementary to the metaphors already discussed.  91  5.2.5 Embodiment Fishkin (2004) provides a classification of  both embodiment and metaphors in relation to Tangible User Interfaces (TUI). Although his categories of  metaphors do not contribute much to the discussion of  IA, he presents an interesting scale of  embodiment that could be used in the context of  IA, after adaptation. His understanding of  embodiment refers to how closely tied is the input focus to the output focus in an interaction: “To what extent does the user think of  the states of  the system as being ‘inside’ the object they are manipulating? To what extent does the user think of  the state of  computation as being embodied within a particular physical housing?” (Fishkin 2004). I believe that embodiment is a critical dimension of  IA. Different impressions of  a system may foster very different attitudes towards the architecture, as well as very different perceptions of  empowerment. The importance of  this dimension of  IA is expected to become clear as I discuss the four levels of  embodiment I propose for the field. Despite being based on the work by Fishkin (2004), the classification I propose diverges significantly. After trying to apply his classification unmodified, it became clear that IA required something better tailored to its particularities. The four levels of  embodiment I propose are described as follows. Full:  the state of  the object is fully embodied in the object. That is, inhabitants engage with an architectural entity and see the effects of  their actions on the very same entity. Thus, inhabitants perceive themselves as interacting directly with the building, which changes its own state in response to the inhabitants. Coupled: the output is tightly coupled to the focus of  the input. Inhabitants must use tools or coupled interfaces of  a different domain to influence the architecture. For instance, inhabitants may use a tablet device to communicate with the building. Inhabitants still perceive the building as an interactive entity that changes its own state according to the interaction, but the interaction itself  must be conducted through an interface that translates the inputs. Disconnected: the interactive entity is disembodied from the architecture, although a link persists between them. It is useful to think of  the fictional examples of  “HAL 9000” from 2001: A Space Odyssey (1968), or “computer” from the StarTrek series. The entity with whom the inhabitant 92  interacts is no longer perceived as the building itself  (or the ship, in the examples given). The building is an inanimate, although actuated, object. The interactive system is rather perceived as a component of  the building, which in turn has the power to affect change to the whole building. Thus the inhabitant affect changes to the building indirectly, through the interactive entity. Detached:  the interactive entity is disembodied from any architecture and may establish links with different architectural elements or layers when desirable. A speculative example would be the case in which personal mobile assistants, such as Apple's Siri or Microsoft's Cortana, could connect to a flexible room or building and act as the brain, or one of  the brains, of  that interactive architecture setting. Fishkin (2004) argues that as embodiment increases, the ‘‘cognitive distance’’ between the input mechanism and the result of  that mechanism decreases. Thus, full embodiment would have great potential for inhabitant engagement and directness of  action, which Weller and Hartson (1993) indicate as important determinants of  empowering interfaces. This setting also provides supports for interaction to happen seamlessly during activities, functioning as a “calm” system. Full embodiment, however, may limit the ways that interaction can occur, especially regarding the input of  more complex messages. Coupled embodiment, on the other hand, could expand what is possible to achieve. Interaction through auxiliary interfaces would allow for the end-user programming of  complex behaviours, for example. The need of  an intermediary tool, however, would require that the user have both access to the intermediate interface and sufficient motivation to access it; thus if  the tool is not omnipresent, the interaction only supported by the tool would require the inhabitant to actively reach for it, potentially disengaging from the activity of  interest. The disconnected and detached embodiments are not pertinent to any discussion of  IA that I have ever come across. We may question if  such examples could qualify as IA at all. They seem to escape what is typically understood as IA in the field, yet they are a natural evolution of  the embodiment levels, as well as reasonably possible settings. Finally, it must be said that levels of  embodiment can be studied from different perspectives and with different outcomes. For instance, Fels (2004) defines four types of  relationships between person and instrument that can be categorized depending upon how deeply embodied an object is into a person 93  or how deeply embodied a person is into an object. The relationships established is depended on the person's perception. These perceptions are: 1) the object is external to herself  and responds to control; 2) the object is embodied within herself, i.e., an extension of  herself; 3) the object is external to herself  and does not respond to control; and 4) herself  is an extension of  the object. The categorization proposed by Fels (2004) talks about interfaces for musical instruments, proposing an alternative way to look at HCI and design for expression and pleasure. They could not be immediately applicable to IA, if  IA is not discussed in those terms. However, Fels’ approach to interaction with regard to the aesthetics of  the forming relationship results in interesting observations. So far, the concepts considered in this thesis were crosscutting and did not explore the longer-term development of  a relationship between interactive system and user. It is worth questioning if  inhabitants could feel embodied by an IA system they are a part of, as opposed to being an autonomous subject who actively engages with the system in a two party interaction. It is also interesting to speculate on the forms of  empowerment that would emerge from these situations. It is possible, for instance, that feelings of  awe in architecture would contribute to a person's perception of  being embodied in the system. It is also possible that complex perceptions of  belonging, resignation and power would develop. This approach to the study of  embodiment is, however, fundamentally different to the approach adopted in the present research, and is not considered complementary to it.  The classification I propose ranges from the interactive ethos being completely embodied in the architecture to being completely disembodied. Fels' (2004) classification, on the other hand, does not refer to the locus of  the interactive ethos. It refers to relations of  control between subject and object, which are also of  importance. In the next section, I discuss more variables that I believe to be important components of  the inhabitant empowerment framework, but that unfortunately have little supporting literature.  94  5.2.6 Other variables: more aspects of  relevance for understanding IA interaction Apart from the main concepts already approached in this chapter, related concepts exist that can be productively incorporated into this discussion. I will explore a few which I believe to be relevant to how IA systems are perceived by inhabitants. The first of  these is the concept of  integration. Several authors in the field of  IA have criticized existing automated systems as being add-on systems (e.g. Jaskiewicz 2013), that is, they are not perceived as part of  the whole architecture, but as an isolated element. Examples of  such is the elevator system. Even when the elevators demonstrate some level of  intelligent behaviour, they tend to be perceived as an isolated system rather than an IA component. Similarly, a network of  smart appliances and components, typical to smart homes settings, may not be perceived as an integral part of  interactive architecture, but simply as an add-on system in a static and conventional architectural environment. On the other hand, projects where the building enclosure is the only element of  responsive nature, for instance, figure in IA publications as examples of  interactive buildings. Examples abound, such as the famous Institut du Monde Arabe, by Jean Nouvel. In these cases, the enclosure is perceived as an integrated part of  the architecture, and not as an add-on system. Note that add-on systems may present full embodiment, yet this full embodiment does not refer to the architecture, but to the isolated system only. For example, a smart elevator might present full embodiment, being perceived as the integral entity that encompasses the system’s ethos, yet also being perceived as something independent from the broader building, not integrated. Where integration is complete, full embodiment might be perceived as pertaining the entire building or space. I believe that levels of  integration can only be solved during the design stage, through an effort of  conceiving interactivity comprehensively. However, empirical tests are still required to identify the main determinants of  such integration, given it is a rather subjective problem. Additionally, I have not found any formal study of  the problem of  integration in IA. Scale of  interaction is another related concept that could be explored. The steering wheel of  a vehicle, for instance, is a representation of  a larger effect, i.e. the entire vehicle's direction. Sometimes the interaction in architectural settings may happen at a one to one scale. It is also possible that the input in IA is of  small, localized dimension, yet the resulting effect is of  the entire building's scale. Scale of  95  interaction may be a complementary notion to the levels of  embodiment, but little is found in the literature about it. Nonetheless, I expect scale of  interaction to have some influence in inhabitants' perception of  empowerment. I would speculate that the larger the scale of  the response, the greater might be the perception of  empowerment. Another crucial set of  variables, however, refers to something that has not been discussed so far: the inhabitant him/herself. As has already been suggested in chapter three, particular characteristics of  individuals, such as locus of  control, have an influence on how people perceive agency. In this section, I will address individual fluid preferences that are situational and related to specific interaction events, as opposed to constant personality traits. The first one is about situational preferences for engagement or disengagement. IA is not only a system, but it is also the environment in which people conduct all of  their daily activities. It is always present. In Metadesign, the same user will assume different and non-concomitant roles during the use and development stages of  a system, depending on the situation at hand. These roles change back and forth between “passive user”, “power user”, “domain designer”, etc, even if  the user is an expert developer (Fischer & Giaccardi 2006). In IA, it is possible that an inhabitant is at same time designer and user of  the same system. However, situations will appear in which inhabitants will prefer to be only users or only designers. People might also want at times their environment to just be static and unresponsive, non-interactive. Thus, people's perception of  IA will depend on whether they want or not to be engaged with, or to be engaged by, IA in a given situation, for a number of  personal reasons, regardless of  their primary goals or how IA could assist in these goals. Inhabitant's situational preferences for level of  control must also be taken into account. Sometimes, inhabitants might wish they have full control of  their environments, analogously to driving a sports car. At other times, inhabitants might prefer to let go of  control and focus on other things, analogously to being a passenger in a limousine. Different authors would argue inflexibly for different levels of  control.  Heinich and Eidner (2009), for instance, present a critique against the “limousine” form of  treatment: 96  It almost seems as if  the developers of  the “intelligent houses” presuppose a passive inhabitant, who wants to be disburdened of  as many tasks as possible, to be looked after, guarded, and entertained. Architecture offers here the wrapping for application programed and predetermined by specialists. On the other hand, a few authors make an argument against the “sports car” form of  treatment. Cetkovic (2012) denounces the problem of  giving people full control of  everything, putting inhabitants under cognitive demand and potentially limiting their interest in engaging with IA. Similarly to Marc Weiser and his advocacy for “calm technology”, Cetkovic (2012) warns that if  all environments are to compete for the attention of  the user, the consequence will be a dissonance and overload of  signals and events - a scenario which the user would try to avoid or ignore altogether.   However, it is not possible to draw rules for situations where engagement or control would be desirable and for when they would not. It is not possible because these preferences can vary greatly with culture, values, age, mood, habits, affective attributions, among countless others. It is, therefore, important to consider inhabitants' empowerment towards the intended empowering system itself: ideally, they should be able to choose between different levels of  control. Other variables can also be mentioned here that have been already presented in previous chapters, such as strategy of  context awareness design, intelligibility of  system, and initiative of  interaction. It is expected that several more relevant concepts were left out of  this review. Yet, I believe that the main determinants of  how people may perceive and interact with IA systems have been established, and will be able to inform the description of  interaction models of  IA.  5.3 Introduction to the problem of  interaction in IA The purpose of  this thesis is not to invent new or improved models of  interaction for IA. Instead, I aim to delineate typical models of  interaction already described in IA literature, operationalizing them to further detail, so that they can inform the development of  archetypical instances of  interactive spaces. Therefore, this section will formulate an introduction to the descriptions of  IA interaction commonly found in the literature. 97  Overall, despite the many exceptions, the large majority of  publications addressing IA seems to treat the whole interaction process as a black box. Again, the lack of  built, fully functional IA buildings or spaces might be the culprit for the lack of  specificity. With most projects being very simple reactive systems, or solely speculative altogether, interaction feels like a given and invariant issue. In general, I observed that the descriptions and analysis of  interaction that can be found in IA publications may be roughly classified in three groups. The groups are hardly isolated categories, but rather sequent marks in a continuum. The first group of  authors assume that IA will not only have human-like intelligence, as it will interact as such (e.g. Adi & Roberts 2010, 2011; Achten 2013). Interaction happens via natural speech as well as deictic and representational gestures, following the “put-that-there” paradigm, and possibly extending to cover the whole breadth of  human communication forms. Negroponte (1975) comes to suggest this kind of  building may be like a new member of  the family. Calderon (2009) discusses the social-political possibilities involved in IA's active participation in society, as a citizen. In such cases, the problem of  personal interaction becomes a problem of  personal relationship: what kind of  personality does my house have? Does it want to help me with my chores today? Was it flirting with my boyfriend? Am I keeping a sentient slave? Interaction in such conditions is easily deflected into the wider discussion of  autonomous artificial intelligence, which far exceeds the scope of  this research. I, however, personally believe that this sort of  intelligence may be desirable in a number of  entities and applications, including ones that may directly influence architecture29, but the built environment itself  is probably not one of  these cases. The second group of  authors is by far the most numerous (e.g. Eastman 1972; Fox & Kemp 2009), although their understanding of  IA seems to avoid the discussion of  interaction in detail. They are the group that the black box critique most suitably fits. These authors describe systems that will intelligently learn all it needs to know by observation, requiring only corrective feedback when necessary. Yona Friedman would call such approaches paternalistic. Matters of  human-like intelligence are not immediately relevant to this group, even if  the system intends to mimic human-like learning. In these cases, IA is the perfect machine that can anticipate needs when these needs are reasonably                                                      29 For instance: “HAL 9000” from 2001- A Space Odyssey (1968), or “computer” from the StarTrek series. 98  predictable, provide logical spatial support to activities it understands, and allocate/manage spatial and functional resources in ways to better support specific goals. The machine is efficient and invisible. The interaction black box precludes an in-depth analysis of  different interaction strategies, because of  what appears to be two underlying assumptions: 1) the machine is nearly flawless and can successfully learn and adapt to changing conditions without the need to bother inhabitants, and 2) the inhabitant wants to be disburdened of  as many tasks and requests as possible, expecting IA to act as a calm technology. What happens when the inhabitant does want to take control or interact, however, is mostly overlooked. The third group of  authors, perhaps of  smallest representation, describe the emergent behaviour of  distributed intelligence and/or the organic-like constant adaptation of  a building to the ecosystem it is inserted in (e.g. Pan & Jeng 2008). Interaction with inhabitants is undefined, possibly occurring in different ways, but above all it is non-deliberate. This kind of  IA is perhaps the one that most closely approximate the natural environment around us. Explorations in this area, however, are too vague to establish a discussion about person-environment interaction modes. Several publications in IA, of  course, are expected to escape this simplified classification arrangement. However, after reviewing a significant number of  publications in previous endeavours (Costa Maia & Meyboom 2015), it so appears that a majority of  interaction descriptions and suggestions will be easily encompassed by the three groups described above. Nevertheless, it has also become evident to me that much more research is still needed in both the conceptual and the pragmatic issues of  inhabitant-IA interaction. For the purposes of  my research, I will suggest a new group of  interaction, on top of  the ones presented so far from the literature. This new group does not have representatives in contemporary literature in IA (or, at least, they have not been found). Yet, the proposition to include this new group is pertinent when considering the debate of  technological vehicles of  participatory design and of  empowering interfaces in computer sciences. The new group is presented in the next section, before all groups are consolidated in interaction models in section 5.5.  99  5.4 One more interaction for inhabitant agency In his book from 1975, “Soft Architecture Machines”, Negroponte puts forward his notion of  what a computer enhanced, responsive architecture should be. He shares with many other authors the idea of  an architecture that can adapt itself  to changing needs. “The general assumption”, he claims, “is that in most cases the architect is an unnecessary and cumbersome (and even detrimental) middleman between individual, constantly changing needs and the continuous incorporation of  these needs into the built environment”. Thus, Negroponte (1975) explores the increasing removal of  the architect and his design function from the design process, until the physical environment is conceived with “the ability to design itself, to be knowledgeable and to have an autogenic existence”. Not every author, of  course, endorses Negroponte's view of  a completely autogenic environment. Most authors, however, do imbue IA with some degree of  autogenic character in their discourse. The idea of  a change of  state is inherent to the common understanding of  IA. This change of  state may be predetermined, but most often it is said to be based on context and changing needs. The concept of  interaction seems to imply an indeterminacy (or at least avoid hard determinacy) of  any IA outcome, in opposition to traditional architecture being a finite process, designed and built in a top-down, fully predetermined manner. However, if  the architect is eliminated as an immediate translator of  needs, culture, values, etc, something else must take its place in defining the parameters for a resulting design, or for a change of  state. In the interest of  fostering inhabitant agency, it can be easily argued that the inhabitant himself  must be the one to set the new parameters. This can be done (1) by allowing the user direct control, or (2) by definition of  an emergent system that responds to the actions of  the user, like a flock of  birds whose behaviour responds to disturbances, or (3) through a learning by observation process. In either case, the design must be responsive to the user. These roughly relate to the options addressed in the literature, except for the one where the inhabitant is given full control. Interestingly enough, this option in not discussed. For this reason, and with an interest in inhabitant agency, this section will try to develop such option further. If  IA is to be designed as a learning system that can adapt to unforeseen conditions,  the strategy that is most recurrently discussed in literature, this implies that the system possesses initial rules of  what adequate spaces, supports and responses for any activity might be. Even if  corrective input is allowed, 100  this may be still considered a highly deterministic approach. It also presents serious technical difficulties that have been discussed in the previous chapter, especially regarding current limitation of  context-awareness in machines. On the other end of  the spectrum, allowing inhabitants direct control of  the system can be overwhelming. As already mentioned, Cetkovic (2012) talks about the problem of  information overload in a situation where every piece of  technology competes for users’ attention. He recalls Mark Weiser’s warning on the need for “calm technology” and advocates for peripheral awareness as a main channel of  interaction between IA and inhabitants. However, if  we are discussing inhabitant agency and empowerment, would not just giving people full control over the IA system be the immediate answer to the problem? Maybe in some cases and not others. For instance, some forms of  empowerment may arise from behaviours that the user might not be able to exert full control over, or the constant need for control upon the means may hinder achievement of  certain goals. Furthermore, if  a system is completely controllable, it is difficult to make a case that it can still be understood as IA. Not a single publication in the field describes such a system for IA, and it generally does not fulfil the most basic definition for the term. This system would rather be an adaptable architecture with automated functions (e.g. executing a command to move a movable wall, instead of  pushing the wall yourself). IA, to be IA, must involve some levels of  internal computation. One solution to have a system proving great control extents to the user and still classify as IA may be based on the concept of  dynamic stability. Sterk (2006a) explains: [...] dynamic stability [...] enables an automated system to outperform a person who is doing the same job, improving the systems overall performance or safety. For example by removing the need for a driver to concentrate upon controlling a car brake skillfully enough to prevent its wheels from skidding, drivers who have cars with anti-skid braking systems are left with a single very simple operation to perform –  ‘braking.’ As such feedback mechanisms can be used to encapsulate many complicated operations into a single, symbolic action (Sterk 2006a). Having inhabitants focusing on symbolic actions, while leaving the system to provide the best outcomes under the inhabitant's terms might be a very adequate approach to inhabitant agency in IA. 101  In computing, Weller and Hartson (1993) define similar approaches as the most empowering ones. The empowering environment “utilizes the computer’s strengths in structured symbol manipulation to empower human accomplishment through a division of  labor: the machine handles the routine mechanics of  a task while the person is immersed in its higher-order meanings” (Dede 1987 apud Weller & Hartson 1993). The distinction between control possibilities is explained by Weller and Hartson (1993) as genres of  control loops. The second genre, they say, “informs the user immediately of  state changes resulting from each small input action, but the computer system is not structured to help with the problem-solving process in the specific application domain”. This is a case where settings could hardly be considered IA. The third genre they discuss, however, is the one that they have been advocating as empowering: “the computer provides functionality to help in the problem-solving process”. Such system is referred to as a hybridized model by Sterk (2006a), who claims it to be both self-regulatory and participatory. In IA literature, however, I have not found any description or project defining how such a system could be designed, or how it could behave, except for Negroponte (1975). The author believes that a human-like intelligent system is the only way for an adequate level of  assistance in the problem-solving process to be effective. I have not merged this kind of  assisted control strategy group with the human-like intelligence group because it is not true that every author seeking one would also be seeking the other. Negroponte (1975) is perhaps the only author I have come across to make this bridge explicitly, that is, to suggest that human-like intelligence can be used to give inhabitants an effective form of  extensive control that is, at same time, assisted and collaborated. Other authors, like Yona Friedman, describe assistive systems that provide inhabitants with feedback on the consequence of  their design decisions, without the need for human-like character and interaction.  Friedman’s work is not here considered the primary example of  this group of  interaction because it is not specifically presented in the context of  IA. More generally, descriptions from IA literature would fall in the general groups presented in the previous section. In this section, I have exposed a few considerations on what could make an interesting system design for inhabitant agency in IA. It is more of  a thought record than an extensive investigation of  possibilities. The purpose of  this research is not to devise, a priori, the best interaction strategies for 102  empowerment, nor to provide specific design guidelines.  However, because the notion of  empowerment seem so close to the notion of  extensive control, I have chosen to define a fourth “type” of  strategy to be investigated, alongside the three already discussed in the previous section. I strongly believe that the means of  interaction is one of  the most determinant aspects of  how any inhabitant will perceive their interactive environment and of  how that environment empowers him or her towards his or her goals. It is not possible to discuss IA, or speculate on its social impacts, without specifically defining its models of  interaction. For this reason, the next section will seek to consolidate four basic interaction models that will serve as the grounds for a less speculative investigation of  inhabitant agency in IA. In the following chapters, the interaction models will be further developed, implemented and tested in a real world scenario, thus providing generalizable information on how IA, in its archetypical forms of  interaction with inhabitants, may support the argument for inhabitant agency.  5.5 Consolidating interaction models of  interactive architecture for inhabitant agency In the previous two sections, four different groups of  IA interaction descriptions were presented in the terms these descriptions are typically found in IA or broader literature. In this section, these descriptions will be encapsulated in defined models of  interaction. Ultimately, I used these models to prototype and test the different archetypes of  interaction with regard to inhabitant agency. The four models are termed as follows: self-adjusting model, direct manipulation model, human-like intelligence model and emergent behaviour model. The self-adjusting model refers to a self-adapting space that requires little deliberate inputs from inhabitants (most of  corrective nature) and accepts only logical, machine-like arguments for self-improvement. This model is intended to anticipate needs and assist inhabitants towards their goals, without requesting great involvement from users. In doing so, and assuming it provides the correct kind of  assistance when needed, it takes away from the user the cognitive load of  making certain choices and demands, concerning the interaction itself, and concerning all informational aspects of  which  a “calm 103  technology” can spare its users. Thus, by reducing cognitive load, this system maximizes overall performance of  the necessary tasks to reach any goal. Fox (2010), for instance, uses an example of  how a movable cabinet can assist inhabitants in retrieving food items as desired. Upon the understanding that the inhabitant is preparing to cook, the self-adjusting setting would automatically make the cabinet's spice shelf  within reach30, thus facilitating the completion of  the task. Apart from the actual physical work that would be otherwise required to reach a high cabinet, the system also takes away from the user the need to plan for that action. If  the goal of  the inhabitant refers to changing the house's behaviour extensively or to reconfigure the organization of  the architectural spaces, however, the self-adjusting model would provide little support. It would also be of  little help when facing new situations or ones it still does not understand. User input is a secondary aspect in this model, and agency towards architecture as a goal in itself  is largely neglected. The possible modalities of  interaction in this model are expected to occur in two different levels: the physical transformation level and the corrective feedback level. In the physical transformation level, interaction is largely involuntary and subconscious, whereas corrective feedback may occur in a variety of  different communication channels. Other concepts such as embodiment, integration and scale of  interaction are undefined and design dependent. For the future purposes of  this research, the metaphor of  the self-adjusting model is plainly that of  self-adaptation (Figure 15). There was little I could find in terms of  metaphor to further substantiate this model.                                                       30 Elaboration on the example was done by me. 104   Figure 15 – Intended mental model for the self-adjusting interaction model.  The next interaction model, the direct manipulation model, has a direct association with the model world metaphor. However, different possibilities of  interaction may bring the direct manipulation model closer or further from the world metaphor. For example, in this interaction model the inhabitant may directly cause the effect in the environment they intend to achieve, such as pushing a wall to make it re-position. In this case, the scale of  interaction is one to one, and the interface is the domain of  action itself. However, the interaction design might request of  the inhabitant the use of  abstract gestures for controlling changes, or even the use of  a desktop computer interface. These designs would impose different scales of  interaction, possibly different levels of  embodiment, and certainly different distances in Norman’s (1986) Gulfs of  Execution and Evaluation. The use of  extra layers of  interface between IA and inhabitant brings advantages and disadvantages. For one, as already suggested, they may require extra steps of  domain translations, distancing inhabitants from their goals. On the other hand, a pure application of  the world model metaphor necessarily requires an “ontological simplicity” of  the action domain (Weller and Hartson, 1993), limiting what is possible to achieve. Regardless of  the interfaces of  interaction, Figure 16 illustrates the overall mental model expected of  inhabitants in this interaction model. 105   Figure 16 - Intended mental model for the direct manipulation interaction model.  The next model, the human-like intelligence model, has been already extensively discussed. The metaphor of  human-human interaction, presented in section 5.2.4, is integrally pertinent to this model. In sum, it describes an artifact (in this case, a building or architectural space) that shall behave as a person, potentially just like the characters Lightning McQueen in “Cars” (from Pixar, 2006) or Herbie in “The Love Bug” (from Disney, 1968). Although these characters are anthropomorphic cars, not buildings, the analogy may still provide a good understanding of  what a functional artifact with human-like intelligence and behaviour can mean. The main distinguishing design factor in these systems, therefore, is that of  defining the social role and the personality of  the IA system. I do not wish to be overly redundant in discussing this model. The interested reader may refer back to sections 5.2.4 and 5.3 of  this chapter for a revision of  the discussion already presented. Negroponte’s (1975) work is perhaps the most instructing material in this subject, and it has also been dispersedly described throughout this manuscript.  Figure 17 illustrates the overall mental model expected of  inhabitants in this interaction model. 106   Figure 17 - Intended mental model for the human-like intelligence interaction model.  Finally, the last interaction model to be delineated is that of  emergent behaviour. The emergent behaviour model can be exemplified by the metaphor of  the coral reef. It is an evolving system that responds to context and inhabitants locally, with no higher-level unified control to coordinate its behaviour towards high-level goals. Instead, the evolution is guided by local responses to local stimuli, and the higher-level conformation of  the architecture is the result of  emergent behaviour. Emergent behaviour, or Emergence, “is a process whereby larger entities, patterns, and regularities arise through interactions among smaller or simpler entities that themselves do not exhibit such properties” (Emergence, n.d.). One interesting development of  the coral reef  metaphor is that such systems do not completely assume different states to support a new situation. Instead, the situation creates a change in the overall system, which motivates a systemic change. The system evolves from the new situation (instead of  towards a higher-level objective), underlying in the idea of  evolution that the mark of  previous states remain as determinants of  the next state. The emergent behaviour model does not act directly to support inhabitants' activities. However, it is possible that the incremental changes triggered by inhabitants will give them a feeling of  co-creation (Wlaszyn 2011) and ownership, analogous to the construction of  informal human settlements. If  this is the case, it is possible that some degree of  inhabitant agency towards architecture would be fulfilled. 107  I could not find in literature relevant material to endorse a discussion around a coral reef  metaphor. It does not map well to other common metaphors, including the ones already reviewed in previous sections.  Figure 18 illustrates the overall mental model expected of  inhabitants in this interaction model.  Figure 18 - Intended mental model for the emergent behaviour interaction model  It is clear that the definition of  the interaction models, as presented so far, does not provide us with sufficiently specific understandings of  how each type of  IA may work in practice. To this point, every argument regarding the potential impacts of  IA on inhabitant agency are just as speculative as they were at the beginning of  this thesis. However, the delineation of  the four interaction models provides a framework upon which more constructions that are technically specific may be operationalized. For the purposes of  this chapter, and in the definition of  “types”, further specifications would prevent the models from being sufficiently representative of  the groups identified in IA literature. Instead, the interaction models set the basis for a broader range of  possible individual designs, one of  which will be described, assembled and tested in the next chapters. In any of  the interaction models, due to the lack of  specificities, any individual design will accumulate a number of  design decisions in different domains. These decisions, as well as other factors altogether, will in turn influence the relation between architecture and inhabitant in terms of  agency. For reference, and based on what has been discussing throughout this chapter, I propose a list of  dimensions that are expected to play a role in how inhabitants should perceive and interact with an IA 108  system. The list is not directly employed in the evaluation of  the IA apparatus developed in the course of  this research; however, it served as a guideline of  the different dimensions the design should purposefully consider.  5.6 A record of  important interaction concepts on inhabitant’s perception of  IA Similarly to Vermeulen et al. (2013), I propose a reference list of  dimensions expected to play a role on the research problem at hand. The list summarizes several aspects that have been discussed so far in this document.  Importantly, these interaction aspects focus on the inhabitant-IA interaction after the inhabitant is sufficiently familiar with the functioning of  the space. It does not include aspects regarding learning (e.g. how difficult it is to learn how to operate the system) and it also does not include affective aspects related to any form of  emotional attachment resulting from continued use. The dimensions are listed below. They are divided in three groups. Under “personal” are dimensions that refer to a person's intrinsic characteristics that have an influence on perceived valences of  empowerment. Under “general” are IA system dimensions that can be measured in any IA system, regardless of  use. They refer to the system design and, most importantly, to the way inhabitants perceive the system. Under “task specific” are dimensions that measure the adequacy of  the IA system in relation to the goals and tasks performed in a specific situation. Lastly, under “situational preference” are the dimensions that measure the particular predispositions of  an inhabitant in a specific time and event. Because most of  these concepts have been already discussed in previous chapters, they will be simply defined in this section. Personal Locus of  control: Locus of  control is a well-studied concept in psychology. It refers to an individual's overall tendency to believe they can control events affecting them. People with strong internal locus of  control will tend to take responsibility for events, e.g. the results of  an exam, while people with 109  strong external locus of  control will tend to put responsibility on external factors, e.g. on the teacher. Locus of  control may have an effect of  a person's perception of  agency and control with regard to an IA system. Value of  environmental control: Value of  environmental control refers to the extent to which an individual personally values having a say on aspects of  the environment they find themselves in. Higher appreciation for environmental control is expected to have individuals cultivating such as a goal when opportunity is available; meanwhile, no appreciation for environmental control at all will allow for no connection between control opportunity and empowerment. Value of  assistance: Value of  assistance refers to an individual's appreciation for third party (spatial) support. It may regard personality traits, such as an individual's preference for carrying activities independent and individually, or for having assistance on tasks. It may also relate to an individual's personal perception of  the built environment as inadequate or sufficient for regular activities. General Intelligibility of  behaviour: Intelligibility of  behaviour refers to how clear and coherent is the system's behaviour to an observing inhabitant. Metaphor of  interaction: Metaphor of  interaction refers to the overall interaction strategy adopted by the IA system, and how the designers of  the system intended it to be apprehended by inhabitants. Modalities of  interaction: Modalities of  interaction refers to whether the IA system communicates and acts by means of  physical response only, or if  other modalities are adopted. Modalities can be complementarity, thus using extra channels to tackle intended outcome; or they can be intermediately, thus using extra channels to facilitate communication with inhabitant and improve the adequacy of  the physical response. Ease of  communication: Ease of  communication refers to the level of  difficulty perceived by the inhabitant in trying to pass on or retrieve information from the system. Levels of  embodiment: Embodiment refers to the extent to which inhabitants perceive the state of  computation as being embodied within the architecture or the architectural system/element. 110  Levels of  integration: Integration refers to o the extent to which inhabitants perceive the interactive system as being integral component of  a building, as opposed to being an add-on system. Scale of  interaction: Scale of  interaction refers to the proportion between the inhabitant's input scale as well as the inhabitant's own scale, and the scale of  the spatial outcome. Initiative of  interaction: Initiative refers to whether interaction needs to be explicitly requested/initiated by the inhabitant; or if  the system will automatically perform as necessary, thus taking the initiative. Vector of  control: Vector of  control refers to an inhabitant's perception of  control/influence hierarchy between herself, others and the system. Task specific Domain of  action: Domain of  action refers to whether the interactive components of  the system are in any way related to the domain of  the activity a given inhabitant is interested on. For instance, if  the activity of  interest is directly related to levels of  light (e.g. sleeping) an interactive facade may act in the right domain, because it has the ability to control levels of  light. On the other hand, a smart plumbing system will not have the ability to act in the right domain, because nothing in the sleeping activity can be supported by plumbing. Inhabitant-system goal alignment: Inhabitant-system goal alignment refers to whether the IA system's internal goal is set to assist inhabitants, whether the IA system's internal goal does not involve the interest of  inhabitants (e.g. the outcomes benefit a third party and/or doesn't take inhabitant's intentions into account), or whether the IA system's internal goal is in fact set to oppose certain goals of  inhabitants (e.g. restrict access to unauthorized areas). In other works, whether the IA system is there to help you, make your life difficult, or it just does not care about you. Contextual alignment: Based on a system's internal goals, contextual alignment refers to whether inhabitants perceive the behaviour of  the system as adequately addressing such goals in the given situation and context. For instance, if  the system's goal appears to be: keeping inhabitants comfortable, are the actions taken by the system context sensitive and adequate for the activities taking place in that space? 111  Spatial fitness: Spatial fitness is the concept proposed by Charles Eastman for IA. It refers to the relative amount of  effort required (in physical, psychological, social or economic terms) to carry out certain patterns of  human activities in a particular environment. Perception of  task performance: Perception of  task performance refers to the inhabitant’s own judgement of  performance in any given task Situational preference (at moment of  interaction) Engagement preference: Engagement preference refers to whether, in that particular moment in time, due to any number of  factors, the inhabitant would prefer to be engaged with an interactive system or not. Control preference: Engagement preference refers to whether, in that particular moment in time, due to any number of  factors, the inhabitant would prefer to hold control or to let go of  control of  the adaptations taking place in the environment.  It must be mentioned that, as it might have been observed by the reader, the dimensions listed in this section do not focus on the objective design characteristics of  the IA system. They focus, more generally, on the inhabitants' perception of  the system, of  their valued states/tasks, and of  the interaction. This operational focus on the perception of  the design, rather than on the design objective parameters themselves, has precedents. For instance, Thue and colleagues (2011) focused on the players' perception of  the video game design rather than on the technical design specifications that led to player agency. Thus, if  certain perception happens by accident or coincidence, it still provides valid information for understanding the phenomena, instead for composing unaccounted error or noise. Finally, the dimensions listed are presented as a summary of  different interaction aspects of  relevance to the problem of  inhabitant agency in IA. It concludes the literature review on the topic, and demarks the end of  the first part of  this manuscript. At this point, all the general literature review has been presented, and all the theoretical discussions have been covered. 112  The next part of  this thesis, comprising all of  the remaining chapters, will build upon the theoretical basis established so far. It will describe a user-centered approach for design and research in Interactive Architecture, focusing on the relation between interaction and inhabitant agency.                    113                   114  6.1 Research problem Chapter 6 initiates the second part of  this thesis, which, based on the theoretical foundation presented in part one, will demonstrate an approach to explore, empirically, the plausibility of  Interactive Architecture’s (IA) claim to foster inhabitant agency. The approach has its own goals and guiding questions, which are distinct from the overarching goal of  this thesis. That is, while the overarching goal relates to applying and testing the new approach, the approach itself  requires a well-defined question to be presented at the onset of  the process.  The research problem that the new approach is going to tackle, for the purposes of  this thesis, has been already discussed in previous chapters.  For clarity, it can be summarized and stated as follows: Inhabitant empowerment is a critical but overlooked aspect of  interactive architecture.  Although empowerment has figured centrally in early debates around IA (see chapter 2), although core concepts of  IA extensively support inhabitant agency (see chapters 2 and 3), and although interactivity has been recurrently associated with democratization and empowerment of  users (see chapter 4), no empirical evidence currently exists to support these arguments and validate the use of  IA in the present architectural landscape. Again, as already argued, it is important to generate the necessary evidence to inform IA’s development and to support its suitability as a solution for existing demands in architecture. The next chapters will present an approach that is user-centered and evidence-based as a reference to future design and research in the field. The next section will present the research question the approach will be employed to answer.  6.2 Research question Based on the gaps and opportunities identified in part one of  this thesis, the following research question was set to frame the investigative process described in part two: 115  How different forms of  interaction influence inhabitants' experience of  Interactive Architecture? Can such experiences, rooted in different interaction models, promote inhabitant's agency and empowerment towards their interactive environment? Specific hypotheses will be presented when specific experiment designs are introduced.   6.3 Research overview The research question can only be answered when inhabitants are given the opportunity to experience an IA space and report on their experience. Thus, the first step towards addressing the research question is designing and building an interactive space that can be inhabited.  The next chapters of  this manuscript will, in the sequence:  (1) Describe the design process of  an IA space;  (2) Test the design concept using a user-centered design method, in order to refine the design concept and to gain further insight on inhabitant’s overall use and experience of  IA; (3) Develop and describe the final apparatus, including the methods to prototype different models of  interaction; and  (4) Conduct a user experience study on inhabitant agency in the assembled apparatus, providing a procedural template to data collection and analysis in future research.       116  7.1 Overview In order to carry out this investigation, a new system must be developed that adequately represents the concept of  Interactive Architecture and that abides by the types of  interaction and experience being studied. The first, most convenient, and possibly most interesting approach for the current research should be to acquire data from inhabitants of  a diverse number of  existing interactive buildings. However, as it has been repeatedly argued, the existing examples of  IA are very limited in quantity and maturity. They are also not conceived to foster agency, which could likely render uninteresting results. Given the predicament of  this first alternative in the current state of  IA development and uptake, the solution is to design, develop and implement appropriate instances of  IA to support the user-centered experiments here proposed to address the research question. This document starts with explaining the main requirements for the IA concept to be developed. Next, it explains the approach to address each requirement individually. Finally, it presents an exploration of  design concepts and a preliminary design proposal.  7.2 Initial requirements The foci of  my research, as well as the resources I have available to pursue them, pose a number of  initial requirements for the new IA system. The main requirements are stated as follows: - The possibility of  inhabitants to change or influence their architectural spaces in a meaningful way; - The need to construct an inexpensive apparatus; - The possibility of  inhabitants to interact with their interactive environment spontaneously, thus approximating the experience inhabitants would have with IA in a non-experimental set-ting; - The possibility to explore the four interaction models of  IA as defined in chapter 5 of  this thesis. 117  Requirements 1 and 2 are addressed together in the following section, given their significant relationship to each other. Next, requirements 3 and 4 are addressed separately.  7.3 An inexpensive IA system that is about core architectural components 7.3.1 An argument for soft architecture The focus on inhabitant agency towards their architectural spaces implies the possibility of  allowing lay users to influence significant components of  architecture with ease, in ways that may not be pre-defined. However, the modification or actuation of  traditional architectural components, especially flexibly and in real-time, is known to be a difficult and expensive problem to tackle.  The study of  IA systems in so-called “hard architectures” is a problem that has been acknowledged since the beginning of  the discussions in the field in the 1960's. Alternatively, designers have chosen to employ new materials, or even new forms of  materiality, in order to enable the exploration of  IA concepts within reasonable technological and economic constraints.  Brodey (1967) is one of  the first to refer to intelligent environments by the name of  “soft architecture”. Although his article does not dive in specific forms of  execution, Negroponte (1975) points out that Brodey adopted for his explorations a pallet of  elements that can be considered literally soft, such as air, light and sound. To this day, “soft” elements define a considerable number of  IA projects. Inflatables and pneumatics, for example, have been used in several IA installations such as Muscle NSA (by the Hyperbody group) and Bubbles (by Michael Fox), as well as in a number of  research prototypes (e.g. Khoo et al. 2011). Even water curtains have been employed to redefine space, as a substitute for “hard” materials, such as in the Digital Water Pavillion (by Carlo Ratti). Considering conventional architecture, which is a composition of  solid materials and void, a highly malleable architecture could require the employment of  efficient self-assembling nano-robots (Fox & Kemp 2009) which still face a long road of  development ahead. Thus, following the example of  others, it appears to be a sensible decision to employ “soft” materials in the development of  the present IA system, given the difficulty of  making current “hard” architecture not only responsive but also responsive in more than a few predefined ways. 118  Nonetheless, it must be noted that “soft” materials and/or systems may describe an infinitude of  possibilities. The next subsections will explore how “soft architecture” may be used in the current project, and which specific systems may be better suited to meet the requirements at hand.  7.3.2 Changing architectural spaces one layer at a time The definition of  an architecture that can modify one or more of  its features in response to computational data characterizes what we refer to as Interactive Architecture. However, the idea of  built environments that can be modified by human beings in varying scales and time spans is part of  a much older and much better explored field than IA. One of  its concepts, valuable to this project, is the concept of  levels or layers. In his early work, Habraken (1961) suggested the introduction of  different levels of  decision making concerning the built environment. He initially defined three main decision-making levels: tissue, support and infill, respectively referring to the urban fabric, the base buildings and their fit-outs. Stewart Brand (1995) has also identified different layers in buildings, which are expected to change at varying timeframes: Site, Structure, Skin, Services, Space Plan, and Stuff. Habraken’s and Brand’s models have been discussed to further detail in section 4.4.1 of  this thesis. The present project will focus on only one of  those levels or layers: Habraken’s infill, or Brand’s space plan, which I consider to be equivalent. They refer to the internal partition of  building floors and overall spatial organization of  a plan. The choice of  this layer alone is justified by several reasons, the main of  which are: - Infill, or space plan, is the layer that more easily and realistically gives itself  to the use of  “soft” architectural elements; - The definition of  infill layers is more purely related to the concern with inhabitant agency, while outfill layers may also incorporate responsiveness to weather and other external condi-tions; - According to Habraken & Teicher (2000), the different layers of  the built environment are hierarchical; that is, layers which are lower in the hierarchy can transform without affecting the higher layers, but the opposite is usually not possible; thus by focusing on the lowest layer (infill) I do not need to concern myself  with adapting other layers (e.g. structure, site); 119  - Lower layers pertain to the decision-making domain of  fewer people, which allows for more manageable situations during the conduction of  the study; - By reducing number of  interacting variables, the use of  only one layer allows for a more mean-ingful analysis of  inhabitants’ experience of  IA; that is, for whatever results that are reached we can pinpoint them as being fully produced by the action of  interactive infills.  7.3.3 Exploring a medium for interactive infill  So far, I have advocated for developing an IA system that focuses on a building’s infill layer and uses “soft” elements in redefining the building’s infill. There are, however, a number of  possibilities for the use of  “soft” materials in this case. None of  them is without disadvantages or figures as an evident best alternative for this project.  The following image (Figure 19) briefly compares different options, including actuated “hard” elements for reference, according to the following criteria: cost (monetary), flexibility (to what extent it can transform and adapt within its domain/function), versatility (whether it can exercise more than one function), and engagement (whether inhabitants can engage with the elements in a natural and/or realistic fashion). 120   Figure 19 - Comparison of  different strategies for the development of  an interactive infill system.  121  For this research and for what is feasible to achieve within resource constraints, I can make use of  a significant pallet of  soft, manipulable materials; or I can simulate the actuation of  “hard” architecture in virtually reality, in ways that are yet to achievable in the material world. Both strategies have positive and negative points. The use of  soft elements provides a limited flexibility needed for under-defined behaviours, however it also makes it difficult to create systems that can be read as architecture. Negroponte (1975) endorses a critique to Brodey's work that focuses on the difficulty of  grasping the relevance of  his “soft architecture” apparatus to architecture in general. Virtual Reality (VR) also counts with its own benefits and limitations. While it allows for the visual experience of  an unimaginable number of  IA possibilities, it significantly restrains the engagement of  other senses. This difficulty of  interaction, especially concerning haptic and kinesthetic feedback, can be a problem in architecture, given most activities taking place in space involve some degree of  physical engagement. Furthermore, VR can cause nausea in some people, limiting the duration of  experiments and possibly the number of  participants to complete the experiments. Despite of  limitations, several projects have been finding human behaviour in VR to be equivalent to their real-world behaviour in different situations (e.g. Nee et al. 2015), including the appreciations of  architectural settings (Stamps 2010). I developed a VR application where “hard” IA could be simulated and experienced, using the game engine Unity and the VR hardware Oculus. Figure 20 illustrates an outside view of  the interactive building as it could be seen in the stereo VR headset. The building had interactive internal levels (platforms) and partitions, as well as interactive lighting, fenestration and access ramps. Initial tests were conducted with three subjects. In two of  the cases, the subjects suffered from nausea before they were able to complete the 20 minutes task asked of  them during the tests. Despite best efforts to improve the comfort level of  the application, the problem persisted. The experience also suggested that issues with engagement and spontaneous occupation of  spaces could be a difficult problem to solve in this kind of  VR environment. In the end, I decided to explore different options for this research, discarding the use of  immersive VR via head-mounted displays as a first alternative. 122   Figure 20 - An interactive building in VR developed to test the media’s suitability towards IA user experience research. Unlike the use of  “soft” architectural elements, the investigation of  IA in VR is still incipient in the field. Adi and Roberts (2010, 2011) present the only examples I have come across where IA in VR is used to test inhabitant’s response to this type of  spaces. They made use of  a cave automatic virtual environment, thus not needing to address some of  the problems associated with head mounts. Nevertheless, their IA setting and interaction was of  exceeding simplicity, providing little support for more complex explorations. Some of  the problems with both VR and soft materials can be overcome if  solutions in the broader mixed reality continuum are considered instead. If  virtual components, such as virtual walls, are brought to the realm of  the real world, the incredible flexibility of  digital information is maintained, while giving inhabitants the opportunity to occupy the space in unstructured ways and in unrestricted numbers. An example of  this kind of  interactive space is the “weightless walls” project, by Takeuchi (2012). Considering flexibility and cost primarily, the use of  computer bits and pixels is a greatly attractive alternative to any physical material. The transformation possibilities of  bits and pixels are virtually unlimited and cost-free. Additionally they can be transported to the physical world through means of  light projection, using a much simpler apparatus than other alternatives would require. The problem 123  of  using projectors, however, is that the utility of  the system, or its versatility, is restricted to problems that do not require materiality. This limitation will be further discussed throughout the remainder of  this section. All things considered, the use of  overhead projectors to define interactive spaces was the option of  choice for the development of  the present research.  7.3.4 How 2D projections may create interior 3D spaces William Mitchel (1990) defines architecture as “the art of  distinctions within the continuum of  space”, a definition remarkably recurrent in post-modern theory. Hillier and Hanson (1984) explain that “buildings are not just objects, but transformations of  space through objects”. Thus, at an infill level, it can be argued that the differentiation and arrangement of  internal spaces is the main role of  architectural elements. But can this be achieved primarily through two-dimensional marks, textures and colors? In a conventional building, the differentiation and arrangement of  interior spaces is mainly defined by physical walls. However, it is not difficult to suggest that other elements may assume this role. Habraken & Teicher (2000), for instance, present explicit arguments against enclosures being the only ways to define space. They state: “the isolated dolmen erected in Neolithic times still dominates the space around it. Approaching the upright stone, at a certain point we seem to cross a boundary”. Similarly, a countless number of  open plan designs make use of  furniture clusters and isolated elements to organize space, without employing physical partitions. The specific use of  interactive 2D markings as a primary way to organize space have not been extensively explored yet. Examples exist, such as BIG’s entry for the Audi Urban Future Award (Figure 21), but these works are speculative.  124    Figure 21 - BIG’s entry for the Audi Urban Future Award. ©Audi Urban Future Initiative. Used with permission. Retrieved from: http://audi-urban-future-initiative.com/facts/big-bjarke-ingels-group  In the wider realm of  art, explorations of  the concept also exist. One example can be seen in the movie Dogville, by Lars Von Trier, where a small villa is entirely defined by demarcations on the floor (instead of  physical walls) and freestanding furniture (Figure 22).   Figure 22 - Scenes from the movie “Dogville”, directed by Lars Von Trier. Source: Von Trier (2003). © Zentropa. Used with permission.  7.3.5 Initial explorations on representing 3D space via 2D images Two-dimensional images cannot define space by themselves, because space is inherently three-dimensional. Instead, two-dimensional images and projections serve as a signal, a representation of  a volume whose definitions are either merely virtual or invisible to varying extents. 125  The first design concept explorations for projection-based infill spatiality, during the development of  this research, was focused on representing different volumes of  space as defined by variation in temperature. The heat “pockets” would delimit and differentiate the larger space, creating zones and territories. In turn, the image projections would represent the invisible spaces and their organizations, turning them visible to human eyes. This concept was largely inspired by Philippe Rahm’s work, a contemporary architect that has been exploring the use of  elements such as radiation and pressure as a form of  organizing space (Figure 23). However, he only uses these elements generatively and his resulting architecture is static.   Figure 23- Example of  Philippe Rahm’s work with heat and radiation as generative elements. Source: Rahm (n.d.). © Philippe Rahm. Used with permission.  This first design concept proposal in the present project consisted entirely in the differentiation of  space though elements such as heat, light, sound and vibration. The most basic layer of  this system was heat due to its ability to form three-dimensional zones and spaces. The other elements are used to reinforce the perception of  differentiated spaces and to change the qualities of  the architecture created by heat. Figure 24 illustrates this concept. The image in the left shows a heated space surrounded by cold air. Because air and air temperature is invisible to humans, a projector is employed to make the arrangement apparent. The second image (right) shows the actual space being formed by heated and cooled zones. 126   Figure 24 - First design concept proposal for projection-based infill spatiality.   Although the heat zones exist in a three-dimensional space, the color-coded light is only projected to the floor, which mitigates the perception of  entering a new space instead on stepping onto a floor pattern. Preliminary tests, which will be later discussed, showed that the difference in heat alone assisted in triggering the perception of  a three-dimensional zone. A vibrating vest was also adopted to reinforce the idea of  entering a 3D space. Unlike heat, which hardly displays a precise boundary, the vibration can be mapped to a very well defined enclosure. The images below (Figure 25) illustrate the invisible enclosure created by vibration when a person crosses the barrier between spaces. On the left, the visualization of  heat is omitted; on the right, it is used to show the equivalence of  the heat and vibration layers.  Figure 25 - Illustration of  vibration layer in the initial design concept.  127  The following images show the test of  the prototypical setup for this system (Figure 26). The prototype incorporated both the use of  vibration and heat, in order to test whether these elements alone, together with the projection, could evoke a perception of  three-dimensional space.  Figure 26 - Prototype test of  first design concept.  This first prototype was only tested by the author of  this thesis; thus, all the following judgements about it are personal. It was my impression that both vibration and heating contributed to the perception of  a three-dimensional space. However, the specific heat-map pattern projected as a representation of  space was of  ambiguous reading. The lack of  direct mapping between people’s mental models of  spatial partitions and the fluid heat-map pattern generated by this initial concept was one of  the problems identified. Furthermore, creating, maintaining and manipulating “heat pockets” accurately presented itself  unfeasible to the levels required by this concept. As expected, despite its effectiveness in reinforcing the idea of  three-dimensionality of  a space, heat could not be employed reliably to such end. The next design explorations that followed this first concept learned from its lessons. While it is possible and even prolific to use secondary elements in the definition of  space, such as heat, these can also be limiting. For the sake of  flexibility, it was considered a better option to use the projections as a representation of  purely virtual spaces. Thus, the projections should stand alone in its capability of  defining spatiality, even if  other elements are complementarily employed with that aim. The next section describes a more systematic approach to the exploration of  design possibilities. 128   7.4. Exploring design alternatives for floor projections There are countless possible designs for a 2D projection onto an open plan space floor, the purpose of  which being to organize and differentiate space. These designs express not only aesthetic intentions, but also different possibilities of  spatiality and interaction. I propose that, concerning IA, possibilities of  spatiality and interaction (or behaviour) must be the defining aspects by which different designs must be characterized and evaluated. Furthermore, it is apparent to me that these two aspects tend do vary together. The figure below simplify this relation (Figure 27).   Figure 27 - Relation between spatiality and interaction in two-dimensional infill patterns.  The next page (Figure 28) will present different design propositions and their position in the continuum described above. All propositions are based on an office-building floor that would be ordinarily organized as the baseline condition illustrated. The two extreme design concepts shown in Figure 26, i.e. the “defined boundaries” and the “multi-layered” concepts, were selected for further exploration. The next section will present the difference between the two conditions and will describe an interaction design for each concept, considering each of  the four interaction models established in chapter 5.  129   Figure 28 - Design propositions in the spatiality/interaction continuum. 130  7.5. Describing interaction in two opposite design alternatives The exploration of  the different projection designs were based on the concepts’ potential to define spaces and to support specific behaviours (Figure 25). Although the matter of  spatiality may be satisfactorily analysed via rendered images, the matter of  behaviour is considerably less apprehensible. To begin to study behaviour and interaction in the concepts, I wrote a description of  how the systems would work in each case. This exercise was conducted for each of  the design concepts generated during the current exploration. For illustrative purposes, the following table (Table 2) presents the behaviour description of  diametrically opposite concepts for comparison. Each behaviour is described considering the four interaction models established in chapter 5.     Table 2 - Comparative description of  behaviour in different projection-based interactive infill concepts    - Ease of direct control - Resonance with existing mental models of architectural space    - Ease of implementing complex behaviour - Higher levels of abstraction and formative possibilities  131    Users control final disposition through gestures and by directly interacting with boundaries. Computer ensures that out-put is coherent and gives informational feedback on problematic dispositions, e.g. lack of access. Users can directly “push” any boundary to make it move. They manipulate spe-cific edges, as well as merge adjacent boundaries. Specific gestures inside a boundary allows for control of heat and sound. Specific gestures also exist for erasure and creation of new boundaries. Eight intuitive gestures must be learned in total. This way, users can easily re-draw the spaces according to need, and they have a very ample power of defin-ing the final internal partition of a building, as long as it is orthogonal. Users define sets of rules for each layer of territory. Rules are personal. An ad-ditional interface is necessary for users to enter their conditional statements. The rules are layer based, and each layer has two or three possible settings. The layers and settings are defined as fol-lows: - Type: “In” and “out” - Heat: “cool”, “average” and “warm”  - Sound: “isolated” and “open” - Light: “bright”, “medium” and “dark” Because users cannot give direct phe-notypical input, the rules are set using radius and offsets values, as well as an-chor points (e.g. furniture and/or per-son positions). Similar functioning as the “perceived direct control” condition above. How-ever, users do not interact directly with the system and they do not need to re-member any of the command gestures. Instead, an intelligent entity controls the system. The intelligent entity can The ability to directly control the defi-nition of rules (such as in the “per-ceived direct control” condition above) does not belong to the user directly, but to an “intelligent entity”.  The “intelli-gent entity” acts like a person in a con-132  learn about users and might not need instructions or requests for many of the procedures. Otherwise, the intelligent entity communicates with users in a hu-man-human communication fashion, through natural language. The entity works like a human person sitting in a control room overseeing and assisting an operation conducted by a number of human agents in a given space that is controllable from that control room. Of course, technology does not cur-rently exist to support this form of in-teraction. Wizard of Oz method is re-quired for its execution. trol room in charge of facilitating activi-ties taking place in a given space, and with whom users can talk when neces-sary. The “intelligent entity” sets the rules of the space according to what it observes and to what the users may re-quest. Communication occurs through natural language, and users do not need to describe the logic of what they want explicitly. Just like with a human per-son, the communication of intentions or desired outcomes may be sufficient. Of course, technology does not cur-rently exist to support this form of in-teraction. Wizard of Oz method is re-quired for its execution. The self-adjusting model is more rigid than the two conditions above. It offers less possibilities of output and limited opportunity for direct input from users. A standard, base phenotype exists and is adapted depending on use patterns, in a context-aware manner. That is, as us-ers engage in activities, the system rec-ognizes each context and provides the adequate enclosure layout, as well as ad-equate heat and sound levels, for that specific activity and context. Adequate A standard, base phenotype + genotype exists and is adapted depending on use patterns. It is a context-aware system, with an established (although evolving) set of genotypic definitions per activity and context. The logic is concerned with functional arrangements depend-ing on activities taking place, similarly to the condition described on the left.  The output, however, is not dependent on shared perimeter and each “layer” behaves independently, with its own set 133   layout for any activity is established (alt-hough evolving) but parametric, so it is responsive to pre-defined parameters (such as number of people participat-ing). The logic of the system is primar-ily concerned with functional arrange-ment depending on activities taking place.  The output is always based on the drawing of the orthogonal perime-ter with confined properties. Users can only give correctional feedback. of rules. Users can only give correc-tional feedback.  The space presents a rule-based behav-iour that considers perimeters in a co-herent way. The rules, however, do not refer to functions or fitness, they are merely formal. Users’ interactions in a local scale propagates and influences the system at a larger scale, as a way to adapt to the new parameters and find new stability after the disturbance caused by users. Disturbances/inputs can be: crossing of boundaries, direc-tion of movement, still time, etc.  Over-all system can also have intrinsic regu-lating parameters, such as being energy bound. The overall behaviour of the system is inspired by the behaviour of fluids. Logic is network based and discrete dis-turbances propagate in a continuous fashion for one specific layer (again, like fluids, for each independent layers). Disturbances/inputs can be: crossing of boundaries, direction of movement, still time, etc.  Overall system can also have intrinsic regulating parameters, such as being energy bound.   134  7.6 A design proposal on interactive architecture After considerable deliberation, it was decided that the “defined boundaries” concept explored in the previous sections should be selected for further development. The reason for the selection of  this specific concept rests on the paramount issues of  conceptual clarity and proximity to people’s mental models of  infill spaces. Informal conversations with friends and colleagues proved the concept of  “virtual walls” to be easily graspable, while the idea of  fluid territorialities was of  more distant relation to ordinary concepts such as “rooms” and “partitions”. Since the purpose of  this work is to elicit generalizable experiences of  interactive architecture, it is especially important for inhabitants to read the projections as representations of  infill spaces the way they know them. It is acknowledged that should systems like this be in common use, they would perhaps be more sophisticated and less reliant on the visual representation of  conventional elements (e.g. well). However, for this experiment, immediate legibility is required. The following images illustrate the different formative possibilities of  “virtual walls” and “virtual rooms”, as the boundaries are easily redefined to change the organization of  the infill layer of  a larger space (Figure 29). 135   Figure 29 – Interactive infill based on projected “virtual walls” and “virtual rooms”  This concept of  interactive space-plans, in the context of  interactive architecture, is one without built precedents. It is therefore unknown how people would interact with such an interactive infill system, or whether this system would be able to fulfill real-world needs of  inhabitants.  Before further developing the concept and implementing it to full scale, a concept-based, anticipated user experience study was conducted. Apart from acquiring valuable data to inform further 136  development of  the concept itself, in a user-centered design cycle, the diary study also shed interesting light on people’s potential relation to interactive environments in their everyday life. The next chapter describes the anticipated diary study in detail.                 137  8.1 Introduction This study relates to the gathering of  information required to assess and substantiate the initial development stage of  the IA apparatus, which, in turn, will be later used to evaluate the effects of  IA experience on human agency. The apparatus is conceptualized as an interactive architecture system where a building’s physical walls are replaced by virtual walls. For the purposes of  the diary studies, these virtual walls are presented as entities that can be easily created, deleted and re-arranged by users. To prevent cognitive overload of  participants, as well as the risk of  misinterpretations, no specific forms of  interaction or behavior are described. Simply, the system is presented as one that can be easily modified to meet inhabitants’ need. The diary study was intended to probe the possible uses and potential user experiences of  the concept mentioned above. More broadly, it also gathered data and information about people’s perception of  an interactive infill space. It was important that the prototype developed for this thesis was sufficiently functional and engaging from the perspective of  users, in order to support the explorations intended for later stages of  the thesis’ research. The apparatus design must attend certain levels of  usefulness and relevance so that inhabitants feel compelled to interact with the system spontaneously. The problem is that very little is known about when, how and why people would choose to engage with IA systems in their everyday life. It is also unknown whether the specific designs proposed can address real world needs and requirements. Therefore, in order to assemble an appropriate apparatus for the main investigation, the development of  the prototype followed good practices of  user-centered design and product development as advocated in literature (Roto et al. 2009, Vermeeren et al. 2010). Most specifically, the current project focused on the anticipated assessment of  user experiences, which, based solely on initial product concepts, can be employed at early stages of  product development (Sproll et al., 2010).  A literature survey revealed that specific techniques for anticipated user experience studies are still 138  limited in number, even beyond the realm of  architecture, and have not been exhaustively tested. Despite a wider theoretical discussion supporting the importance of  user-centered studies in early design concept stages, specific methodologies are less available. Thus, one of  the contributions of  this thesis lies on applying this type of  study to the problem of  IA. It is important to re-state that this study is presented in this thesis with an objective to demonstrate and report on the suitability of  this type of  approach to the design of  IA concepts. The process is commented with regard to adaptations of  the original methodology and lessons learned along the way.  The study, titled Anticipated Experience Diary for Interactive Architecture, was carried out with 17 participants and is approved by UBC’s Behavioural Research Ethics Board, certificate number H15-02936. Participants only had access to the conceptual description of  the apparatus system, who interacted with the system in imaginary, role-playing situations.   8.2. Research question The current project intended to acquire information directly from potential users in order to inform the design of  the Interactive Architecture (IA) apparatus to be developed. In order to ensure that the new IA apparatus (as well as the sequent experiment design) supports natural situations of  use, the research question was stated as follows: In their everyday lives, when, where, how and why users would choose to engage with an IA system focused on infill customization, given it was a ubiquitous feature in the built environment? The methods used to address this question are presented in the following section.  8.3. Methodology 8.3.1 Research design This project explores the potential user experience of  an IA building concept. Thus, participants did not have access to any physical prototype of  the concept. Instead, participants were introduced to the system’s concept in a video. The participants were asked to imagine their experience with the concept system in their daily routine and to report this experience in diaries. This study is based on the methods 139  proposed by Sproll and colleagues (2010) for user experience assessment in early product development stages. The participants who chose to be study subjects in this research were conducted to the following website: http://interacting.space/diary. The website contains all the instructions necessary for participation. Each step in the instructions section of  the website can be summarized as follows: Step 1: Submit signed consent form. Participants are instructed to carefully read the consent form, sign it and submit it to the researchers, either electronically or in paper form. Step 2: Answer a few questions in a questionnaire. Participants are prompted to fill a questionnaire, whose questions are presented in detail in the instrumentation section of  this study proposal. Step 3: Watch the video. A video explaining the research and the IA system’s concept is presented to participants. Participants are then asked to make use of  imagination and imaginative role-playing in their daily routine for one week. More specifically, they are asked to consider that the buildings they inhabit have the capabilities described in the video, and imagine situations when they would engage with those capabilities.  The concept presented (henceforward referred to as “core concept”) was mostly focused on the possibility of  (re)creating and (re)arranging internal (infill) spaces and spatial boundaries. The description of  the IA system, however, was intentionally vague, and participants were instructed to not limit their imagination to what they assume to be limitations of  the system presented. Additionally, participants were told that, apart from being able to re-define internal partitions, they could also control sound and thermal comfort inside each bounded space. Participants were then asked to imagine the prototype concept in their daily routine. They were asked to imagine as frequently as possible that the buildings they inhabit are instances of  the core concept presented, for the period of  one week. Step 4: Submit diary entries. Participants are asked to keep a diary of  all imagined uses and situations they have experienced. A template for printing is provided in case the participant wants to keep a hand written diary. Alternatively, an online electronic form is also made available for participants to submit diary entries as the imagined experiences occur.  Step 5: Wait for the final survey. After one week, a researcher will contact the participant to inform 140  the 7 days period has completed. Participants are then asked to fill one final survey, composed of  open questions, in order to identify potential problems and gather more information on participants’ experiences.  All the material that participants had access to can be found in the aforementioned website.  8.3.2 Sampling The population of  interest to this study is very comprehensive: it includes all persons who inhabit buildings. The sampling strategy used in this study, however, was opportunistic one. Random and representative sampling is not required, for this study has no inferential ambitions. It is instead interested in qualitative insights from anyone interested in contributing to the research. This means that the results of  the present study must be interpreted with caution. Although the results will accurately describe the anticipated experience of  a group of  volunteer participants, there is no insurance that this result represents the larger population of  all building inhabitants. In order to ensure a diversity of  occupations and geographic locations, a call for voluntary participation was posted online, in social media websites. Specifically, the advertisements was posted in a broad range (as broad as possible) of  social media communities known to the author of  this study and/or that the author could have access to. Paid advertisements were also divulgated on Facebook using the material illustrated below (Figure 30). It is estimated that over 1000 people were reached by the advertisements. 141     Figure 30 - Advertisements posted on Facebook  When potential participants were interested in the advertisements, they were directed to a webpage further explaining the project, as well as giving instructions to enroll. Enrollment was considered complete once participants submit a signed electronic consent form, as instructed in the webpage.  8.3.3 Monetary benefits or compensations There was no monetary benefits or compensations for participation.  8.3.4 Instrumentation All the material presented to participants are available at http://interacting.space/diary for review. All the data collection of  the study was carried out online, and all participants chose to submit their diary entries via the electronic form available in the website. For reference, the questions contained in the questionnaire (“step 2”) are copied below.  Q1: What is your age? Q2: What is your occupation? Q3: In the scale below, indicate your level of  agreement with the following statement: “It is important 142  to me that I have a say on how my environment should be like” (Likert scale). Q4: In the scale below, indicate your level of  agreement with the following statement: “I prefer to let a computer make decisions about the optimum arrangement of  my spaces for me, instead of  needing to make decisions myself  every time I need a different organization of  space” (Likert scale). Q5: In the scale below, indicate your level of  agreement with the following statement: “I prefer to let another person (e.g. an architect) make decisions about the optimum arrangement of  my spaces for me, instead of  needing to make decisions myself  every time I need a different organization of  space” (Likert scale). A paper version of  a diary entry page can be found in the appendices (Appendix A), as well as the final survey protocol (Appendix B).  8.3.5 Data collection and analysis All data was received via electronic forms. The data from the initial survey was graphed and analysed using simple descriptive methods. The analysis of  the data from the diaries was initially based on the methodology proposed by Sproll et al. (2010). The methodology was adapted and expended to take better advantage of  the data collected and to better fit the context of  IA. Further details on data analysis is provided in the results and discussion section.  8.3.6 Protection of  Human Rights  When participants chose to be subjects in this study, it was made explicit and clear that participation is voluntary and that participants can choose to withdraw from the study at any time.  All the data collected from participants was protected and encrypted. Participant’s confidentiality was also protected during analysis and publication, by omitting in the documents any information that may allow for the identification of  individuals.  8.4 Results and discussion Seventeen (17) people participated in the first step of  the study, which consisted of  filling a brief  143  survey about their personal opinions on being able to control the state of  their build environment. The majority of  participants (13 out of  17) had between 25 and 29 years old, which reflect the social circles the researcher had easier access to. The sample was very varied in terms of  participant’s main jobs or occupations, including attorneys, developers, actors, linguists, engineers, teachers, students and others, and had a balanced proportion of  females (n=9) and males (n=8). The initial survey consisted of  a three Likert items, requesting participant’s level of  agreement to three different statements. The results and the statements are shown in the image below (Figure 31).  Figure 31 - Frequency distribution of  responses to initial survey  Most respondents (15 out of  17) agreed or strongly agreed that it is important for them to have a say on their environment. However, respondents were mostly divided regarding whether they would prefer for another entity to make the decisions for them on a regular basis. Although the frequency distribution of  responses (Figure 30) may suggest a preference for ceding control to another human being instead of  to a computer, the difference is not statistically significant. Of  the 17 participants who started the study, 15 continued to its main component: the diary keeping. Together, the 15 participants submitted 66 diary entries, an average of  4.4 entries per participant 144  during a period of  one week. Following the methodology proposed by Sproll and colleagues (2010) for exploring UX potentials at early product development stages, all diary entries were classified according to two aspects. The first aspect is the proximity of  the features that participants idealized for fulfilling their needs in the reported experiences to the original concept under scrutiny. Analysis of  said proximity allowed us to judge the adequacy of  the original concept to different uses and circumstances. The second aspect is the need fulfilled in each reported experience. Proximity to core concept is attributed to each diary entry according to the scale below: 1. Core concept: “The feature or the need fulfilment item is exactly contained in the original core concept” (Sproll et al. 2010). Thus, without any alteration to the original system design, the participant made use of  the system in their daily routine. 2. Similar to core concept: “The feature or the need fulfilment item has similarities with the original core concept” (Sproll et al. 2010).  3. Independent: “The feature or the need fulfilment item is independent from the core concept, but can be integrated into the original core concept” (Sproll et al. 2010).  4. Extraordinary: “The feature or the need fulfilment item has an extraordinary character and cannot be integrated into the original concept” (Sproll et al. 2010). Proximity to core concept is a main component of  this study’s results because the description of  the concept, as presented to participants, was intentionally vague. Additionally, participants were encouraged to not be limited by said concept description, and instead imagine the system as it could be in order to fulfill their needs. Therefore, if  the core concept is not adequate as is, we should expect considerable departures from it in participants’ reported experiences. The classification of  each diary entry according to the proximity levels presented before was conducted by the author of  this thesis (single rater). It is, thus, prone to interpretation and subjectivity. Ideally, to ensure reliability, this type of  analysis should be conducted by two independent raters.  Furthermore, proximity levels were defined regarding two different components of  the diary entries. Sproll et al. (2010) describe the levels as encompassing both “feature” and “the need fulfilment item” together. It was observed in the present study that these components could be rated separately and differently (i.e. they did not always agree with each other). 145  For the present study, proximity to core concept was identified (1) in relation to the experience itself, as imagined and described by participants; and (2) in relation to the needs and problems being reported, considering whether they could be satisfactorily resolved by the features of  the core concept. As an example, one participant described being able to define glass partitions in real time in order to reinforce territoriality. The described experience itself  is not supported by the concept system, because the organization of  glass partitions is not among the system’s features. However, it is entirely possible that the need at hand, that of  defining territoriality, could have been fulfilled by the concept system’s original features. Thus, in this example, the reported experience of  features would have been classified as a level 3 of  proximity, while the need fulfillment would have been classified as a level 1 of  proximity. Of  the 66 diary entries, 55% (n=36) were classified as a proximity level 1 when considering need fulfillment, while only 39% (n=25) were classified as a proximity level 1 when considering the imagined features as reported. The main outcome of  this analysis, however, cannot be conveyed by such aggregated numbers.  The most valuable information provided by this study was the fact that diary entries related to different architectural programs had different degrees of  proximity to the core concept. This means that the core concept, which solely refers to the re-arrangement of  spaces (e.g. instantiation, size, location), their internal ambiance and environmental levels, may be very useful and pertinent to certain architectural programs but not others (which would require the involvement of  more architectural features). The following image (Figure 32) illustrates the total number of  entries per architectural program, and the proportions with which the entries employed the core concept without alterations, for both need fulfillment (under “applicable opportunity”) and described feature (under “described experience”). 146   Figure 32 - Distribution of  diary entries per architectural program, proximity to core concept and need/features 147   It is also important to observe that the different aspects of  the core concept - termed infill space definition, infill ambiance and infill environmental comfort - are also not uniformly reported nor uniformly distributed across the different architectural programs. Infill space definition, or the way that internal partitions are organized, is the aspect most recurrently used overall. Again, however, distribution is not uniform across programs. All the architectural programs in which the infill space definition have level 1 of  proximity to core concept in over 50% of  entries are inherently shared, social spaces: office, living room, pub, library, gym. The conclusion stated above was not one unexpected at the onset of  this study. The redefinition of  internal partitions is important in the continuous (re-)negotiation of  spaces between the users who occupy it. More specifically, the diary entries revealed that there is often a need to define personal or group territories in shared spaces, to define private “no disturb” spaces, and to re-distribute/re-size space depending on size of  groups occupying each area. In contrast, more private spaces such as bathrooms and kitchens required different kinds of  features which relate to physical partitions and furniture. Even the bedroom, where 33% of  entries were in level 1 of  proximity to core concept, these related to either ambience or environmental comfort only.  The following are some statements extracted from the diary entries, which exemplify the social aspect of  infill manipulation. Participant a: "The pub is very crowded and the chairs of  the different tables are very close together [...]. It would be nice if  dividers could be activated between the tables, so that the groups stay more comfortable and the limit of  space between tables are respected.” Participant b: "I want my colleagues to know that I am very focused and any conversation can break my flow [...]. I open an app that lets me control the system and ask for a private space with a soft red light to indicate that I'm focused and not to be disturbed.” Participant c: "Residents of  the complex like to come [to the swimming pool+sauna space] in couples or groups of  people (when they invite friends for example, like in my case). However, there is only one big space [...]. There is a need for separation of  all this spacious room with the swimming pool into several segments [...]. That would create small private areas [...] but still keep the view visible from inside and out.” 148  Several of  the 1st proximity level entries in shared spaces also concerned how the number of  people in certain spaces should define the relative area occupied by that space. Participant d: "The kitchen/eating area of  the place where I work is very small, which prevents all employees from having lunch at the same time. On the other hand, there are empty spaces in other sectors during this time, which are later occupied when people go back to work. [...] I would like to expand the space of  the eating area only during lunch time". Participant e: "Meeting room shortage. Combining and borrowing other people's office space to create a larger meeting room." The examples provided are only a few among many. However they represent what is perhaps the most recurrent opportunities for when and where there core concept is applicable and in line with inhabitants needs. All the diary entries were also analysed in terms of  what are the underlying needs in each reported experience. This is the second main analysis of  the diaries’ data. Sproll et al. (2010) suggest the identification of  the fulfilled needs according to a general list of  basic human needs (e.g stimulation, relatedness, etc). For this study, however, we classified the needs in terms of  modification of  the built environment, which provided the present study with more meaningful results. The frequency distribution of  the needs are shown in the graph below (Figure 33).  Figure 33 - Frequency distribution of  needs, as inferred from diary entry data 149   It is interesting to notice the high frequency of  “create/remove physical barrier” and “assistive action”. Together, these needs configure the majority of  diaries entries that had proximity levels to core concept of  2, 3 or 4. Respectively, they define needs where physicality is required (e.g. “to prevent the dog from accessing a room”) and where the interactive space deliberately help inhabitants conducting activities (“the space lights up in specific areas to remind me to do a certain task in that location”). One last quantitative analysis was conducted on the diary data. It refers to whether the experience of  interaction imagined by participants involved direct action from users, via varied devices, or whether participants imagined some sort of  intelligent or automated system that could act without users’ command. The following image (Figure 34) describes the distribution of  entries according to the aforementioned possibilities.  Figure 34 - Use of  system intelligence or automation  It must be noted that 6 out of  8 diary entries that mentioned assistive action used system intelligence or automation, a clear overrepresentation. At least one third of  automation was used for assistive action. The methodology presented by Sproll et al. (2010) gives great weight to aggregated data analysis (though diagrams, tabulations and quantitative analysis), overseeing a qualitative appreciation of  what 0510152025303540No Yes UnespecifiedUse of system intelligence or automation150  has been reported by the study participants. The authors do not provide a guide for qualitative, case-by-case based learning.  Given the non-representative sample used in the present study, it can be argued that qualitative insights might be even more valuable than the analyses presented so far. The first search for case-specific information from the data tried to identify anomalies on what participants were reporting. However, the data was very heterogeneous, making it unfeasible to identify outliers. Every diary entry had a very particular context to which the report was pertinent.  The first search for case-specific information looked for any situations that were not already expected or anticipated and that, nonetheless, used features bounded by the core concept. Some of  these situations include:   Creating “ambient moods” for helping persons achieve goals, such as waking up. This could be expanded to a number of  situations, capitalizing on the findings of  environmental psychology.  Allowing people to create their own definition of  personal spaces, and assuring this is respected.  Reminding and prompting people for performing tasks by preparing the space accordingly at a pre-specified time.  Communicating statuses with others, such as personal availability, space availability, objects availability, etc.  Having the intelligent space automatically finding out best layout arrangement based on criteria provided by participants, e.g. optimize desk arrangement so that the most people can be facing the windows.  Creating adaptable spaces inside heritage buildings without compromising the original building features. Although the insights listed above could not be incorporated in the final design, which had a limited space for complexity, they inform the features that would be interesting to include in a more 151  sophisticated version of  the prototype.  8.5 Conclusion and limitations The anticipated diary study allowed us to answer the following research question:  “In their everyday lives, when, where, how and why users would choose to engage with an IA system focused on infill customization, given it was a ubiquitous feature in the built environment?”.  Inhabitants mostly used the core concept in shared spaces, in situations where they needed to manage the available space with their peers. They mostly interacted with the space via some form of  direct manipulation means, for varied reasons. It is reasonable to say that the political aspect of  architecture, the one that has been the focus of  this thesis, becomes evident primarily when social dynamics are salient. In other situations, IA appears to approximate much more the role of  a tool, perhaps then sharing more similarities with other types of  interactive systems and devices (e.g. automobile). There are two main limitation in the present study that must be re-stated, in order to allow for a correct interpretation of  results. The first limitation is that study participants are not a representative sample of  any larger group. Thus, given sample bias, it is possible that studies covering different populations would have very distinct results from the one reached in this study. The other limitation concerns the need to interpret and to classify the data in the diaries, which can be a very subjective process. The use of  more than one rater or researcher independently conducting the analysis is the correct way to increase reliability of  results. However, for this thesis, the use of  inter-rater reliability measures was not possible. Another minor limitation also refer to the fact that participants are necessarily suggested by the way the concept is presented. Given the lack of  direct experience with a prototype, participants must form a mental model based on the descriptions and images provided during the study. This must be taken into account when interpreting the results.   152  9.1 Introduction The anticipated diary study, reported in chapter 8, provided a validation for the concept of  interactive infill based on “virtual walls”, at least for inherently social/shared architectural programs. The concept tested in the diary study described giving inhabitants the capability of  reorganizing internal boundaries, as well as controlling sound and thermal comfort inside each boundary. However, especially in the social or shared architectural programs, most of  the experience reports described interaction with infill organization only. Noise and thermal control were less frequent requests and mostly secondary. Based on this information, the IA apparatus to be developed focused on the interactivity of  the infill organization, discarding the features of  noise and heat control. Furthermore, the IA apparatus were conceived as a space where multiple people can occupy at the same time, socially. The apparatus is a prototype of  an interactive space plan space. This prototype is different from typical prototypes in IA in the sense that it aims to produce interaction models rather than physical models, primarily. In order to prevent creating specific expectations about the function of  the space, the IA apparatus was simply advertised as “the interactive room”, a multi-purpose space when people can come to “study, play, chill or just have a cup of  coffee”. The following sections will describe the final design and assembly of  the interactive room, presenting how each interaction model was prototyped.  9.2 System overview The fully developed IA setting, called “the interactive room” was assembled in the school of  Architecture and Landscape Architecture’s (SALA) building, namely Frederic Lasserre Building, at UBC Vancouver campus. It was installed in a large room (room 309) without fixed furniture, contiguous to students’ studio spaces. The interactive system is intended to act as an interactive infill for that room, further organizing and differentiating interior spaces. It can define interactive interior 153  boundaries as well as interactive properties for ambiance within each bounded space.  The interactive room is composed by two wall-mounted short-throw projectors assembled with mirrors, a variety of  mobile furniture, a curtain separating a control space from the rest of  the room, two cameras, and free coffee and snacks available for visitors.  The interactive infill works by defining virtual spaces, mapping them to the real room space, and projecting the location of  the “virtual walls” onto the room’s floor via the projectors. Figure 35 provides an overview of  the overall assembly of  the interactive room and Figures 36 shows photographs of  the actual space (not in function).  Figure 35 - Overview of  the interactive room 154     Figure 36 - The interactive room apparatus. Photos by Rohini Nair.  The main components of  the apparatus are the projectors. The short-throw projectors were assembled with mirrors in a specially made mount, and mounted to the wall almost at ceiling height. Located at opposite sides of  the room, the projectors could cover half  of  the floor space each. Figure 37 shows the mounted projectors.   Figure 37 - Projectors' mount. Photo by Rohini Nair.  As shown in figures 35 and 36, a black curtain separated an isolated control room, from where the interactive infill could be operated. In order to assist the human operator in the control room, as well 155  as to track the position of  inhabitants (depending on interaction model), two cameras were installed in the room. Figure 38 shows one of  the cameras and the control room behind the curtains.   Figure 38 – Apparatus of  the Interactive room. Cameras (right) and the control room (left). Photos by Rohini Nair. The interactive room counted with three movable desks and chairs; one movable chaise and one movable beanbag chair. Additionally, food and coffee were served on a fixed counter. Since the interactive infill implies a constant re-organization of  space, it did not make sense to have fixed furniture in the room. Therefore, measures were taken to ensure all furniture (except for the counter) was easily mobile (Figure 39). This way, a redefinition of  internal partitions can be fully accomplished, via the adequate placement of  furniture, as exemplified in Figure 40.    Figure 39 - Casters on furniture ensure they are easy to re-locate. 156   Figure 40 - Example of  an initial setting without partitions (left) and example of  user organized space with interactive partitions and color (right).  UBC students were invited to come and use the space to conduct their usual schoolwork activities, if  they would like to do so. Participants were also expected to visit and explore the space out of  curiosity or out of  wish to contribute towards the research. The space design was not set to endorse a specific use or activity, nor the experiment design. Instead, participants are encouraged to occupy the space as they see fit. Figures 41 and 42 show the functioning interactive room, with different examples of  infill configurations. 157   Figure 41 - The interactive room. Photo by Rohini Nair.  Figure 42 - The interactive room. Photo by Rohini Nair. 158   The ways with which inhabitants will interact with such interactive infill space will depend on four different interaction models supported by the apparatus. The interaction models are the ones defined in chapter 5 of  this thesis, and are referred to as: direct manipulation model, human like intelligence model, self-adjusting model, and emergent behaviour model. Each of  these is described in following sections.  9.3 System behaviour and operation As already described, the infill partitions are created by projectors mounted near the ceiling, projecting light and color onto the floor. The projections represent the boundaries of  virtual rooms, which can be influenced and/or transformed in different manners, depending on the interaction model employed. The virtual room, and consequently the mapped projections, are controlled by a computer that was operated by the researcher. All the interaction models, except for the Emergent Behaviour model, used Wizard of  Oz method in their execution. This means that an operator was effectively controlling the alterations in the virtual rooms manually. The way the operator conducted the system’s behaviour, however, was different depending on the interaction model being tested, as the operator emulated each specific interaction model accordingly. This was the main method used to prototype the interaction. The Wizard of  Oz method is very common in interaction design and broader user-centered design research. Its assumption is that the full development of  the system is not the main goal of  this type of  research, which is more concerned with users’ perception and experience of  that system. The virtual rooms and partitions are created and controlled in a web application, developed in Javascript by the author. The output image is then mapped to the physical room and projected using two short-throw projectors. The diagram in Figure 43 explain to better detail the entire system. 159   Figure 43 – Control system overview It must be noted that the system described above could have been simplified by the use of  devices such as Matrox’s DualHead2Go. This would preclude the use of  the two extra computers connected to each projector. The control system illustrated in Figure 43 is the same for three of  the interaction models: direct manipulation, human-like intelligence, and self-adjusting. Figure 43 also describes how the Wizard of  Oz method participate in the overall system for those three conditions. It can be argued that, in some situations, Wizard of  Oz is even preferred to a fully developed and automated system. This is because a complete autonomous system would be required to capture all the necessary input for its operation, interpret that data, and execute the correct behaviour flawlessly. Any errors and delays in this process, which are to be expected in this kind of  project, would potentially frustrate users and change their experience. Wizard of  Oz, in these cases, allows for an 160  observation of  user experience without the interference of  technical limitations and errors. The only interaction model that does not employ the Wizard of  Oz’s method is the emergent behaviour model, which has a different control system. More specifically, instead of  a human operator, the entirety of  the system’s behaviour in the emergent behaviour model is controlled by a computer software developed by the author. In the emergent behaviour model, as it will be later explained to detail, the interactive infill responds to inhabitant’s number, position and movement patterns. Therefore, it needs to know the coordinates of  all inhabitants at all times. Wizard of  Oz’s method would require, in this case, the continuous work of  several operators, making it unfeasible. For the purpose of  tracking inhabitant’s position, a system was devised partially inspired by PS Move’s tracking devices. The tracking system developed used two cameras to track the position of  glowing spheres inhabitants could wear on their heads, triangulating the final coordinates from the stereo image (Figure 44). The tracking system was developed in Python using OpenCV. The use of  the tracking gear is also a way to simplify a problem in the project, typical of  prototypical studies. Ideally, this kind of  interactive space would track inhabitants using technologies such as LiDARs coupled with computer vision, which would dispense inhabitants from needing to wear trackers. However, for the purpose of  this study, the use of  a simpler tracking technique was sufficient. 161   Figure 44 - Tracking system overview  All of  the specific characteristics and behaviours of  the interactive room, under each of  the interaction models, will be further described in the next sections.  9.4 Self-adjusting interaction model In the self-adjusting interaction model, the system can recognize and identify each context and each activity taking place inside the space. After activity is identified, the system provides the adequate enclosing area for that activity, as well as adequate ambience and lighting levels.  Adequate layout for any activity is pre-established (although it can evolve via correctional feedback) 162  and parametric (thus sensitive to context, such as the number of  people participating in given activity). The logic of  the system is primarily concerned with functional arrangement depending on activities taking place.   This interaction model follows the following logic flow: (1) to identify which activity is taking place, (2) to identify contextual parameters for that activity, such as number of  people involved, (3) to define adequate area, lighting and color based on activity and parameters, (4) to constantly check for changes in activity and parameters, adapting accordingly, (5) to constantly check whether the last change performed received correctional feedback, (6) if  correction is flagged, undo changes, record learning data and re-run logic flow. Any change in the room always follows these steps. In the current setup, these steps are followed by a human operator, using a Wizard of  Oz method. Figure 45 illustrate the instructions provided to inhabitants for how to interact with the interactive room, under a self-adjusting interaction model.  Figure 45 - Instructions for interacting with the interactive room, under a self-adjusting interaction model  163  Figure 46 exemplifies the response of  the interactive room when an inhabitant occupies it. In the example, the inhabitant enters the interactive room (a) and heads towards the counter for coffee and snacks (b). The space by the counter is minimum, but it expands as it is identified that the inhabitant has entered that space and is occupying it while eating a few snacks. When the inhabitant leaves the eating area towards the lounge space, the eating area retreats while the lounge space expands (c). Next, when the inhabitant moves one of  the desks away from the wall, the internal partitions update to better accommodate the new location of  the desk and of  the inhabitant (d) (e). The inhabitant claps once to indicate required correction. The room then re-runs the steps for self-adjustment, but this time reaching a different configuration than it did the first time, given the learning process (f). Next, when the inhabitant decides to use a larger space for conducting manual tasks, joining two desks together, the interactive infill once again updates to the new activity and context (g) (h). A larger space is defined around the desks and better lighting is provided for the conduction of  the manual tasks (i).   Figure 46 - Example of  inhabitant-room interaction under the self-adjusting interaction model. Photos by Rohini Nair  164  9.5 Direct manipulation interaction model In the direct manipulation interaction model, inhabitants control the final disposition of  infill partitions through gestures and by directly interacting with spaces and boundaries. The system then checks if  output is coherent and gives informational feedback on problematic dispositions, e.g. lack of  access.  The system may also give general feedback during every interaction, informing inhabitants of  general data (e.g. room size, percentage of  total space taken by room, electricity consumed by room size and light levels, etc) and known consequences for specific design decisions. However, in the interest of  simplicity and for the purposes of  this research, feedback was limited to the identification of  potential layout problems. Figure 47 presents the set of  gestures inhabitants could use to manipulate the interactive infill. Most gestures allow inhabitants to act directly on the world domain, e.g. inhabitants can directly “push” any boundary to make it move. Other gestures cannot be mapped directly to what they are meant to control; however, relational proximity was attempted. Using the set of  gestures provided, inhabitants can easily redraw the spaces according to their need, and they have a very ample power in defining the final internal partition of  the space. Figure 48 show an inhabitant re-defining the infill configuration of  the interactive room via the set of  gestures provided. Finally, Figure 49 demonstrates an instance in which a problematic layout triggers a feedback from the system, instructing the user about the potential complication. Due to difficulties in implementing gesture control in this scale, and because the technical resolution of  these difficulties are not the focus on the present study, the direct manipulation interaction model is emulated by a human operator using Wizard of  Oz method. Gestures are observed via cameras installed in the room and the commands are translated by the operator into the control application developed by the author.   165   Figure 47 - Instructions for interacting with the interactive room, under a direct manipulation interaction model  166   Figure 48 - Example of  inhabitant-room interaction under the direct manipulation interaction model. Photos by Rohini Nair  167   Figure 49 - Example of  feedback instructing users of  potentially problematic layout  9.6 Human-like interaction model In the human-like interaction model, inhabitants interact with an intelligent room, which in turn can make changes to its own infill organization. Interaction occurs via natural language, and any requests to the room can be made as if  talking to a human being. Thus, no machine-like commands are necessary. Instead, higher-level commands and conversations can be established successfully.  Figure 50 illustrates the instructions that were given to inhabitants so that they could interact with the interactive room. Once again, Wizard of  Oz method was used to emulate the interaction model behaviour. Wireless speakers were installed in the room and the human operator orally communicated with inhabitants using a voice synthesizing software.  168   Figure 50 - Instructions for interacting with the interactive room, under a human-like intelligence interaction model  Figure 51 illustrates one interaction between an inhabitant and the “intelligent room”. Notice that in the example the inhabitant does not need to tell the room the exact steps it must take to achieve the desired outcome. Instead, the request is made in a much higher level, in a way that it could have been made to another human being.  169   Figure 51 - Example of  inhabitant-room interaction under the human-like intelligence interaction model.  9.7 Emergent behaviour interaction model The last interaction model to be described in this chapter is also the most complex one. The emergent behaviour model needs to be described in terms of  its internal generative logics, given it does not follow a higher purpose behaviour. Because the outcome of  interaction in this model is a result of  a number of  smaller, local interactions, the transformation of  the interactive infill cannot be emulated by a human operator using a Wizard of  Oz method. A human operator could not possibly account for the complexity of  this kind of  behaviour. It must be noted, however, that the emergent behaviour interaction model can encompass an infinity of  different forms of  interactions and behaviours. This description in only one in a very vast and very 170  diverse array of  possibilities. The design of  this specific instance of  emergent behaviour IA is based on the dynamics of  underlying invisible cells (Figure 52). Each cell has a center and a diameter and it competes with the other cells for space. The cells cannot occupy the same space, thus they push each other away in local interactions.   Figure 52 - The underlying logic of  the emergent behaviour interaction instance  171  Without the presence of  inhabitants, the cells will continue to interact with each other, trying to find stable positions. The presence of  inhabitants, however, causes disturbances to the system, influencing the overall dynamic. The specifics of  how the cells react to the presence and movement of  inhabitants will soon explained. However, it is first necessary to explain how the internal partitions, or the infill organization, of  the interactive room is defined based on the disposition of  the invisible underlying cells. The infill partition of  the interactive room is a Voronoi diagram that uses the cells’ centroids as its generative seeds. A Voronoi diagram is a partitioning of  a plane (in this case, the entire floor area of  the interactive room) into regions based on distance to points (or “seeds”) contained in the plane. Each seed defines a region consisting of  all points closer to that seed than to any other seed on the plane. On Figure 52, the Voronoi diagram is drawn in cyan, and the seeds are identified as the center of  the underlying cells. Each of  the Voronoi’s regions configure a Voronoi room in the interactive infill. The movement and travel patterns of  inhabitants inside the interactive infill influence the lighting and the color of  the Voronoi rooms. When an inhabitant leaves a room, that room gets darker while the room that has just been entered lights up. Regarding colors, all Voronoi rooms will tend to reach a calm shade of  blue. However, high movement levels inside a room will cause it to “stir” and reach increasingly warmer colors, such as red. Again, upon rest, the color will try to return to the cool shades of  blue. Apart from color and brightness, inhabitants also influence the position and behaviour of  partitions by disturbing the dynamics of  the underlying invisible cells that define the formation of  the Voronoi diagram. When inhabitants enter a new room, the underlying cell correspondent to that room will inflate (“stealing” from its neighbours) and gain more “strength” in pushing the other cells away. This causes the Voronoi room to increase in size and forces the other cells to re-accommodate. Inhabitants, however, do not have access to the information of  how the underlying logic of  the system works. Instead, they can only perceive the emergent behaviour of  the system (thus the name). Figure 53 shows the instructions provided to inhabitants on how to interact with the room. 172   Figure 53 - Instructions for interacting with the interactive room, under an emergent behaviour interaction model  Figure 54 exemplifies the behaviour of  the system based on the activities of  three inhabitants. The photos in Figure 54 were taken 5 seconds apart from each other. 173   Figure 54 - Example of  inhabitant-room interaction under the emergent behaviour interaction model.   174  10.1 Introduction With an IA apparatus that supports the use of  the four typical interaction models for IA, it is now possible to conduct a user experience study to test inhabitant agency in relation to interactive spaces. This chapter describes a study that can be used in later stages of  IA concept development in order to assess its potential to fulfill its fundamental claims. This study is based on all the precedent discussions introduced to far. It has an ambition to provide initial answers to the research question framing the part two of  this thesis. However, its main objective is to test the user-centred approach proposed and report on the problems and opportunities encountered along the process, laying the basis for later similar studies. The study presented in this chapter is a pilot study and must be interpreted as such.  10.2 Research question As already stated, the research question guiding this study is the following: How do different forms of  interaction influence inhabitants’ experience of  Interactive Architecture? Can such experiences, rooted in different interaction strategies, promote inhabitant’s agency and empowerment towards their interactive environment? The experimental method used to address this question is presented in the following section.  10.3 Methodology 10.3.1 Research design Based on design concept explorations and an anticipated user experience study (unpublished, UBC BREB Number H15-02936), the current research built an Interactive Architecture experimental settings and invited participants to occupy it. Different groups of  participants used and tested four different models of  interaction with the IA system.  Thus, this experiment had a between-subjects 175  design, aka independent measures. One of  the main research design decisions faced in this study related to either conducting a highly structured within subjects study or a non-structured between subjects study. A non-structured between subjects study would allow people to come and go in the space, whenever they wanted, occupying it the way they’d see fit according to their needs and intentions in the space. The advantage of  this design is that it would favor natural situations of  use. People would be able to come and occupy the space in a way similar to when they occupy architectural spaces (e.g. office, home) in their daily routine. The downside of  this approach is that it would require a very large number of  participants, for two reasons. One of  the reasons is that between subjects study designs are known to require more participants, given the total number of  participants are split among the different conditions being tested. The other reason is that the non-structured procedure for participants would allow for many different kinds and durations of  occupancy, resulting in a less consistent data set. More participants are then needed to compensate for the variations. A structured within subjects study, on the other hand, would require less people, since the same group of  people would be able to test all the study’s conditions. However, it would require a greater commitment from the group of  participants, since they could not just come at any time, for any purpose, and to any duration, and since they would have to return for four different days to experience all the test conditions.  Nonetheless, the fact that participants would be able to compare and discuss their experience regarding different models of  interaction could provide much more rich qualitative insight than the alternative. The downside of  this approach is that it would not be able to afford natural situations of  use. It would require, instead, a specific protocol to be followed, such as a list of  tasks for participants to complete each day. There are also known problems with within-subjects designs for measuring specific variables, given participants are influenced by previous experiences of  previous test conditions. This can be partially mitigated by random order of  participation and temporal distance between test days. The very social aspect of  the interactive space-plan concept, as made evident by the diary study, was the element to determinate the choice for the present research. Different forms of  social association 176  and space negotiation could be discouraged in the structured study design, or fail to happen altogether. Additionally, in the structured within subjects design, people’s participation in the study would need to be scheduled and organized in groups, which could pose many technical difficulties. In the end, the non-structured between subjects design was elected for this study. Participants filled questionnaires prior and after experiencing the space. The first questionnaire probed participants regarding personal characteristics and preferences that could play a role in their perception and attitude towards the interactive space. The last questionnaire asked participants about their experience of  the space (using established UX survey material), plus specific questions designed to inquire about participants’ perception of  personal agency towards the space (based on self-efficacy and self-determination theories). In between these two surveys, participants were left free to occupy the space in whatever way they wanted. Participants were observed during their use of  the space. Aspects such as whether participants choose to use the system features, and the situations when they choose to do so, were recorded in written form.   10.3.2 The interactive architecture setting The IA system has been already described in detail in the previous chapter. It was presented separately in order to maintain its relation to the diary study, a user centered design method that assisted in the definition of  the final concept, and to allow for a more lengthy description of  the prototyping process. The reader may refer to chapter 9 to review the description.  10.3.3 Sampling and recruitment Participants for the current study were mainly recruited among students who ordinarily use Lasserre building, as well as other students from the School of  Architecture and Landscape Architecture (SALA). Opportunistically, other UBC students were also invited to participate. Recruitment to participate occurred in two different ways. The first one was anticipated advertisement, in which case banners were publicized in SALA’s buildings up to two weeks prior to the beginning of  the study. Advertisements were also published in an internal bulletin for students at SALA and shared 177  on social media pages associated with SALA students. Anticipated advertisement was intended to target students and staff  that may be interested in the study and interested in scheduling their participation for when the Interactive Room was available. The second form of  recruitment took place during the days when the experiment was running. It consisted of  banners and branding inviting passers-by to enter the space and participate in the research.  10.3.4 Monetary benefits or compensations There was no fixed monetary benefits or compensations for participation. However, snacks and coffee were being served at no cost for participants. Furthermore, after completing participation, participants were entered in a prize draw for the chance of  winning $100 CAD.  10.3.5 Instrumentation and data collection Data collection took place through: (1) initial questionnaire, (2) experience questionnaire, and (3) observation notes. Both the questionnaires and the observation protocol can be found in the Appendices (Appendices C, D and E, respectively). All the raw data is being kept in UBC Vancouver campus in the principal investigators’ computer. After analysis, data was stored in encrypted files.  10.3.5 Protection of  human rights  When participants choose to be subjects in this study, it is made explicit and clear that participation is voluntary and that participants can choose to withdraw from the study at any time. Participants are requested to read and sign a consent form prior to participation.  All the data collected from participants was protected and encrypted. Participant’s confidentiality was also protected during data collection, by omitting in the data any information that may allow for the identification of  individuals. No record was kept of  the video captured by the cameras installed in the room. The video was only be streamed locally in real time, not recorded. 178   10.4 Results and discussion on the data collected The analyses presented in this section are intended as a template to demonstrate how to analyze and present the data collected during the inhabitant experience study described so far in this chapter. Because this is a pilot study, and due to methodological limitations, the data collected cannot be considered sufficient and satisfactory evidence to answer the research question. However, it demonstrates how future research will be able to do so. The study counted with 30 participants in total, divided into four groups in a between-subjects experiment design: self-adjusting room group (n=8), direct manipulation room group (n=8), human-like intelligence room group (n=7) and emergent behaviour room group (n=7). Of  the 30 participants, only 13 filled the initial survey online. From the 13, it was only possible to link the data from initial and post-occupancy surveys in three instances, because most participants did not fill the identification field in the post-occupancy survey. Therefore, it was not possible to investigate the relation between the user experience of  the interactive room and participants’ previous attitudes towards the capability of  control over one’s environment. Nevertheless, the initial survey indicated that most participants are students (13 out of  13) who fall within the age group of  25 to 29 years old (9 out of  13). As shown in figure 55, they largely value independence and having a say on how their environment should be like. They also prefer choosing and customizing their own environment than ceding that power to either a machine or another human being. There is no difference between acceptance of  ceding control to a human or a machine in the sample. 179   Figure 55 - Frequency distribution of  the answers to the Likert scale items in the Initial Survey.  On average, as self-reported, the 30 participants who visited the interactive room spent 15.18 minutes inside the room (SD = 7 minutes). During that time, they tried to interact with the interactive room in average 11.86 times (SD = 10.31). These numbers vary each day as described in the table below (Table 3). Table 3 - Comparison of  length and number of  interactions per interaction mode Interaction mode Reported time spent inside the room Reported number of interactions Average (min.) Standard dev. Average Standard dev. Self-adjusting 15.83 12.42 8 2.45 Direct manipulat. 16.25 6.94 20 14.33 Human-like int. 20.00 8.66 6.5 6.95 Emergent behav. 12.14 3.93 10.17 5.31  People tended to spend more time in the Human-like intelligence room, despite that being the room with which they interacted the least. As expected, due to the nature of  the interaction mode, the direct manipulation room was the one with the higher number of  interactions. A one-way analysis of  variance (ANOVA)31 test showed the difference in the number of  interactions between the groups to be statistically significant (F=3.206, p=0.043). A Tukey post-hoc test, which compared groups in pairs                                                      31 All of  the following assumptions were met: the dependent variable is measured at the ratio level (i.e., it is continuous); the independent variable consist of  categorical, independent groups; there is independence of  observations; there are no significant outliers; the dependent variable is approximately normally distributed; and there is homogeneity of  variances. 180  rather than comparing all groups together, revealed that the difference in number of  interactions was statistically significantly only between the Direct Manipulation and the Human-like Intelligence groups, and only admitting a liberal level of  significance (p=0.056). There was no statically significant difference between other pairs of  groups and in considering time spent in the room as a whole. The short periods of  time that participants spent inside the interactive room, alongside the high density of  interaction (average of  one interaction every 1.28 minutes), portrays a pattern that has been observed in the field. That is: most participants would come to the interactive room to explore the space as a primary intent, not to develop other daily activities inside the space provided. This observation defines a significant limitation of  this study. Any insight derived from the present study must be considered as primarily concerning a first exploratory interaction between an inhabitant and an unfamiliar type of  interactive architecture. The results cannot say anything about the continued use of  an interactive space for daily activities. Future studies must consider surveying the use of  interactive spaces for an extended period of  time, allowing inhabitants to get used to the room. They should also consider allowing this cognisance period to occur outside the umbrella of  a research study, for the condition of  being a research subject may have greatly contributed to the way participants apprehended the space and behaved inside the room. The sequence of  figures presented ahead describe the frequency distribution of  participants’ answers to each Likert-scale item in the user experience survey (Figure 57 to Figure 77). For clarity of  the results, the size of  the distribution bars has been normalized so that 100% of  the respondents for the self-adjusting room and for the direct manipulation room measure exactly as much as 100% of  the respondents for the human-like intelligence room and for the emergent behaviour room. This way, despite the fact that the first two rooms count with 8 participants each and the last two rooms count with 7 participants each, their results can be compared. Thus, the sizes of  the bars are set in percentages, notwithstanding each bar being composed of  blocks representing individualized answers. All figures must be interpreted using the following legend (Figure 56). 181   Figure 56 - Legend to be used to interpret Figures 55 to 75   Figure 57 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 1 of  the user experience survey.   Figure 58 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 2 of  the user experience survey  182   Figure 59 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 3 of  the user experience survey   Figure 60 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 4 of  the user experience survey  Figure 61 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 5 of  the user experience survey  183   Figure 62 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 6 of  the user experience survey   Figure 63 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 7 of  the user experience survey  Figure 64 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 8 of  the user experience survey  184   Figure 65 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 9 of  the user experience survey   Figure 66 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 10 of  the user experience survey  Figure 67 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 11 of  the user experience survey  185   Figure 68 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 12 of  the user experience survey   Figure 69 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 13 of  the user experience survey  Figure 70 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 14 of  the user experience survey  186   Figure 71 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 15 of  the user experience survey   Figure 72 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 16 of  the user experience survey  Figure 73 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 17 of  the user experience survey  187   Figure 74 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 18 of  the user experience survey   Figure 75 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 19 of  the user experience survey  Figure 76 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 20 of  the user experience survey  188   Figure 77 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 21 of  the user experience survey  The figures show that all the proxies being used to understand human agency scored from balanced to high agreement across interaction models: basic agency (as in being able to cause an effect on the world), autonomy (based on self-determination theory), competence (based on self-efficacy theory) and empowerment. Figure 78 provides a brief  comparison of  the four measures.  Figure 78 - Comparative of  measures of  basic agency, autonomy, competence and empowerment  The large majority of  participants agreed that they could influence and/or cause changes to the interactive room. They also agreed that they caused the changes because these changes interested them. Levels of  agreement dropped when participants were asked directly whether their felt competent and powerful. Interestingly, especially regarding competence and empowerment, levels of  agreement seemed to vary considerably depending on the model of  interaction. Statistical analysis comparing the results between the different models of  interaction will be presented in next pages. 189  It can also be pointed out that, based solely on a visual study of  the graphs, the self-adjusting model appears to be the one with the lowest indicators in all measures of  agency, whereas direct manipulation appeared to be the one with the highest. It is also interesting to notice that aspects considered to be directly influenced by agency do not seem to consistently respond to variations in responses to the previously mentioned indicators (Figure 79).  Figure 79 - Comparative of  measures of  meaning, place identity, attachment, authorship and ownership  For more significant results, different statistical analyses were carried out on the survey’s data. The first analysis was the Kruskal-Wallis H test (also called "one-way ANOVA on ranks"). This test is a nonparametric method that can be used to test whether there are statistically significant differences between two or more groups of  an independent variable, such as the different interaction modes in the interactive room, on an ordinal dependent variable, such as the Likert-scale items in the user experience survey. Next, the four interaction modes are grouped in two groups and re-analysed with the method mentioned above. The two new groups are: (1) direct input group, containing the Direct Manipulation and the Human-like Intelligence interaction modes; and (2) indirect input group, containing the Self-Adjusting and the Emergent Behaviour interaction modes. The hypothesis is that regardless of  specific methods, the modes in which participants are able to specifically determine the outcome of  the interactive room would elicit different experiences than the ones in which participants are not, especially regarding agency and empowerment. Thus, in this analysis, the independent variable is whether participants could directly define the outcome or not. Finally, I carried out a cumulative odds ordinal logistic regression with proportional odds on the data. 190  This test is used to predict an ordinal dependent variable given one or more independent variables. It is used in this study to find out whether different items in the survey are correlated, and if  participant’s response to one item can be predicted by their response to a different, independent item. All analysis are conducted using SPSS Statistics software. Using p=0.05 as the cut reference, the Kruskal-Wallis H test showed that there was a statistically significant difference in responses among the different interaction modes in three of  the survey’s items.  There was a statistically significant response to the statement S11 (“I expected more from the experience”) among the tested groups,  χ2(2) = 8.270, p = 0.041, with a mean rank of  22.38 for Self-Adjusting room, 13.19 for Direct Manipulation,  10.86 for Human-Like Intelligence and 14.93 for Emergent Behaviour. There was a statistically significant response to the statement S17 (“The experience made me feel nervous”) among the tested groups,  χ2(2) = 12.001, p = 0.007, with a mean rank of  17.25 for Self-Adjusting room, 12.56 for Direct Manipulation,  23.50 for Human-Like Intelligence and 8.86 for Emergent Behaviour. There was a statistically significant response to the statement S18 (“The experience made me feel annoyed”) among the tested groups, χ2(2) = 8.986, p = 0.029, with a mean rank of  18.75 for Self-Adjusting room, 13.13 for Direct Manipulation,  20.71 for Human-Like Intelligence and 9.29 for Emergent Behaviour. It must be noted that, as could have been expected, the interaction mode in which participants had to speak to the room is the one that made participants feel more nervous and annoyed. Yet, this same Human-Like Intelligence interaction mode is the one where participants reported least disappointment with the experience. It can also be added that, given a less conservative p value than the one adopted in this analysis, response to the statement S1 (“I felt that I could influence the Interactive Room with my presence or my actions”) among the tested groups could also be included in the significant results. With χ2(2) = 7.585, p = 0.055, a mean rank of  10.31 for Self-Adjusting room, 20.25 for Direct Manipulation,  14.00 for Human-Like Intelligence and 17.50 for Emergent Behaviour; it is possible that a larger sample size would find statistically significant differences between the groups regarding this statement. 191  The second round of  analyses created a new independent variable by combining the interaction modes into whether or not the interaction mode allows participants to directly define the outcome of  the interactive room. For most of  the survey’s items, creating these two groups caused the difference between groups to reduce rather than increase, with two notable exceptions: competence and empowerment. There was a statistically significant response to the statement S15 (“The experience made me feel competent”) among the two groups, χ2(2) = 5.084, p = 0.024, with a mean rank of  12.07 for the indirect group, and a mean rank of  18.93 for the direct group. Figure 80 illustrates the difference per group. Statement S16 (“The experience made me feel powerful”) also increased effect size and significance considerably after the grouping, however with p=0.12 it remained not statistically significant.  Figure 80 - Per group comparative frequency distribution of  levels of  agreement (in Likert scale) to statement 15 of  the user experience survey  Additionally, after the grouping, the statistically significant difference between groups regarding S11 (“I expected more from the experience”) remained,  χ2(2) = 4.996, p = 0.025, with a mean rank of  18.90 for the indirect group, and a mean rank of  12.10 for the direct group. However, the grouping annulated the significance previously found concerning other statements. Finally, one more statistically significant item emerged after grouping. With p = 0.049, participants’ response to the statement S20 (“I was completely focused on my personal activity inside the room, not paying much attention to the environment or the room”) differed between the two groups, χ2(2) = 3.867, with a mean rank of  18.50 for the indirect group, and a mean rank of  12.50 for the direct group. This evidence suggests that whether or not the interaction mode allows participants to directly define 192  the outcome of  the interactive room can have an influence on whether or not inhabitants feel competent and, potentially, powerful. More research is needed to generate stronger evidence for or against this claim. Either way, it is interesting to note that a same phenomenon (i.e. effect size being larger when considering direct vs. indirect action) is not observed on participants’ perception of  control, autonomy, attachment, authorship and ownership. The revised literature have created the expectation that these different items could have an influence on each other. In order to further investigate the interdependence between the items of  the survey, an ordinal regression test was conducted. More specifically, it was used a cumulative odds ordinal logistic regression with proportional odds, and the independent variables (likert-scale items) were treated as interval variables.  The only significant association found was the one between competence and empowerment. An increase in accordance to feeling competent was associated with an increase in the odds of  feeling powerful, with an odds ratio of  8.413 (95% CI, 1.940 to 36.474), Wald χ2(1) = 8.098, p = 0.004. Again, no such association was found between participants’ perception of  control, autonomy, attachment, authorship and ownership. As already stated, the main purpose of  this study was to test and demonstrate its application in the context of  IA research, learning from the process. The next chapter will discuss the lessons learned to further detail, summarizing and commenting on the contributions of  this work. It will also condensate a set of  recommendations for future research.        193  11.1 Main contributions This thesis took an important first step in assembling, testing and demonstrating an inhabitant-centered approach for research and design in Interactive Architecture (IA). This is a much-needed contribution, as it seeks to address a critical gap in the field. As already discussed, a few authors highlight the need for user-centered methodologies in IA (e.g. Achten and Kopřiva, 2010), yet, to the best of  my knowledge, there are no reported applications of  user-centered and evidence-based techniques to research and design in the field (Costa Maia and Meyboom, 2015). Established user-centered design techniques needed to be studied in the context of  IA for a number of  reasons. For one, each available technique is usually only applicable to a narrow range of  situations and must be employed accordingly (Vredenburg 2001). IA also presents its own challenges regarding inhabitant interaction and experience that were yet to be explored in a functional IA setup. Moreover, even more importantly, the particular development state that the field of  IA finds itself  in must be taken into account, for it determinates which are the most important questions that presently ask for answers. This thesis studied how existing methods can be employed within the frameworks of  IA, considering the specific challenges and purposes of  architecture, and thus defining an appropriate approach for the field. Given its early stage of  realization, IA is surrounded by untested claims about its social relevance. On the other hand, it finds little to no demand for its incorporation into the built environment in current day scenario. Among other difficulties, IA is expensive to design, build and maintain. Thus, one of  the most urgent questions that need to be answered is whether IA can in fact deliver what it claims to, assuming these claims meet real world demands in architecture and may justify the extra investment that IA represents. This thesis discussed how interaction could potentially be an instrument to bring about inhabitant agency to architecture. This is one of  the earliest rationales for the social relevance of  IA. It argues that IA, through interactive feedback loops, could give inhabitants the chance to participate in the formation of  the architectural spaces they occupy. This ability includes IA in the broader discussion of  participatory design, inheriting its pressing real-world demand. IA allegedly defines a continuous participatory process, where changes can happen in 194  real time and users – not only owners, designers and other stakeholders - are the ones defining the final spatial outcome of  the forms they inhabit.  To validate these types of  claims, we needed first to examine processes and methodologies for testing the interaction aspect of  IA concepts. As already stated, it is, after all, the interaction component that qualifies IA differently than other, better-known instances of  architecture. In IA, it is a common practice to develop prototypes of  components and architectural forms. However, methods to prototype the interaction in IA have not yet been proposed and demonstrated. This work described how this could be achieved, serving as a reference for other works coming after it. There are well-studied methodologies available in the field of  interaction design that can enable researchers and designers to assess whether a system’s interaction is working and whether it is adding value to the user experience. This thesis showed how IA can take advantage of  this extensive tradition. The next section of  this chapter summarizes some of  the most important lessons learned in the process. This thesis also explored the necessary theories, from psychology and social sciences, needed to support the specific enquiries on human agency the proposed approach was expected to support. Evaluation and assessment methodologies in general are known to have a particular relationship to theory that must be emphasized. They make use of  well-established research theory to define the goals and standards to be employed for measurement (Deming and Swaffield, 2011). Thus, the first step of  this thesis was to identify an evaluation question of  interest to guide the assessment of  IA instances and interaction models. The evaluation question was stated as follows: “Can interactive architecture promote inhabitant agency?” The next step was to review accepted theories in human agency and derive a measuring instrument for that concept in the context of  architecture. Based on the work of  Alkire (2005) and others, this thesis described three different concepts that can be used as an indicator of  human agency. These concepts are: empowerment, autonomy and capability. Autonomy and capability are part of  two well-established theories, namely self-determination and self-efficacy theories, respectively. Through the last decade, these theories have generated a number of  validated survey items geared towards a number of  situations, which can be reliably used as measuring instruments for each concept.  195  An extensive literature search revealed, however, that there is no published material or readily available tools addressing human agency, empowerment, autonomy or capability in architecture. Following express guides for constructing scales in self-efficacy theory (Bandura 2006), referencing the base theories, and using existing scales for non-architectural situations as examples, this thesis constructed a list of  items that can be used in the context of  architecture. Due to time constraints, the scales proposed could not be validated during the course of  the present research. This is not critical in this thesis, because its focus is on the demonstration of  the process rather than on the robustness and validity of  the final user data analysis.  In a next stage of  this study, in order to achieve valid study results, it will be necessary to test and ensure the validity and reliability of  the scales used. Particularly, following research can develop the measuring instruments presented in this thesis and provide validated scales for the concepts of  empowerment, autonomy and capability with regard to the built environment. Such scales can be invaluable to user-centered approaches to architecture, especially around participatory design. The next step in the research was to create a “microcosm” that could be used to test ideas out and to evaluate specific experiences of  interest, such as that of  human agency. This is the point that well-tested methods in user-centered design were employed to assist in the exploration of  IA ideas and in the construction of  an IA apparatus design. This thesis presented the detailed development of  an interactive space-plan concept using mixed- reality. The concept was explored using a user-centered technique for assessing user experience in early design stages. Its process was described in this thesis, including necessary adaptations for the context of  IA and suggestions on how to take the most advantages of  the strengths of  the method. These are reviewed to further detail in the next section. Finally, this thesis described the process of  prototyping an apparatus that could be used to test the interaction component of  IA, especially with an interest in assessing whether IA could promote inhabitant agency. Again, no previous work in the field has attempted similar endeavours. The need for prototyping the interaction in the apparatus made evident the necessity of  having a well-defined understanding of  how this interaction can happen. To date, no interactive space-plans, built 196  or prototyped, exist that could serve as reference. An operational appreciation of  what Interactive Architecture is, considering behaviour and interaction as main determinants in this definition, had to be distilled from speculative descriptions in the literature.  Based on these descriptions, I developed interaction models that could be implemented in an interactive space-plan setting. The development of  these interaction models is another important contribution of  the present work. Not because they represent desirable forms of  interaction, but because they put to test ideas that authors in IA have been reproducing without systematically acknowledging other possibilities or the specific implications of  the type of  IA behaviour they (implicitly or explicitly) present. Thus, the interaction models suggested allow us to start to think critically about how IA is usually depicted in the literature, and provides a basis for the exploration of  more thoughtful forms of  interaction. In conclusion, the goal of  this thesis was to test and demonstrate a user centered approach for evaluating interaction in IA design concepts, especially with regard to the possibility of  fulfilling one of  IA’s many untested claims. This goal was accomplished, making explicit the problems and opportunities in the process.    11.2 Lessons learned  The main part of  this thesis is the one that describes the use of  user-centered design and research methods to the problem of  Interactive Architecture (IA). It involved trying these methods, overcoming difficulties and learning from the process. This section summarizes the work, and highlights the most important lessons learned.  Within a range of  alternatives, two interaction design methodologies were selected to explore and assess the concept: an anticipated experience diary study and a user experience study of  an interaction prototype. The anticipated experience diary study is based on a methodology for assessing user experience at early stages of  product development, as proposed by Sproll and colleagues (2010).  It is intended to provide insights on a product concept, especially regarding the identification of  user needs, before the product is fully developed. 197  A literature survey revealed that available methodologies and applications for anticipated user experience studies are still limited, even beyond the realm of  architecture. Thus, one of  the contributions of  this thesis lies on applying this type of  study to a new problem, reporting on the qualities, limitations and necessity for adaptation that arose during the process. The prototype user study, on the other hand, is a very common research design in HCI and interaction design. It was focused on prototyping the interaction rather than an artifact and, by disposing of  a set of  established methods, it could test people’s experience of  different interaction models. The diary study and the prototype user study are intended for different stages in the concept’s development process. The diary study was, thus, the first one to be conducted in this thesis’ process, focusing on the early design concept. One of  the strengths of  the diary study lies in its ability to bring up situations outside the realm of  what was known or expected for a given product concept. Thus, as it was observed during this research, much of  the value of  this kind of  study can be lost when data is aggregated for analysis.  The methodology presented by Sproll et al. (2010) gives great weight to aggregated data analysis (though diagrams, tabulations and quantitative analysis), overseeing a qualitative appreciation of  what has been reported by the study participants. I found this type of  analyses to provide important information as well. However, it must be complemented with qualitative, case-by-case based learning. This is especially true in the context of  the present research, which did not have access to a large and representative sample of  participants. One of  the main outcomes of  the aggregated analyses was an overall information on how the experiences reported by participants diverged from the core concept32 (i.e., the concept as is, with no alterations). Reports diverged further when the architectural program was a private program, usually occupied by only one person at a time (e.g. bathroom and kitchen). Meanwhile, reports diverged considerably less in shared spaces. This means that, in the real world, the core concept could be useful in common areas, but not as useful in private spaces. The core concept, which affords the re-definition of  space-plan in terms of  spatiality, is mostly                                                      32 The core concept described interactive internal partitions in a space plan. Participants were asked to imagine solid walls ceased to exist, being replaced by virtual walls that could be transformed indefinitely, as need arises. The core concept also allowed control of  lighting, color and temperature inside the interactive space plan. 198  reported in architectural programs where people need to negotiate space with each other (e.g. open offices, pubs, libraries). A review of  individual reports complemented that information, indicating that the core concept was often used as a form of  demarking territorialities or of  communicating something to peers. In both cases, a highly social endeavour. A review of  individual reports also indicated that in non-social situations, space in terms of  territory is not as relevant. Instead, needs turn more pragmatic, as in assisting people in conducting specific tasks.  It is reasonable to say that the political aspect of  architecture, the one that has been the focus of  this thesis, becomes evident primarily when social dynamics are salient. In other situations, IA appears to approximate much more the role of  a tool, perhaps then sharing more similarities with other types of  interactive systems and devices (e.g. automobile). Another informative outcome of  aggregate data analyses refers to whether participants reported some sort of  automation or system intelligence when writing about their imagined experiences. Only 16 reports out of  66 did. In general, people would imagine to engage with the system when they knew exactly what kind of  change they wanted made in that specific moment in time. They needed the interactive “muscle”, not the interactive “brain”. Beyond what was proposed by Sproll et al. (2010), this thesis also probed the data, in a case-by-case basis, searching for case-specific information. A first iteration tried to identify anomalies. However, the data was very heterogeneous, making it unfeasible to identify outliers. Every diary entry could be an outlier in its own account. A second iteration parsed for not suggested or anticipated situations that, nonetheless, used features bounded by the core concept. This provided interesting insights for more sophisticated versions of  the prototype, which, as built, focused only of  the basic defining features of  the design concept. One of  the downsides of  the diary study, which was questioned by independent reviewers of  this thesis, is the fact that participants are necessarily suggested by the way the concept is presented. If  people had access to the system itself, this would allow them to develop a mental model of  it through experience. Otherwise, participants must form a mental model based on the descriptions and images provided during the study. Although this cannot be avoided, it must be considered when interpreting the results. For instance, in the diary study presented in this thesis, it is possible that the great 199  prevalence of  reports relating to office spaces could have been a consequence of  the fact that the image used to illustrate the concept depicted an office building. The second study presented in this thesis was the prototype user study. This study is more robust, for allowing people the experience of  a prototype in later stages of  development. It is, however, less open ended than the diary study and is not suitable for an early exploratory stage of  a concept. I.e., it would not allow situations to emerge that are not afforded by, first, the core concept and, later, by the implemented system definitions. The prototype user study is intended to explore the evaluation question (defined as that study’s research question). The diary study would not allow for an accurate evaluation of  a specific experience component. In this second study, however, the interactive space-plan interaction models could be prototyped and participants could be subject to the actual experience of  interaction. The prototype user study was informed by the results of  the diary study. Most centrally, it used the information that interactive space-plans are more pertinent to architectural programs that are shared and social. This is even more relevant when considering this thesis’ interest with inhabitant agency and the political nature of  space formation. One of  the main research design decisions faced in this study related to either conducting a highly structured within subjects study or a non-structured between subjects study. A consideration of  the two designs is presented in section 10.4. Conducting the prototype user study with a non-structured between subjects design revealed two major problems. The first one was the fact that I could not get a very large number of  participants in the time I had available. The second one regarded the fact that, despite the intention to provide a natural use environment, the main purpose of  most participants was still to be a research participant rather than to occupy the space provided. Thus, the goal of  studying natural situations of  use could not be achieved. Instead, the study could only probe people’s initial experiences with the concept of  IA. Solutions for these problems, however, are very possible. In the next stages of  this research, it is advised that a structured within subjects is conducted prior to the between subjects one. That research design would allow researchers to acquire more valuable qualitative data in order to further our understanding of  the research problem. Information regarding the subjective comparison of  the different models of  interaction would simply not be accessible in 200  the alternative research design. In this case, quantitative data do not represent a main part of  results; instead, it should focus on qualitative insight. However, it is my conviction that after validated measurement instruments for human agency in architecture are ready, and after more qualitative insights on the problem are available, a better version of  the between subjects design would be the one more suitable for providing empirical evidence against the claim that IA can promote human agency. This new version of  the between subjects design must learn from the problems found in the study presented in this thesis. The ideal setup for the non-structured between subjects study must be located in laces with known demands for the kind of  programs supported. For instance, at UBC campus, the prototype could have been installed in one of  the main libraries, adjacent to study and lounge areas. These areas have very high demand and often cannot absorb all of  it, creating, thus, immediate demand for the new space. The ideal setup for the non-structured between subjects study also must be a longitudinal one. It must allow participants a reasonable time of  getting familiar with the space and its behaviour. IA is still a very new concept for lay users, and the feeling of  novelty is overwhelming in the experience. This feeling must be overcome before significant results are generated. The ideal setup will be able to use the already demonstrated techniques of  interaction prototyping, low fidelity representation and wizard of  oz. These techniques, common in HCI and interaction design fields, could be successfully employed to the study of  IA as reported in this thesis. The results of  the prototype user study presented show a template for how to analyse the type of  data acquired. It can serve as a reference for the next iteration of  the study. The data itself, given the problems already described, could not conclusively indicate whether IA could promote inhabitant agency. However, some of  its outcomes seem to point towards interesting areas to be explored. For instance, the importance of  the social role of  IA when it is conceived as an intelligent space that communicates with inhabitants via natural language. The results suggested the possibility that people are more nervous when they need to communicate with the space in this manner. A full range of  explorations is possible around the topic. Another example is the performance of  the emergent behaviour model in several of  the measured indicators. It raised the question of  whether it is possible that, because of  its entertaining quality, it had a positive effect on conceptually different components of  interaction. This resonates with contemporary debates in interaction design 201  and brings up another area of  exploration for IA. Some insights also resulted from observation during the prototype user study. They are:  The dynamics of  use and interaction diverged when participants used the space 1) alone, 2) with friends, 3) or at the same time as other participants with whom they were not familiar. The concepts of  collective agency versus individual agency, which were not explored in this thesis, presented itself  as a relevant way forward.   Some comments from participants related to the antithesis of  “being taken care of ” versus “being in control”. This antithesis was an important stating point of  the discussion presented in this thesis, however it did not take an explicit part in its final format. This is another topic that could be revisited in future debates.  As already stated, the aspect of  novelty played a huge role during the study. People spent most of  their time in the space playing with the interactive space plan features for its own sake. This is an important dynamics as well, but it is just pertinent to an initial stage of  a concept’s life. It is necessary to understand the role of  these spaces over time.  Together, the studies presented are examples of  kinds of  experiments that can be performed in IA, which have been therein tested and demonstrated. In this thesis, however, they illustrate pilot studies, setting up the basis for this kind of  (currently deficient) exploration in the field of  IA.   11.3 Future research The next step in this research will be to refine the research design, as prescribed in previous sections, and run a methodologically robust study to generate valid data and attest to the plausibility of  IA’s inhabitant agency claim. In an even further step, this research will also revisit the models of  interaction themselves and go beyond what is currently described in the literature. Aspects to consider include the integration of  IA in the lager ecology of  interactive devices, and the possibility to support different forms of  interaction in an integrated model. 202  As discussed before, what might be considered the ideal forms, mediums and channels of  interaction may vary according to personal and contextual circumstances. With an interest in inhabitant agency, it can be argued that IA should support different types of  interaction, and even different levels of  complexity within each type.  Following the trajectory, and informed by what might be accomplished at each stage of  this research, in future it might be possible to design a specific instance of  IA that optimizes inhabitant agency, and which can be recommended to full development and construction.                203   Aarts, E., & Encarnaçao, J. (2006). True Visions: The Emergence of  Ambient Intelligence. Springer. Achten, H. (2013). Buildings with an Attitude: Personality traits for the design of  interactive architecture. In eCAADe 2013: Computation and Performance–Proceedings of  the 31st International Conference on Education and research in Computer Aided Architectural Design in Europe, Delft, The Netherlands, September 18-20, 2013. Achten, H., & Kopřiva, M. (2010). A design methodological framework for interactive architecture. In Proceedings of  the 28th eCAADe Conference (pp. 169-177). Adi, M. N., & Roberts, D. (2010). Can you help me concentrate room? In Virtual Reality Conference (VR), 2010 IEEE (pp. 131–134). IEEE. Adi, M. N., & Roberts, D. J. (2011, March). Using VR to assess the impact of  seemingly life like and intelligent architecture on people's ability to follow instructions from a teacher. In VR Innovation (ISVRI), 2011 IEEE International Symposium (pp. 25-31). IEEE. Alkire, S. (2005). Subjective quantitative studies of  human agency. Social Indicators Research, 74(1), 217-260. Akrich, M. (1992). The de-scription of  technical objects. Shaping technology/building society, 205-224. Anderson, C. (2012). Makers: the new industrial revolution. Crown Business, New York Andrejevic, M. (2009). Critical Media Studies 2.0: an interactive upgrade. Interactions: Studies in Communication & Culture, 1(1), 35-51. Arbib, M. A. (2012). Brains, machines and buildings: towards a neuromorphic architecture. Intelligent Buildings International, 4(3), 147–168. Arnstein, S. (1969). A ladder of  citizen participation. J Am Plan Assoc 35:216–224 Bellotti, V., & Edwards, K. (2001). Intelligibility and accountability: human considerations in context-aware systems. Human–Computer Interaction, 16(2-4), 193-212. Bandura, A. (1977). Self-efficacy: toward a unifying theory of  behavioral change. Psychological review, 84(2), 191. Bandura, A. (2006). Guide for constructing self-efficacy scales. Self-efficacy beliefs of  adolescents, 5(307-337). Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual review of  psychology, 52(1), 1-26. 204  Bateson, M. C. (1991). Our own metaphor: A personal account of  a conference on the effects of  conscious purpose on human adaptation. Smithsonian Institution Press. Bentham, J. (1843). Bowring, J. (Ed.). The Works of  Jeremy Bentham. Retrieved July 10, 2015, from http://oll.libertyfund.org/titles/bentham-works-of-jeremy-bentham-11-vols Biloria, N. (2010). Interactive environments: a multi-disciplinary approach towards developing real-time performative spaces. In Entertainment Computing-ICEC 2010 (pp. 254-261). Springer Berlin Heidelberg. Biloria, N. (2012). Interactive morphologies: An investigation into integrated nodal networks and embedded computation processes for developing real-time responsive spatial systems. Frontiers of  Architectural Research, 1(3), 259-271. Blackwell, A. F. (2006). The reification of  metaphor as a design tool. ACM Transactions on Computer-Human Interaction (TOCHI), 13(4), 490-530. Bongers, B.. (2002). Interactivating spaces. In Proceedings of  Symposium on Systems Research in the Arts, Informatics and Cybernetics.  Brand, S. (1995). How buildings learn: What happens after they're built. Penguin. Brodey, W. M. (1967). The design of  intelligent environments: Soft architecture. Broeck, A., Vansteenkiste, M., Witte, H., Soenens, B., & Lens, W. (2010). Capturing autonomy, competence, and relatedness at work: Construction and initial validation of  the Work‐related Basic Need Satisfaction scale. Journal of  Occupational and Organizational Psychology, 83(4), 981-1002. Brown, G., & Gifford, R. (2001). Architects predict lay evaluations of  large contemporary buildings: whose conceptual properties?. Journal of  Environmental Psychology, 21(1), 93-99. Bruns, A. (2008). Blogs, wikipedia, second life, and beyond: from production to produsage. Peter Lang, New York Byrne, B. M. (2013). Structural equation modeling with Mplus: Basic concepts, applications, and programming. Routledge. Calderon, R. (2009). Socio-Political Communication Enabled Spaces. University of  British Columbia (Master’s thesis). Card, S. K., Newell, A., & Moran, T. P. (1983). The psychology of  human-computer interaction. Carver, C. S., & Scheier, M. F. (1981). Attention and self-regulation: A control theory approach to human behavior. New York: Springer. 205  Cetkovic, A. (2012). Unconscious Perception in a Responsive Architectural Environment. Clement, A. (1990, September). Cooperative support for computer work: a social perspective on the empowering of  end users. In Proceedings of  the 1990 ACM conference on Computer-supported cooperative work (pp. 223-236). ACM. Comerio, M. C. (1987). Design and empowerment: 20 years of  community architecture. Built Environment, 15-28. Conrads, U. (1970). Programs and Manifestoes on 20th-century Architecture. MIT Press. Costa Maia, S. C., Lima, M., & Neto, J. D. P. B. (2016). 4 A systemic approach to the concept of  value in lean construction. Value and Waste in Lean Construction, 45. Routledge. Costa Maia, S., & Meyboom, A. (2015). Interrogating Interactive and Responsive Architecture: The Quest of  a Technological Solution Looking for an Architectural Problem. In Computer-Aided Architectural Design Futures. The Next City-New Technologies and the Future of  the Built Environment (pp. 93-112). Springer Berlin Heidelberg. Cuperus, Y. (2001, August). An introduction to open building. In Annual Conference International Group For Lean Construction (Vol. 9). Davidoff, P. (1965). Advocacy and pluralism in planning. Journal of  the american Institute of  Planners, 31(4), 331-338. Davidoff, S., Lee, M. K., Yiu, C., Zimmerman, J., & Dey, A. K. (2006). Principles of  smart home control. In UbiComp 2006: Ubiquitous Computing (pp. 19-34). Springer Berlin Heidelberg. Davis, D., Salim, F. D., & Burry, J.: Designing Responsive Architecture: Mediating Analogue And Digital Modelling In Studio. Proceedings of  the Computer-Aided Architectural Design Research in Asia (CAADRIA) 2011, 155–164. (2011). Dey, A. K., Hamid, R., Beckmann, C., Li, I., & Hsu, D. (2004, April). a CAPpella: programming by demonstration of  context-aware applications. In Proceedings of  the SIGCHI conference on Human factors in computing systems (pp. 33-40). ACM. Deming, M. E., & Swaffield, S. R. (2011). Landscape Architecture Research: Inquiry, Strategy, Design. Hoboken, N.J, John Wiley and Sons. 206  Duane, A., & Finnegan, P. (2003). Managing empowerment and control in an intranet environment. Information Systems Journal, 13(2), 133-158. Dubberly, H., Pangaro, P., & Haque, U. (2009). ON MODELING What is interaction?: are there different types?. Interactions, 16(1), 69-75. Eagleton, T. (1996). Literary theory: An introduction. U of  Minnesota Press. Eastman, C. (1971). Adaptive-Conditional Architecture, in Proceedings of  the Design Research Society’s Conference Manchester 1971, Academy Editions, London, pp. 51-57 Emergence. (n.d.). In Wikipedia. Retrieved May 10, 2016, from https://en.wikipedia.org/wiki/Emergence Feldman, M., Friedler, S. A., Moeller, J., Scheidegger, C., & Venkatasubramanian, S. (2015, August). Certifying and removing disparate impact. In Proceedings of  the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 259-268). ACM. Fels, S. (2004). Designing for intimacy: Creating new interfaces for musical expression. Proceedings of  the IEEE, 92(4), 672-685. Firat, A. F., & Venkatesh, A. (1995). Liberatory postmodernism and the reenchantment of  consumption. Journal of  consumer research, 22(3), 239. Fischer, G., & Giaccardi, E. (2006). Meta-design: A framework for the future of  end-user development. In End user development (pp. 427-457). Springer Netherlands. Fishkin, K. P. (2004). A taxonomy for and analysis of  tangible interfaces. Personal and Ubiquitous Computing, 8(5), 347-358. Fogg, B. J. (2003). Persuasive technology: using computers to change what we think and do. San Francisco: Morgan Kaulfmann Publishers. Fox, M. (2010). Catching up with the Past: A Small Contribution to a Long History of  Interactive Environments. FOOTPRINT, 4(1), 5-18. Fox, M., & Kemp, M. (2009). Interactive architecture (Vol. 1). Princeton: Princeton Architectural Press. Franke, N., Schreier, M., & Kaiser, U. (2010). The “I designed it myself ” effect in mass customization. Management Science, 56(1), 125-140. Freire, P. (1970). Pedagogy of  the oppressed (MB Ramos, Trans.). New York: Continuum, 2007. 207  Friedman, Y. (1971). Pour une architecture scientifique. Belfond, Paris Friedman, Y. (1975). Computer Aided Participatory Design. In: Negroponte, N. (1975) Soft architecture machines. Cambridge, MA: MIT press Frohlich, D. M. (1992, January). The design space of  interfaces. In Multimedia (pp. 53-69). Springer Berlin Heidelberg. Füller, J., MüHlbacher, H., Matzler, K., & Jawecki, G. (2009). Consumer empowerment through internet-based co-creation. Journal of  Management Information Systems, 26(3), 71-102. Gagné, M., & Deci, E. L. (2005). Self‐ determination theory and work motivation. Journal of  Organizational behavior, 26(4), 331-362. Gajos, K., Fox, H., & Shrobe, H. (2002). End user empowerment in human centered pervasive computing. In Proceedings of  Pervasive 2002 (pp. 1-7). Giaccardi, E. (2005). Metadesign as an emergent design culture. Leonardo, 38(4), 342-349. Gill, R. (2007). Critical respect: The difficulties and dilemmas of  agency and ‘choice’for feminism. European Journal of  Women’s Studies, 14(1), 69-80. Goyal, U. B. S. (2008). Principles of  control systems. Technical Publications. Goulthorpe, M., Burry, M., & Dunlop, G. (2001). Aegis Hyposurface©: The Bordering of  University and Practice. Granath, J. Å., Lindahl, G. A., & Rehal, S. (1996). From Empowerment to Enablement. An evolution of  new dimensions in participatory design. Logistik und Arbeit, 8(2). Greenberg, S. (2001). Context as a dynamic construct. Human-Computer Interaction, 16(2), 257-268. Greguras, G. J., & Diefendorff, J. M. (2009). Different fits satisfy different needs: linking person-environment fit to employee commitment and performance using self-determination theory. Journal of  Applied Psychology, 94(2), 465. Habraken, N. J. (1961). Supports: an alternative to mass housing. London: Architectural Press(1972), 97 PP.(General). Habraken, N. J., & Teicher, J. (1998). The structure of  the ordinary: form and control in the built environment. MIT press. 208  Haque, U. (2007). The architectural relevance of  Gordon Pask. Architectural Design, 77(4), 54-61. Henderson, A., & Kyng, M. (1992). There’s no place like home: Continuing design in use. In J. Greenbaum & M. Kyng (Eds.), Design at work: Cooperative design of  computer systems (pp. 219–240). Hillsdale, NJ: Erlbaum. Ihde. D. (1979). Technics undpruxis. Dordrecht, The Netherlands: D. Reidel. Ishii, H., & Ullmer, B. (1997, March). Tangible bits: towards seamless interfaces between people, bits and atoms. In Proceedings of  the ACM SIGCHI Conference on Human factors in computing systems (pp. 234-241). ACM. Jaskiewicz, T. (2008). DYNAMIC DESIGN MATTER [S]. In Proceedings of  the First international conference on critical digital: What Matters(s)? Cambridge (USA): Harvard University Graduate School of  Design. Jaskiewicz, T. (2013). Towards a methodology for complex adaptive interactive architecture. TU Delft, Delft University of  Technology (PhD thesis). Jeng, T. (2012). Interactive Architecture: Spaces that Sense, Think. Computational Design Methods and Technologies: Applications in CAD, CAM and CAE Education, 257. Jung, Y. (2011). Understanding the role of  sense of  presence and perceived autonomy in users' continued use of  social virtual worlds. Journal of  Computer‐Mediated Communication, 16(4), 492-510. Karlin, B., Ford, R., & Squiers, C. (2014). Energy feedback technology: a review and taxonomy of  products and platforms. Energy Efficiency, 7(3), 377-399. Khoo, C., Salim, F., & Burry, J. (2011). Designing architectural morphing skins with elastic modular systems. International Journal of  Architectural Computing, 9(4), 397-420. Kilian, A. (2006) Design exploration through bidirectional modeling of  constraints, PhD thesis,  Massachusetts Institute of  Technology, Boston, MA. Klimmt, C., Roth, C., Vermeulen, I., Vorderer, P (2012). The UX-tool: Measurement device and documentation for empirical assessment of  the user experience of  Interactive Storytelling. Project Number FP7-ICT-231824. Iris. Kline, R. B. (2005). Principles and practices of  structural equation modeling. Second Edition. New York, London, The Guilford Press. 209  Kluger, A. N., & DeNisi, A. (1996). The effects of  feedback interventions on performance: a historical review, a metaanalysis, and a preliminary feedback intervention theory. Psychological Bulletin, 119(2), 254–284. Kroner, W. M. (1997). An intelligent and responsive architecture. Automation in Construction, 6(5), 381–393. Lally, S.  (2014). Untitled One [Online image]. Retrieved April 10, 2016 from http://www.weathers.cc/ Lawson, B. (2005) How designers think. London, Architectural Press, 4th edition. Latham, G. P., & Locke, E. A. (1991). Self-regulation through goal setting. Organizational Behavior and Human Decision Process, 50, 212–247. Latour, B. (2005). Reassembling the Social – An Introduction to Actor-Network-Theory. Oxford University Press. Lee, J. D. (2012). Adaptable, kinetic, responsive, and transformable architecture: an alternative approach to sustainable design. Lee, S. Y., & Brand, J. L. (2005). Effects of  control over office workspace on perceptions of  the work environment and work outcomes. Journal of  Environmental Psychology, 25(3), 323-333. Lo, T. T., Schnabel, M. A., & Gao, Y. (2015). ModRule: A User-Centric Mass Housing Design Platform. In Computer-Aided Architectural Design Futures. The Next City-New Technologies and the Future of  the Built Environment (pp. 236-254). Springer Berlin Heidelberg. Lynn, G. & Oosterhuis, K. (2014). NSA Muscle. Canadian Centre for Architecture. Mackay, H., Carne, C., & Beynon-Davies P. (2000) Reconfiguring the user: using rapid application development. Soc Stud Sci 30:737–757 Malard, M. L., Conti, A., Souza, R. D., & Campomori, M. J. L. (2002). Avaliação pós-ocupação, participação de usuários e melhoria de qualidade de projetos habitacionais: uma abordagem fenomenológica. Coletânea Habitare. ANTAC, 1, 243-267. Mann, S. (1998, May). Wearable computing as means for personal empowerment. In Proc. 3rd Int. Conf. on Wearable Computing (ICWC) (pp. 51-59). Marschall, S. (1998). Architecture as empowerment: The participatory approach in contemporary architecture in South Africa. Transformation, (35). Mcluhan, M., & Fiore, Q. (1967). The Medium is the Massage: An Inventory of  Effects. New York: Penguin Books. 210  McMeel, D., & Amor, R. (2013). Fabricate It, Paint It–And Don’t Wait up: Separating Fact from Fiction in Digitally Sponsored Fabrication. In Global Design and Local Materialization (pp. 149-158). Springer Berlin Heidelberg. Meagher, M. (2010). Dynamic Ornament: The Design of  Responsive Architectural Environments (Doctoral dissertation, École Polytechnique Fédérale De Lausanne). Metcalfe, J., Eich, T. S., & Castel, A. D. (2010). Metacognition of  agency across the lifespan. Cognition, 116(2), 267-282. Minsky, M. (1988). Society of  mind. Simon and Schuster. Minsky, M., & Riecken, D. (1994). A conversation with Marvin Minsky about agents. Communications of  the ACM, 37(7), 22-29. Nahmias, E. (2005). Agency, authorship, and illusion. Consciousness and Cognition, 14(4), 771-785. Narahara, T. (2010). Designing for Constant Change: An Adaptable Growth Model for Architecture. International Journal of  Architectural Computing, 8(1), 29-40. Nee, C., White, M., Woolford, K., Pascu, T., Barker, L., & Wainwright, L. (2015). New methods for examining expertise in burglars in natural and simulated environments: preliminary findings. Psychology, Crime & Law, 21(5), 507-513. Negroponte, N. (1970). The architecture machine: towards a more human environment (pp. 287-326). Cambridge, MA: MIT press. Negroponte, N. (1975) Soft architecture machines. Cambridge, MA: MIT press. Ng, O.  (2010). Wallbot [Online image]. Retrieved March 2, 2016 from http://www.ottocad.net/blog/?p=243 Nieuwenhuys, C. (1972). New Babylon. Constant: New Babylon, 154. Norman, D. A. (1986). Cognitive engineering. User centered system design: New perspectives on human-computer interaction, 3161. Norman, D. (1988). The Design of  Everyday Things (Originally published: The psychology of  everyday things). Basic books. Novak, M. (2015). Transmitting architecture: the transphysical city. CTheory, 11-29. 211  Oh, S., Patrick, V., & Llach, D. C. (2014, April). Typologies of  architectural interaction: a social dimension. In Proceedings of  the Symposium on Simulation for Architecture & Urban Design (p. 7). Society for Computer Simulation International. Orlikowski, W.J. (1991) Integrated information environment or matrix of  control? The contradictory implications of  information technology. Accounting, Management and Information Technology, 1, 9–42. Pan, C.-A., & Jeng, T. (2008). Exploring Sensing-based Kinetic Design for Responsive Architecture. In Conference of  Computer-Aided Architectural Design Research in Asia (CAADRIA). Pan, C.-A., & Jeng, T.: A robotic and kinetic design for interactive architecture. In Proceedings of  SICE Annual Conference 2010 (pp. 1792–1796). IEEE. (2010). Park, J. W. (2013). Interactive Kinetic Media Facades: A Pedagogical Design System to Support an Integrated Virtual-Physical Prototyping Environment in the Design Process of  Media Facades. Journal of  Asian Architecture and Building Engineering, 12(2), 237-244. Parlac, V. (2013). Surface Change: Information, Matter and Environment. In Conference on Computer-Aided Architectural Design Research in Asia (CAADRIA 2013) (Vol. 935, p. 944). Parvin, A. (2013). Architecture for the people by the people [Video file]. Retrieved January 3, 2015, from http://www.ted.com/talks/alastair_parvin_architecture_for_the_people_by_the_people Pask, G.: Architectural Relevance of  Cybernetics, in Architectural Design, September, pp. 494-496 (1969) Price, C. (1961). Fun Palace for Joan Littlewood, project Stratford East, London, England Perspective. Drawing. Retrieved December 20, 2014, from http://library.artstor.org. Rabeneck, A. (1969). Cybermation: a useful dream. Architectural Design, 497-500. Rafaeli, S. (1988). Interactivity: From new media to communication. In R.P. Hawkins, J.M. Wieman, & S. Pingree (Eds.), Advancing communication science: merging mass and interpersonal processes (p110-134). Newbury, CA: Sage.   Rahm, P.  (n.d.). Domestic Astronomy [Online image]. Retrieved January 10, 2016 from http://www.philipperahm.com/data/projects/domesticastronomy/index.html Rizopoulos, C., & Charitos, D. (2011, July). Implications of  Theories of  Communication and Spatial Behavior for the Design of  Interactive Environments. In 2011 Seventh International Conference on Intelligent Environments (pp. 92-99). IEEE. 212  Rosenblueth, A., Wiener, N., & Bigelow, J. (1943). Behavior, purpose and teleology. Philosophy of  science, 10(1), 18-24. Roto, V., Rantavuo, H., and Väänänen-Vainio-Mattila, K. (2009). Evaluating user experience of  early product concepts. In Proceedings of  the International Conference on Designing Pleasurable Products and Interfaces - DPPI'09. Compiegne, France: Compiegne University of  Technology. Salim, F., Burry, J., Peers, J., & Underwood, J. (2012). Augmented spatiality. International Journal of  Architectural Computing, 10(2), 275-300. Sanders, E. B. N., & Stappers, P. J. (2008). Co-creation and the new landscapes of  design. Co-design, 4(1), 5-18. Santo, Y. (2012, November). An interactive and adaptive building layer: strategies for allowing people to become advanced building-users. In Proceedings of  the 24th Australian Computer-Human Interaction Conference (pp. 521-529). ACM. Sartre, J. P. (1950). "What is literature?" and other essays. Methuen & Co. Ltd, London. Scannell, L., & Gifford, R. (2010). Defining place attachment: A tripartite organizing framework. Journal of  Environmental Psychology, 30(1), 1-10. Scholtz, J., & Consolvo, S. (2004). Toward a framework for evaluating ubiquitous computing applications. Pervasive Computing, IEEE, 3(2), 82-88. Schomaker, L. (1995). A taxonomy of  multimodal interaction in the human information processing system. A report of  the ESPRIT Project 8579 MIAMI. Segal, R. & Weizman, E (Eds.). (2003). A Civilian Occupation: The Politics of  Israeli Architecture, New York, Verso. Sen, A. (1985). Well-being, agency and freedom: the Dewey lectures 1984. The journal of  philosophy, 169-221. Shafti, L. S., Haya, P. A., García-Herranz, M., & Pérez, E. (2013). Inferring ECA-based rules for ambient intelligence using evolutionary feature extraction. Journal of  Ambient Intelligence and Smart Environments, 5(6), 563-587. Simons, R. (1995) Levers of  Control. Harvard Business School Press, Boston MA. Sproll, S., Peissner, M., and Sturm, C. (2010). From product concept to user experience: Exploring UX potentials at early product stages. In Proceedings of  the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries - NordiCHI'10 (pp. 473-482). New York: ACM Press. 213  Solomon, G. (1992). The computer as electronic doorway: Technology and the promise of  empowerment. Phi Delta Kappan, 74(4), 327. Stamps III, A. E. (2010). Use of  static and dynamic media to simulate environments: a meta-analysis 1. Perceptual and motor skills, 111(2), 355-364. Standage, M., Duda, J. L., & Ntoumanis, N. (2005). A test of  self‐determination theory in school physical education. British Journal of  Educational Psychology, 75(3), 411-433. Sterk, T. D. E. (2005). Building upon Negroponte: a hybridized model of  control suitable for responsive architecture. Automation in construction, 14(2), 225-232. Sterk, T. D. E. (2006a). Responsive Architecture: User-Centered Interactions within the Hybridized Model of  Control. In Proceedings Of  The Game Set And Match II, On Computer Games, Advanced Geometries, and Digital Technologies, Netherlands: Episode Publishers (pp. 494–501). Sterk, T. D. E. (2006b). Shape Control in Responsive Architectural Structures–Current Reasons & Challenges. In Proceedings of  the 4th World Conference on Structural Control and Monitoring, San Diego, CA, USA. Sullivan, J., Sullivan, J. W., & Tyler, S. W. (1994). Intelligent user interfaces. Takeuchi, Y. (n.d.). Weightless Walls [Online image]. Retrieved May 5, 2016 from http://tinylab.me/otherprojects/index.html Takeuchi, Y. (2012, May). Synthetic space: inhabiting binaries. In CHI'12 Extended Abstracts on Human Factors in Computing Systems (pp. 251-260). ACM. Tetteroo, D., & Markopoulos, P. (2015). A Review of  Research Methods in End User Development. In End-User Development (pp. 58-75). Springer International Publishing. Thue, D., Bulitko, V., Spetch, M., & Romanuik, T. (2011, September). A Computational Model of  Perceived Agency in Video Games. In AIIDE. Toffler, A. (1989). The third wave. William Morrow & Company, New York. Vallgårda, A. (2014). Giving form to computational things: developing a practice of  interaction design. Personal and Ubiquitous Computing, 18(3), 577-592. van Onck, A. (1965). Metadesign. Edilizia moderna, 85. 214  Vardouli, T. (2015). Who Designs?. In Empowering Users through Design (pp. 13-41). Springer International Publishing. Vardouli, T., & Buechley, L. (2014). Open source architecture: an exploration of  source code and access in architectural design. Leonardo, 47(1), 51-55. Vassão, C. A. (2008). Arquitetura livre: complexidade, metadesign e ciência nômade (Doctoral dissertation, Universidade de São Paulo). Verbeek, P. P. (2011). Moralizing technology: Understanding and designing the morality of  things. University of  Chicago Press. Vermeeren, A. P. O. S., Law, E., Roto, V., Obrist, M., Hoonhout, J., and Väänänen-Vainio-Mattila, K. (2010). User experience evaluation methods: Current state and development needs. In Proceedings of  the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries - NordiCHI'10 (pp. 521-530). New York: ACM Press. Vermeulen, J., Luyten, K., & Coninx, K. (2013). Intelligibility Required: How to Make Us Look Smart Again. Virilio, P. (1995). The art of  the motor. U of  Minnesota Press. von Hippel, E. & Katz, R. (2002). Shifting innovation to users via toolkits. Social Science Research Network, Rochester von Trier, L. (Director). (2003). Dogville [Motion picture]. Denmark. Vredenburg, K., Isensee, S., Righi, C., & Design, U. C. (2001). An integrated approach. Englewood Cliffs: Prentice Hall. Weller, H. G., & Hartson, H. R. (1993). Metaphors for the nature of  human-computer interaction in an empowering environment: Interaction style influences the manner of  human accomplishment. Computers in human behavior, 8(4), 313-333. Wellesley-Miller, S. (1971). Self-organizing Environments. Design Participation. Wellesley-Miller, S. (1975). Computer Aided Participatory Design. In: Negroponte, N. (1975) Soft architecture machines. Cambridge, MA: MIT press Waugh, D. A., & Taylor, M. M. (1995). The role of  feedback in a layered model of  communication. Nato Asi Series F Computer And Systems Sciences, 142, 215-215. 215  Wiener, N. (1961). Cybernetics or Control and Communication in the Animal and the Machine (Vol. 25). MIT press. Wiberg, M. (Ed.). (2010). Interactive Textures for Architecture and Landscaping: Digital Elements and Technologies. IGI Global. Winner, L. (1986). The whale and the reactor: A search for limits in an age of  high technology. University of  Chicago Press. Wlaszyn, J. (2011). Re-thinking metaphor, experience and aesthetic awareness. Kybernetes, 40(7/8), 1196-1206. Zhang, T., & Brügge, B. (2004, August). Empowering the user to build smart home applications. In ICOST 2004 International Conference on Smart Home and Health Telematics.      216  Appendix A: Diary entry protocol  217  Appendix B: Final diary survey protocol  Introduction The survey will allow us to know more about your experience with the Anticipated User Experience Diaries study and about specific diary entries you may have made. Sections A: Understanding of  the concept 1. Was the concept of  this new kind of  technology easy to grasp? 2. Can you describe the concept in a few words, as you understand it?  B: The diary keeping 3. Did ideas occur naturally to you during your routine or did you have to put in some effort in order to produce diary entries?  C: Assessment of  usefulness 4. In general, would you say that you would like the experiences imagined to be real? Would you want to be able to change your environment in real time for it to adapt to specific situations? 5. Does this possibility of  easily changing your built environment raise any concerns in you? 6. Which of  the features of  the built environment you thought to be the most important ones for you to change at will? E.g. lighting, visual barriers, textures, furniture, walls, etc. 7. If  you could change all the features of  the built environment at will, but only inside a single room, which room would this be? 8. Which of  the diary entries you made is your preferred one? Why? 9. Would you install a system in your home and/or in your workspace that allows you to change differ-ent features of  the space in real time, but that is heavily dependent on electronic systems, infor-mation technologies and electric energy?       218  Appendix C: Initial questionnaire for the Interactive Room study  Please answer the questions below about yourself.  Question 1 Please select your gender: ( ) male, ( ) female, ( ) other  Question 2 Please write your age in years:  Question 3 Please use the scale to indicate your level of  agreement to the following statement: “It is important to me that I have a saying on how my environment should be like”. [Likert scale]  Question 4 Please use the scale to indicate your level of  agreement to the following statement: “I prefer choosing and customizing my own room than having a computer objectively selecting the best setting for me”. [Likert scale]  Question 5 Please use the scale to indicate your level of  agreement to the following statement: “I prefer choosing and customizing my own room than having another person (e.g. an architect) selecting the best setting for me”. [Likert scale]  Question 6 Please use the scale to indicate your level of  agreement to the following statement: “I prefer doing things on my on than relying on assistance from others”. [Likert scale]                219  Appendix D: User experience questionnaire for the Interactive Room study  Introductory information Access code:  __ __ __ __ - __       (You received an access code after signing the consent form online)  Estimate of  time spent inside the Interactive Room:               _________ hours and _________minutes. During this time, how often do you think you tried to interact with the room?   _____________ times. What was your main purpose when interacting with the room? _____________________________________________________________________________________  User Experience Questions 1. Please use the scale to indicate your level of agreement to the following statements about your experience with the interactive room. Statements Scale (select only one per statement)  Strongly disagree Disa-gree Neutral Agree Strongly agree “I felt that I could influence the Interactive Room with my presence or my actions”.   “I caused changes to the space in the room be-cause these changes interested me”.   “I feel I have control over my environment in this room”.   “I can have the space personalized in a way that is meaningful to me”.   “It was easy to use and interact with the Inter-active Room”.   “By the time I left the Interactive Room, I be-lieve it reflected who I am to some extent”.   “I feel some level of attachment to this space after using it”.   220  “I am happy to take credit for the current state of the Interactive Room. I helped creating it”.    “I have a feeling that the spaces that came into being because of me inside the Interactive Room are mine. They belong to me”.   “I interacted with the space spontaneously and automatically without having to think”.   “I expected more from the experience”.    “I expected the experience to be more engag-ing”.   “I expected the aesthetic experience to be bet-ter”.   “The experience was enjoyable”.    “The experience made me feel competent”    “The experience made me feel powerful”    “The experience made me feel nervous”    “The experience made me feel annoyed”    “The experience made me feel bored”    “I was completely focused on my personal ac-tivity inside the room, not paying much atten-tion to the environment or the room”.   221  “I felt that inside the Interactive Room the way time passed seemed to be different from nor-mal”.    2. Can you think of  any needs that arose during your use of  the space which were met by the Interactive Room? _____________________________________________________________________________________ _____________________________________________________________________________________ 3. Can you think of  any needs that arose during your use of  the space and that the room failed to support? _____________________________________________________________________________________ _____________________________________________________________________________________  4. Would you recommend a friend to visit the Interactive Room?  Yes        No  5. Is there anything else you would like to comment about your experience? __________________________________________________________________________________________________________________________________________________________________________         222  Appendix E: Observation notes protocol for the Interactive Room study  Observation notes protocol Participant (attribute a pseudo name): Interaction number: Purpose of  interaction: Feature actioned: Length of  interaction:           

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