Education, School of (Okanagan)
DSpace
UBCO
Naghshbandi, Serveh
Doctor of Philosophy - PhD
University of British Columbia
This qualitative study developed a multilayered participatory approach, exploring learning spaces for doctoral education. As an exploratory process, this research supported the development of design methodology and domain theory based on Design-Based Research (DBR). It identified the main conceptualizations of learning space from doctoral students’ points of views and developed a participatory model to make students’ multiple voices heard. Doctoral experience is viewed as being influenced by social practices of the scholarly communities and learning space in this context is a collective resource that can be altered through imagination of its inhabitants. Intersection of Production of Space in Architecture and Situated Learning theory in Education enabled me to build an integrated conceptual framework to explore doctoral students’ perceptions, lived experiences, and imaginations of learning spaces at UBC Okanagan. Three research questions reflected theoretical and practical aims. To answer them, I developed a multi-phased research through three sequential phases: questionnaire, Photovoice, and prototyping, which respectively addressed subjective, objective, and co-constructed aspects of learning spaces. Inductive, deductive, and latent approaches in Thematic Analysis informed the data analysis process. My findings suggest that while doctoral students emphasized individual space as a necessity in any PhD journey, they viewed a learning space beyond its physicality. Participants’ experiences reinforced that learning is embedded in communities of practice in doctoral undertaking. They implied creation of communities can turn any space into a place. Participants imagined spaces that support physicality (individual and shared spaces), liminality (in-between and on the margins), and (re)-configurability. Four themes emerged as design principles: 1) learning space is a layered multi-faceted phenomenon, 2) learning space is an indicator of support, 3) learning space has a potential to improve and sustain well-being, and 4) learning space is a changing entity. I offered contextual recommendations which reflected participants’ thoughts and ideas, while I remain conscious that learning is more than the space in which it occurs, and space is more than the practices it contains.
TOWARDS CO-CREATING A SENSE OF PLACE A Multilayered Participatory Approach, Exploring Learning Spaces for Doctoral Education Based on Design-Based Research by Serveh Naghshbandi M.A., University of British Columbia, 2014 M.A., Tehran University of Art, 2006 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE COLLEGE OF GRADUATE STUDIES (Interdisciplinary Studies) THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan) March 2021 © Serveh Naghshbandi, 2021ii The undersigned certify that they have read, and recommend to the College of Graduate Studies for acceptance, a thesis entitled: TOWARDS CO-CREATING A SENSE OF PLACE A Multilayered Participatory Approach, Exploring Learning Spaces for Doctoral Education Based on Design-Based Research submitted by Serveh Naghshbandi in partial fulfillment of the requirements of the degree of Doctor of Philosophy. Dr. Susan Crichton, Okanagan School of Education, University of British Columbia Supervisor Dr. Karen Ragoonaden, Okanagan School of Education, University of British Columbia Co-supervisor Dr. Lynn Bosetti, Okanagan School of Education, University of British Columbia Supervisory Committee Member Dr. Patricia Lasserre, Irving K. Barber School of Arts & Sciences, University of British Columbia Supervisory Committee Member Dr. Susan Frohlick, Irving K Barber Faculty of Arts and Social Sciences, University of British Columbia Supervisory Committee Member Dr. Martin Blum, Faculty of Creative and Critical Studies, University of British Columbia University Examiner Dr. Barbara Brown, Associate Dean Teaching & Learning, Werklund School of Education, University of Calgary External Examiner iii Abstract This qualitative study developed a multilayered participatory approach, exploring learning spaces for doctoral education. As an exploratory process, this research supported the development of design methodology and domain theory based on Design-Based Research (DBR). It identified the main conceptualizations of learning space from doctoral students’ points of views and developed a participatory model to make students’ multiple voices heard. Doctoral experience is viewed as being influenced by social practices of the scholarly communities and learning space in this context is a collective resource that can be altered through imagination of its inhabitants. Intersection of Production of Space in Architecture and Situated Learning theory in Education enabled me to build an integrated conceptual framework to explore doctoral students’ perceptions, lived experiences, and imaginations of learning spaces at UBC Okanagan. Three research questions reflected theoretical and practical aims. To answer them, I developed a multi-phased research through three sequential phases: questionnaire, Photovoice, and prototyping, which respectively addressed subjective, objective, and co-constructed aspects of learning spaces. Inductive, deductive, and latent approaches in Thematic Analysis informed the data analysis process. My findings suggest that while doctoral students emphasized individual space as a necessity in any PhD journey, they viewed a learning space beyond its physicality. Participants’ experiences reinforced that learning is embedded in communities of practice in doctoral undertaking. They implied creation of communities can turn any space into a place. Participants imagined spaces that support physicality (individual and shared spaces), liminality (in-between and on the margins), and (re)-configurability. Four themes emerged as design principles: 1) learning space is a layered multi-faceted phenomenon, 2) learning space is an indicator of support, 3) learning space has a potential to improve and sustain well-being, and 4) learning space is a changing entity. I offered contextual recommendations which reflected participants’ thoughts and ideas, while I remain conscious that learning is more than the space in which it occurs, and space is more than the practices it contains. iv Lay Summary This study explored doctoral students’ understandings, experiences, and imaginations of learning spaces at UBC Okanagan campus. It viewed space as a “socially constructed” notion and supported more participation in learning space design to make doctoral students’ multiple voices heard. I found that the notion of learning space is a maze of different spaces that is continually unfolding and changing based on different needs. Doctoral students emphasized the effective learning spaces related to well-being, belonging, and engagement that they felt help support them in their studies. I suggest creating flexible and configurable home-like intimate spaces to switch positions from time to time. Also, considering that conducting doctoral thesis in isolation is the dominant problem of doctoral experience, being part of scholarly communities was seen to be helpful. v Preface This dissertation is an original intellectual product by the author, Serveh Naghshbandi. I conceptualized and designed the study, conducted the research, analyzed the data, and wrote this manuscript following the guidance of my supervisors Dr. Susan Crichton and Dr. Karen Ragoonaden as well as my supervisory committee members, Dr. Lynn Bosetti, Dr. Patricia Lasserre, Dr. Robert Belton (retired), and Dr. Susan Frohlick. Ethics approval for this study was received from The University of British Columbia Okanagan Behavioural Research Ethics Board. The number on the certificate was H17-03546 (Appendix A). The approval was renewed on an annual basis. vi Table of Contents Abstract iii Lay Summary iv Preface v Table of Contents vi List of Tables xiv List of Figures xvi List of Abbreviations and Terms xix Acknowledgement xxi Dedication xxii Chapter 1: Introduction 1 1.1 Preamble ................................................................................................................. 1 1.2 Overview of Chapter 1 ............................................................................................ 2 1.3 Overview of the Study ............................................................................................ 2 1.4 Context of the Study................................................................................................ 4 1.5 Research Questions ................................................................................................. 5 1.6 Research Approach ................................................................................................. 6 1.7 Theoretical Framework ........................................................................................... 7 1.8 Purpose of the Study ............................................................................................... 8 1.9 Significance of the Study ........................................................................................ 8 1.10 Organization of the Dissertation ........................................................................... 9 Chapter 2: Conceptual Framework and Review of the Literature 11 2.1 Overview of Chapter 2 .......................................................................................... 11 2.2 Scope of the Review .............................................................................................. 11 2.3 Changing Conceptions of Doctoral Education ...................................................... 11 2.4 Opening up Two Points of View to Explore Learning Spaces ............................. 13 vii 2.4.1 Learning spaces from educational perspective: learning as a dynamic social process ............................................................................................................... 16 2.4.2 Learning spaces from architectural point of view: a dynamic interaction between space and occupants ........................................................................... 18 2.5 Connecting the Dots: Role of Design and Intentional Change to (Re)Imagine Learning Spaces ................................................................................................... 22 2.5.1 Why learning space? ................................................................................... 22 2.5.2 How Design can help re-negotiate learning spaces in ever-changing times? .................................................................................................................... 22 2.5.2.1 Wicked problems in the throes of COVID-19 pandemic .................. 23 2.5.3 Participatory design to view learning spaces as collective resources ......... 24 2.6 Theoretical Framework ......................................................................................... 25 2.6.1 Scope of the framework: creating third space ............................................. 26 2.6.2 Complexity and ambiguity of space: framing learning spaces within Lefebvre’s Production of Space ................................................................. 27 2.6.3 Situatedness and complexity of learning: framing learning spaces within Situated Learning theory ............................................................................ 31 2.6.4 Process to re-creating the learning spaces: [participatory] design .............. 32 2.6.4.1 Making/prototyping to explore the future possibilities. .................... 34 2.6.4.2 Designing a generative toolkit drawing on participatory and human-centered approach to design. ............................................................. 35 Chapter 3: Methodology and Research Design 37 3.1 Overview of Chapter 3 .......................................................................................... 37 3.2 Research Questions and An Overview of the Research ........................................ 38 3.3 Design-Based Research (DBR) Methodology and the Tenets of the Study ......... 42 3.3.1. Having a pragmatic stand ........................................................................... 43 3.3.2. Grounding in theory and real practice ........................................................ 43 3.3.3. Conducting iterative and flexible process .................................................. 43 3.3.4 Using multiple perspectives to ensure integration of data sources ............. 44 3.3.5 Connecting to the context ........................................................................... 44 3.4 Design-Based Research and its Interrelationship to the Research Questions ....... 45 viii 3.5 DBR and Participatory Design to Develop Domain Theories and Design Methodology ........................................................................................................ 47 3.6 Research Design within a DBR Framework ......................................................... 49 3.7 Decision on Data Collection Methods .................................................................. 51 3.8 Constructing an Eclectic Thematic Analysis-Informed Approach for Data Analysis ................................................................................................................ 52 3.8.1 Why not Grounded Theory? ....................................................................... 53 3.8.2 Reflexive Thematic Analysis ...................................................................... 54 3.8.3 Coding the data ........................................................................................... 56 3.9 Iterative Cycles of Reviewing the Related Literature ........................................... 58 3.10 First Phase, Questionnaires ................................................................................. 59 3.10.1 Questionnaires to address subjective aspect of learning spaces ............... 60 3.10.2 Participants in questionnaires .................................................................... 61 3.10.3 Questionnaire design ................................................................................. 61 3.10.4 Questionnaire analysis .............................................................................. 63 3.10.5 Questionnaire issues/limitations ............................................................... 65 3.11 Second Phase, Photovoice ................................................................................... 67 3.11.1 Photovoice plus semi-structured interviews to address objective aspect .. 68 3.11.2 Participants in Photovoice ......................................................................... 69 3.11.3 Photovoice procedure design .................................................................... 69 3.11.3.1 Recruiting a group of Photovoice participants. ............................... 69 3.11.3.2 Introducing Photovoice methodology to participants ..................... 69 3.11.3.3 Obtaining informed consent ............................................................ 70 3.11.3.4 Providing time to participants to take photos ................................. 70 3.11.3.5 Meeting to discuss photographs ...................................................... 71 3.11.3.6 Engaging decision-makers (action). ................................................ 71 3.11.4 Semi-structured interviews ....................................................................... 72 3.11.4.1 Interview protocol. .......................................................................... 72 3.11.5 Photovoice analysis ................................................................................... 73 3.11.6 Photovoice issues ...................................................................................... 77 3.12 Third Phase, Participatory Prototyping ............................................................... 79 ix 3.12.1 Participatory prototyping to address co-constructed aspect of learning spaces ....................................................................................................... 81 3.12.2 Participants in participatory prototyping ................................................... 83 3.12.3 COVID-19 and virtual prototyping studio ................................................ 83 3.12.4 Design and development of virtual co-prototyping studio ........................ 84 3.12.4.1 Form, purpose, and context. ............................................................ 85 3.12.4.2 Virtual studio: method, tools, and techniques. ................................ 85 3.12.5 Participatory prototyping analysis ............................................................. 89 3.12.6 Participatory prototyping issues/limitations .............................................. 91 3.13 Recruitment and Ethics Management ................................................................. 93 3.13.1 Participants recruitment ............................................................................ 94 3.13.2 Security of data during the study .............................................................. 95 3.14 Trustworthiness ................................................................................................... 95 3.15 My Role as a Researcher ..................................................................................... 97 Chapter 4: Analyzing the Data 100 4.1 Overview of Chapter 4 ........................................................................................ 100 4.2. Data from Questionnaires .................................................................................. 101 4.2.1 First section of questionnaire, demographic questions ............................. 101 4.2.2 Data from second section of questionnaire ............................................... 101 4.2.3 What mattered most? ................................................................................ 106 4.2.4 Beyond physicality .................................................................................... 107 4.2.5 General comments on doctoral students’ perceptions of learning spaces . 111 4.2.6 Specific comments on doctoral students’ perceptions of learning spaces 112 4.2.6.1 Discipline-dependent ...................................................................... 112 4.2.6.2 Physical and conceptual entity. ....................................................... 112 4.2.6.3 Individualized space. ....................................................................... 113 4.2.6.4 Digital space. ................................................................................... 113 4.2.6.5 Well-being ....................................................................................... 114 4.2.6.6 Affordances ..................................................................................... 114 4.2.6.7 Potential for choice ......................................................................... 114 4.2.7 Data from third section of questionnaire ................................................... 115 x 4.2.8 What needed most? ................................................................................... 118 4.2.9 Comments on doctoral students’ experiences of learning spaces ............. 122 4.2.9.1 Social space ..................................................................................... 122 4.2.9.2 Individual space .............................................................................. 122 4.2.9.3 Library ............................................................................................. 122 4.2.9.4 Affordances ..................................................................................... 122 4.2.10 Data from fourth section of questionnaire .............................................. 122 4.2.11 Comments on doctoral students’ ideals and imaginations of learning spaces ..................................................................................................... 124 4.2.12 Reviewing/Refining the themes on doctoral students’ perceptions ........ 125 4.3 Data from Photovoice ......................................................................................... 127 4.3.1 An eclectic approach to analyze the data from Photovoice ...................... 129 4.3.1.1 Coding the data ............................................................................... 130 4.3.2 An analysis of each participant’s transcript .............................................. 133 4.3.3 A cross-case analysis comparing all transcripts ........................................ 134 4.3.3.1 Thematizing .................................................................................... 134 4.3.3.2 UBC Okanagan’s spaces ................................................................. 138 4.3.3.3 If you can change one thing ............................................................ 138 4.3.4 Incorporating arts-informed approach to gain a deeper understanding of the transcript data ........................................................................................... 139 4.3.5 General comments on doctoral students’ experiences of learning spaces 144 4.3.6 Specific comments on doctoral students’ experiences of learning spaces 144 4.3.6.1 The need to have one’s own space: an intimate space to feel belonged ......................................................................................................... 144 4.3.6.2 Lack of office spaces ...................................................................... 145 4.3.6.3 A journey together or “squeezing” together? .................................. 146 4.3.6.4 Need for community ....................................................................... 148 4.3.6.5 Need to access to virtual spaces everywhere .................................. 149 4.3.6.6 Tuning marginal spaces to spaces for learning ............................... 151 4.3.6.7 Need for reconfigurable spaces ....................................................... 153 4.4 From Space to Place: Comparing the Questionnaire and Photovoice Data ........ 154 xi 4.4.1 Space: What doctoral students perceived as their learning spaces ........... 157 4.4.1.1 Beyond physicality, social spaces. .................................................. 157 4.4.1.2 Individual spaces ............................................................................. 157 4.4.1.3 Virtual spaces .................................................................................. 157 4.4.2 Place: How doctoral students interacted with their learning spaces ......... 157 4.4.2.1 Need for individual spaces .............................................................. 157 4.4.2.2 Experiencing isolation .................................................................... 157 4.4.3. Imaginations ............................................................................................. 158 4.5 Data from Participatory Prototyping ................................................................... 159 4.5.1 Analyzing the prototypes .......................................................................... 159 4.5.2 General comments on doctoral students’ imaginations of learning spaces .................................................................................................................. 164 4.5.3 Specific comments on doctoral students’ imaginations of learning spaces .................................................................................................................. 164 4.5.3.1 A balance between individual and shared spaces ........................... 164 4.5.3.2 In-between and on-margin of the existing defined spaces .............. 165 4.5.3.3 A balance between fixed and customizable .................................... 166 5.4.3.4 Connecting to the nature, indoor and outdoor: a balance between built and natural environment. ................................................................. 167 4.5.3.5 Comfort: home-like spaces. ............................................................ 168 4.6 Summary of Chapter 4 ........................................................................................ 168 Chapter 5: Discussion of Findings 170 5.1 Overview of the Study ........................................................................................ 170 5.2 Space as Perceived: Subjective Aspect of Learning Spaces (First Question) ..... 172 5.2.1 Beyond physicality: multiplicity of spaces for multiple identities ........... 173 5.2.2 Social space, community as a missing vital layer of space ....................... 173 5.2.3 Individual space, a necessity in any PhD journey ..................................... 174 5.2.4 Virtual space, still an ill-defined space ..................................................... 174 5.3 Space as Conceived: Objective Aspect of Learning Spaces (Second Question) 175 5.3.1 Lack of personalized space ....................................................................... 176 5.3.2 Lack of community and connection with peers ........................................ 178 xii 5.3.3 Spatial affordances .................................................................................... 179 5.4 Space as Lived: Co-Constructed Aspect of Learning Spaces (Third Question) . 180 5.4.1 Physicality, individual and shared spaces ................................................. 180 5.4.2 Liminality, in-between and on the margins .............................................. 181 5.4.3 (Re)-Configurability .................................................................................. 181 5.5 Summary of Chapter 5 ........................................................................................ 182 Chapter 6: Conclusion and Recommendations 183 6.1 Contribution to the Literature: Developing Design Methodology and Domain Theory Drawing on DBR ................................................................................... 183 6.1.1 Design methodology ................................................................................. 185 6.1.2 Domain theory ........................................................................................... 185 6.2 Design principles (Lessons Learned) .................................................................. 186 6.2.1 Learning space is a layered multi-faceted phenomenon ........................... 186 6.2.2 Learning space is an indicator of support ................................................. 188 6.2.3 Learning space has a potential to improve and sustain well-being ........... 188 6.2.4 Learning space is a changing entity .......................................................... 190 6.3 Recommendations for Future Research .............................................................. 192 Recommendation 1 ............................................................................................ 192 Recommendation 2 ............................................................................................ 192 Recommendation 3 ............................................................................................ 192 6.4 Contextual and Practical Recommendations ....................................................... 193 6.5 Looking Back on My journey/Final Comments .................................................. 195 References 197 Appendices 226 Appendix A: Behavioral Research Ethics Board Certificate of Approval ................ 226 Appendix B: Tri-Council Policy Statement (TCPS 2: CORE) Certificate ............... 227 Appendix C: Information Sheet and Initial Consent for Using Data from the Questionnaires ..................................................................................... 228 Appendix D: Questionnaire ....................................................................................... 230 Appendix E: Information Sheet and Informed Consent in Photovoice ..................... 234 xiii Appendix F: Photovoice Training Agenda ............................................................... 237 Appendix G: Instructions for Photovoice Participants.............................................. 238 Appendix H: Consent to Use of Image Form ............................................................ 239 Appendix I: Photo Release Form .............................................................................. 241 Appendix J: Semi-structured Interview Questions ................................................... 242 Appendix K: Information Sheet and Informed Consent for Participating in Participatory Design ............................................................................ 243 xiv List of Tables Table 3.1 Summary of research questions and methods of data collection and analysis .... 39 Table 3.2 Demographic of participants ................................................................................ 40 Table 3.3 The Analysis procedure for each photo drawing on reflexive iteration .............. 77 Table 3.4 Establishing trustworthiness during each phase of thematic analysis, adapted from Nowell et al. (2017) ..................................................................................... 97 Table 4.1 Summarized data from questionnaire’s second section ..................................... 104 Table 4.2 Different aspects of learning spaces and their degree of importance to doctoral students in questionnaire .................................................................................... 106 Table 4.3 Codes and themes regarding additional spaces participants considered as learning space (questionnaire) ......................................................................................... 107 Table 4.4 Synthesis of pre-established categories and emerged codes into themes (questionnaire) ................................................................................................... 108 Table 4.5 Combining the emerged codes into themes: participants’ perceptions of learning spaces (questionnaire) ....................................................................................... 110 Table 4.6 Participants’ degree of agreement with the statements in the third section of the questionnaire ...................................................................................................... 119 Table 4.7 Comments on UBC Okanagan’s learning spaces, participants’ experiences (questionnaire) ................................................................................................... 120 Table 4.8 Codes and themes from section four of questionnaire, participants’ ideals and imaginations ....................................................................................................... 123 Table 4.9 Refined themes and areas for discussion and exploration (data from questionnaire) ..................................................................................................... 126 Table 4.10 Codes and themes from the deductive analysis of the interview transcripts ... 131 Table 4.11 Themes developed from codes: individual transcripts and cross-case coding/thematizing (interviews) ..................................................................... 136 Table 4.12 Doctoral students’ experiences in existing spaces, data from interviews ........ 138 xv Table 4.13 Themes developed from codes: individual and cross-case coding/thematizing, data from participatory prototyping ................................................................ 162 xvi List of Figures Figure 2.1 Conceptual framework to study learning spaces in doctoral education ............. 27 Figure 2.2 Lefebvre’s (1991) spatial triad — Production of space ..................................... 30 Figure 2.3 Adapting Lefebvre’s (1991) production of space and research questions — Production of learning space .............................................................................. 30 Figure 3.1 DBR stages by Plomp (2007) and their interrelationship to the research questions ............................................................................................................ 46 Figure 3.2 DBR and participatory design to develop domain theories and design methodology ...................................................................................................... 49 Figure 3.3 Design Research Methods based on Different Levels of User’s Knowledge adapted from Sanders (2002) ............................................................................. 50 Figure 3.4 Sequential phases of data collection drawing on Design Research Methods ..... 51 Figure 3.5 DBR (Reeves, 2006), Design Research Methods (Sanders, 2002), and data collection methods ............................................................................................. 52 Figure 3.6 A schematic overview of the sequential yet overlapped phases of the study ..... 56 Figure 3.7 Captured screens from VideoScribe ................................................................... 89 Figure 4.1 Coding strategies and development of themes drawing on Thematic analysis ............................................................................................................. 103 Figure 4.2 Classrooms have been the most important learning spaces during my studies. 116 Figure 4.3 Most of my learning takes place in the labs, which are typically assigned to a specific department or program ....................................................................... 116 Figure 4.4 Campus library is a motivating learning space ................................................. 116 Figure 4.5 I have found the Graduate Collegium a productive learning space .................. 116 Figure 4.6 Bookable Student Study Spaces on campus (for example in EME building) have been useful as individualized spaces for writing and reflection ...................... 116 Figure 4.7 The graduate office provided by my supervisor/program has been an important space in my PhD program. ............................................................................... 116 xvii Figure 4.8 I prefer doing my studies off campus in informal spaces such as coffee shops 117 Figure 4.9 I would rather work from home whenever it is possible .................................. 117 Figure 4.10 If I have access to a quality internet and online resources, I can be anywhere to do my work .................................................................................................... 117 Figure 4.11 Social spaces that foster conversations with scholarly communities have been important during my PhD experience. ........................................................... 117 Figure 4.12 I have done [part of] my PhD in an interdisciplinary environment interacting with peers from different backgrounds and I have found it productive. .......... 117 Figure 4.13 Being a member of a wider scientific community on campus has helped me dealing with isolation in my PhD .................................................................... 117 Figure 4.14 Available physical spaces on campus have been sufficient and helpful to conduct my PhD .............................................................................................. 117 Figure 4.15 Campus Map to prioritize the usage of the spaces by participants ................. 121 Figure 4.16 Coding strategies in Photovoice analysis drawing on Thematic Analysis ..... 135 Figure 4.17 Photovoice analysis collage, deductive approach in Thematic Analysis ....... 141 Figure 4.18 Photovoice analysis collage, inductive approach in Thematic Analysis ........ 142 Figure 4.19 Photovoice analysis collage, latent approach in Thematic Analysis ............. 143 Figure 4.20 Doctoral student’s individual space in a shared office ................................... 145 Figure 4.21 International doctoral student’s work space at home ..................................... 146 Figure 4.22 Supervisor’s front porch space used for research meetings ........................... 148 Figure 4.23 Supervisor’s sketches used in meetings ......................................................... 148 Figure 4.24 Doctoral student working in a café ................................................................. 150 Figure 4.25 Doctoral student working from home in a weekend ...................................... 150 Figure 4.26 Doctoral student’s workspace in the kitchen .................................................. 152 Figure 4.27 An under-stair area and a random couch turning into a learning space ......... 153 Figure 4.28 MacLab as a flexible space on campus .......................................................... 154 xviii Figure 4.29 Portable cardboard standing desk made by a doctoral student ....................... 154 Figure 4.30 Comparing students’ identified learning spaces and students’ experineces ... 156 Figure 4.31 Sudents’ experiences in individual and social level ....................................... 158 Figure 4.32 Padlet contents ................................................................................................ 160 Figure 4.33 Coding and theme development strategies in prototype analysis .................. 161 Figure 4.34 Participatory prototyping analysis collage, inductive approach in Thematic analysis .......................................................................................................... 163 Figure 4.35 Arrangement of private and collective spaces ................................................ 165 Figure 4.36 Arrangement of private and collective spaces ................................................ 165 Figure 4.37 Participant’s digital post-it note, bottom right note ........................................ 165 Figure 4.38 Movable coffee cart ....................................................................................... 165 Figure 4.39 Turning an unused space on campus into a workspace .................................... 166 Figure 4.40 Folding doors ................................................................................................... 167 Figure 4.41 Movabe and writable walls .............................................................................. 167 Figure 4.42 Temporary outdoor shelters ............................................................................. 168 Figure 4.43 Indoor green office space ................................................................................ 168 Figure 6.1 Summarizing contributin of this study to the related literature ........................... 184 xix List of Abbreviations and Terms Abbreviations DBR: Design-Based Research EME: Engineering Management and Education Building, University of British Columbia’ Okanagan Campus FCCS: Faculty of Creative and Critical Studies, University of British Columbia’s Okanagan campus FHSD: Faculty of Health and Social Development, University of British Columbia’s Okanagan Campus IGS: Interdisciplinary Graduate Studies, University of British Columbia’s Okanagan Campus IKBSAS: Irving K. Barber School of Arts and Sciences, University of British Columbia’s Okanagan Campus OSE: Okanagan School of Education, University of British Columbia’s Okanagan Campus SOE: School of Engineering TA: Thematic Analysis UBC: University of British Columbia UBCO: University of British Columbia’s Okanagan Campus xx Terms Design intervention: Design intervention is the prototype(s) that provoke real world action and intervene in existing human condition to address a problem and offer potential solution(s). In the context of this study, ideational space or representational space in prototyping phase was the space(s) that inhabitants attempted to intervene in and adapt the existing learning spaces to their own requirements. Design solution: In the Design-Based Research literature design solution or design framework is the end product as a means to offer solution(s) to a specific design problem. The design solution may be further refined in the future iterations. Eclectic approach to data analysis: This multiple-phased study explored there different, yet related, research questions and required an eclectic method of data analysis. This study drew on the logic of DBR, which allows employing different data analysis strategies based on the collected data in order to explore the phenomenon in its complexity. Knowledge-based society: A knowledge-based society generates, shares, and makes knowledge available to all members of the society to improve the human condition. An increasing shift to the knowledge-based societies is occurring due to globalization and the problems that it has caused, which reinforces the importance of the doctoral programs more than ever. xxi Acknowledgement My sincere gratitude goes to my doctoral supervisors, Dr. Susan Crichton and Dr. Karen Ragoonaden. Dr. Crichton’s caring, enthusiastic, and motivating approach enabled me to take risks and enlarged my vision of design in the new age. She always challenged me at the right times and provided intellectual and moral support. Dr. Ragoonaden’s deeply insightful comments and penetrating questions, driven by her expertise in teaching and learning scholarship as well as her mindful approach to teaching and learning, taught me to question more deeply. I also want to express my heartfelt gratitude to my doctoral committee members, Drs. Lynn Bosetti, Robert Belton, Patricia Lasserre, and Susan Frohlick for their thoughtful discerning feedback that helped me improve the articulation of my ideas. I will treasure forever the Research Methodologies in Education course taught by Dr. Bosetti at the very beginning of my PhD program. Through thoughtful conversations, she helped me better identify the epistemological and ontological assumptions of my research. I would like to thank Dr. David Labaree in Stanford Graduate School of Education and also Stanford’s Design School (d.school) for their generous approach to host me as a visiting student. Attending design thinking workshops at d.school was a great first-hand experience to explore different possibilities of design as a human-centered approach. In addition, my gratitude goes to the UBC for the University Graduate Fellowship (UGF) during my studies. As a recipient of the Vicki Green Graduate Award, I would like to thank Dr. Green for her generous support and the award committee for nominating and selecting me. This research study would not have been possible without the involvement of my research participants. Many thanks are owed to the participants in this research, doctoral students and alumni of UBC Okanagan, for taking the time to share their insights. At the moments of intense loneliness of a PhD student, my dear friend and my “PhD buddy”, Dr. Mahsa Pakravan, from University of Alberta was always at the other end of the phone; I am so thankful for all her unflinching and heartwarming words. I would like to extend a special acknowledgement to my family for their constant care and encouragement when all seemed muddy and dark. Finally, my deepest thanks go to Mohammad, my dear spouse, for his love, care, and support; his loyal support during every single stage carried me through. xxii Dedication To Mohammad: !میدرک شمومت We made it! 1 Chapter 1: Introduction 1.1 Preamble This research reflects part of my wanderings in the world of Design and Education. Over the past two decades, I have been working as a design practitioner, design educator, and design researcher in four different countries in three continents. I have observed and experienced shifts, re-framings, and connections in different areas of design, all of which suggest a move from designing of things through conventional approach towards designing informed by interactions with people and systems through a participatory approach. These changes have propelled design from designing for people to designing by people and with people. They have altered my perceptions about design and challenged my assumptions about my responsibilities as designer. Having been trained as an industrial designer, I started my professional journey with a designing-for mindset and later, I gradually moved towards a designing-with/by mentality. As a part of this transition, this research project reflects my exploration on “what to design” instead of “how to design”. Moreover, my interest in teaching and learning has gradually evolved through teaching as an instructor and coming back to graduate school to pursue a MA in Education. My position as a PhD candidate in Interdisciplinary Graduate Studies within Okanagan School of Education seemed an excellent terrain to combine my interests in Design and Education. My passion for conducting this research on learning spaces lies in the fact that it is situated in the intersection of Design and Education. It was also my deep interest for space and place that fueled my passion for this research. Living as an immigrant, I have always grappled with the notion of space and how it could be turned into a place. In addition, as a graduate student, I had the chance to experience several campuses as a visiting student; I have felt that how different layers of learning spaces along with the scholarly communities could impact my work, well-being, and sense of belonging. My deep intention to conduct this study was to contribute to creating meaningful involvement of doctoral students that connects them more to place. The last part of this study was conducted during COVID-19 global pandemic and still so many uncertainties remain as educational institutions plan for the reopening of their buildings to students and educators. Considering the radical changes that COVID-19 has brought in how we work, collaborate, study, and engage in social events, the timing is right 2 for higher educational institutes to rethink their learning spaces for the post- COVID era in order to support students’ learning and their meaningful engagement in learning communities and learning spaces. While further exploration on learning spaces in post- COVID time is beyond the scope of this study, it will certainly inform my subsequent work. 1.2 Overview of Chapter 1 In this chapter, I provide an overview of the study and explain the context of the study and research questions. This chapter also includes the research approach I chose to answer my research questions. Then, I briefly explain the theoretical framework that underpins this study as well as purpose and significance of this research. At the end of the chapter, I outline the organization of this dissertation. 1.3 Overview of the Study An increasing shift to the knowledge-based societies is occurring due to globalization and the problems that it has caused. As a result, participation of scholarly communities to offer solutions to those problems has been increasingly required, which reinforces the importance of the doctoral programs more than ever. This shift has necessitated programs to re-frame doctoral education through incorporating responsive approaches, skills, and environments to support students’ learning and prepare them for the potential diverse futures within and/or beyond the academia, where they can address the complex problems of the new age (Flores & Nerad, 2012; Nerad, 2012; Walker et al., 2009). Learning space is an important factor, among many, in the complex relationship that enables learning and is an integral part of teaching, learning, and research activities. Learning spaces have been investigated within a range of disciplinary perspectives including architecture and design (Long & Ehrmann, 2005; Savin-Baden, 2007), environmental behaviorism (Scott-Webber, 2004), and library sciences (Beatty, 2016; Elmborg, 2011). Often, learning space in the higher education setting has been considered in the context of space planning, or in the context of campus master-planning and architecture, which aim at providing appropriate amounts of space for the defined uses and to maximize their uses (Temple, 2007). The idea of strategic planning of the university estate has emerged to link decisions about the estate to wider issues of institutional strategy, but it has been dominantly concerned about space utilization and financial effectiveness (Avery, 1994; HEFCE, 2000). There is limited literature with a focus on space issues in relation to teaching 3 and learning, or research-related practices (Temple, 2008). Furthermore, despite an increasing interest in learning space research both in education and architecture, the key basic concepts in relation to learning and space remain uninvestigated (Boys, 2011). McAlpine and Norton (2006) suggest if doctoral education is to be changed, it can best be achieved through thinking and acting based on the factors that are influencing students’ experiences of the doctorate. Acknowledging that students are central to the doctoral undertaking, literature suggests their voice is least heard (Golde, 2000; McAlpine & Norton, 2006). Therefore, it is safe to assume that the voice of students, the intended users of the learning spaces, is also missing in designing such spaces. At the same time, contemporary approaches in architecture and design emphasize the direct and active participation of all stakeholders in the design process. This approach can make design a participatory process and more meaningful to the people who will ultimately benefit from the products of design. This approach is based on a contemporary shift in perspective at the collaborative domain of design and social science which Sanders (1999) calls postdesign. It focuses on a co-design process where people are invited to play the game through designing together providing a large set of ideas and opportunities. In this study, I developed an integrated conceptual framework and a process for data gathering and knowledge creation which allowed me to explore learning space design for doctoral education. The procedure developed in this study addressed subjective, objective, and co-constructed aspects of learning spaces in doctoral education. The purpose was to reach areas connected to understandings, experiences, and imaginations of doctoral students about learning spaces. Intersection of Lefebvre’s (1991) Production of Space along with Situated Learning theory (Lave & Wenger, 1991) enabled me to build an integrated conceptual framework to explore spaces for learning in doctoral education context. Findings from this study are not intended to produce any generalized design solutions or provide a complete account of learning space design. In this study, I developed and tested a new framework and methodology for data gathering and knowledge creation about learning space design for doctoral education through a participatory approach. The results represent a 4 vision, a beginning base to take action based on students’ understandings, experiences, needs, and imaginations about learning spaces. 1.4 Context of the Study While it is possible to ask whether a space makes a difference to learning (Durán-Narucki, 2008; Kumar, O’Malley, & Johnston, 2008), Woolner et al. (2012) explain it is also important to acknowledge that this is not a simple, quantitative relationship, where better environments produce better learning. In reviewing older examples of school settings (e.g., Gislason, 2010; Higgins et al., 2005; Saint, 1987; Weinstein, 1979), we may notice inconclusive and contradictory research evidence which indicates a complex and interactive relationship between learning and space. An educational institution is part of a wider, dynamic web of cultural and social aspects which requires contextual investigation to unravel the relationship between space and learning. Gislason (2010) urges closer investigation of institutions to suggest how involving elements (space, organization, and culture) “can be aligned to ensure a positive learning environment” (p. 145) and this complex inter-relationship suggests the necessity of an in-depth understanding of the setting, adaptation, and changes both to teaching and learning practices and to learning spaces. Canada has contributed to the global conversation about doctoral education reform (Challenges to Innovation in Graduate Education, 2005; Osborne et al., 2014; Porter & Phelps, 2014; SSHRC, 2015). However, the origin and nature of doctoral education might be quite different among the institutions and disciplines which require specific contextual investigation due to the autonomy and different policies, aims, and development trends of the universities in Canada (Jones, 2014; Williams, 2005). In addition, learning engages with the complex and situated intersections with the spatial and social practices (Boys, 2011a) and learning spaces —including conceptual, personal, social, digital, and physical space— need to be studied in the context of each institution’s culture. Drawing on Situated Learning theory, Nerad (2012) confirms that learning is situated in the activity, context, and culture of the place where it takes place. This study is situated at the University of British Columbia’s (UBC) Okanagan campus, a relatively new campus within UBC system. UBC Okanagan is situated on the unceded lands of the Syilx Okanagan People. It was established in 2005 with the promise of becoming a research-intensive institution and the aim of developing a model for new ways of 5 thinking about interdisciplinary and innovative programs appropriate for the 21st century (Aspire, 2014). It is developing both its academic identity and its core commitments of “transformative student learning, research excellence and community engagement at this Place” (p.11). “Place” is a category that has been identified as a priority area for future explorations at UBC Okanagan. Identifying strategies to develop and maintain a distinctive learning environment grounded in the integration of innovative teaching and research has been addressed in the intended plans of the UBC Okanagan for future efforts (Aspire, 2014). Moreover, University of British Columbia, which consists of two campuses – Point Grey and Okanagan, is a member of U15 Group of Canadian Research Universities, an association of 15 Canadian public research universities focused on research and research development. The U15 members attempt to identify and nurture talents and seeking to fulfil the potential of the next generation of Canadian and world leaders. Collectively, the members of U15 represent 70 percent of all full-time doctoral students in the country (U15, 2017). UBC Okanagan, with its developing identity within the UBC system, was an ideal base to conduct this study. Findings from this research identify further studies to improve doctoral education’s learning spaces in a larger scale. 1.5 Research Questions The intention to conduct this study was twofold. The first aim was to unravel what matters about learning space in graduate programs—including conceptual, personal, social, digital, and physical space— and its relationship with learning and research practices from doctoral students’ perspectives. The second aim was to create a case for a participatory design process, where students can imagine the future of their learning spaces. This study addresses and answers the following research questions: 1. How do doctoral students perceive a “learning space” and its intended use(s)? Considering the distinguished characteristics and aims of doctoral education within the broader picture of higher education, understanding the interactions between learning and 6 space, where transformative ideas can cultivate and flourish, remain unrecognized. Hence, the second question has been developed to answer: 2. What is the relationship, if any, between the university’s provided learning spaces and students’ identified spaces? The third question explores the ways to collaboratively envision the future of learning spaces based on findings from the first and second questions: 3. How might doctoral students envision the future of their learning spaces? Taking a participatory and human-centered approach in the context of learning space, this phase of study explores learning spaces through hearing students’ voices, the multiple voices that have been missed in the process of learning space design, with the aim to envision the learning spaces for doctoral education. 1.6 Research Approach The research questions of this study reflect both theoretical and practical aims, which were refined through the conduct of the study. The iterative development of the research questions aligns with a qualitative approach to research design (Creswell, 2007, p. 43) and Design-Based Research framework (Joseph, 2004). To answer the research questions, I developed a multi-phased research through three sequential phases, and accordingly, I used different methods of data collection and analysis for each phase. Data from the questionnaires addresses subjective aspect of learning spaces (first question), Photovoice and plus semi-structured interviews address objective aspect of learning spaces (second question), and participatory prototyping informs co-constructed aspect (third question). The purpose of multiple approaches was to reach areas connected to understandings, emotions, memories, experiences, and ideals of participants about learning spaces. With this purpose in mind, I drew from the concept of different degrees of users’ knowledge in Design Research Methods including what people say, what people do, and what people make (Sawhney, Prandelli & Verona, 2003), which correspond respectively to explicit, tacit (observable), and latent knowledge of the participants. Doctoral students and alumni from UBC Okanagan participated in this research. Thirty-eight individuals accepted the recruitment invitation and participated in the first phase. 7 Participants of the second and third phase (eleven and twelve people, respectively) were emanated from the original thirty-eight. A combination of interconnected strategies for analyzing the data was applied in this study. While Thematic Analysis (TA) (Braun & Clarke, 2006; Boyatzis, 1998; Roulston, 2001), as the general method, informed the data analysis process at all stages, complimentary strategies were integrated to each phase; reflexive iteration and axial coding in questionnaires analysis, reflexive iteration, axial coding, and art-informed approach in Photovoice, and reflexive iteration and art-informed approach in participatory prototyping. The benefits of using such an eclectic approach included cross-disciplinary non-linear investigation, creating a complete picture of participants’ knowledge obtained in different levels, enhancement of trustworthiness and rigor, and building a creative medium to interpret the data. 1.7 Theoretical Framework Intersection of Lefebvre’s (1991) Production of Space along with Situated Learning theory (Lave & Wenger, 1991) enabled me to build an integrated conceptual framework to explore spaces for learning in doctoral education context. This framework is not merely about developing a design guideline or offering any design solutions; it is more about questions to ask within the complex relationship between space and the act of learning, which can support and inform design of learning spaces in the future. To explore learning spaces from a Lefebvrian perspective, it was necessary to explore the production of such spaces considering the complexities of social reality and avoiding binary thinking about learning spaces (for example formal versus informal spaces). Careful attention to the perceived, conceived, and lived spaces, respectively related to students’ perceptions, experiences, and imaginations of doctoral students, explored in questionnaires, Photovoice, and prototyping, can illuminate how learning space is produced. Lefebvre’s conception of space (1991) suggests investigating the interactions between occupants and space. Based on this view, the societal production of space is a dialectical interaction between physical, mental, and social spaces. Lave and Wenger’s (1991) Situated Learning and communities of practice model sees learning as a dynamic social process and acknowledges that students’ learning is situated within distinct and different academic communities. Drawing from this integrated framework, learning is always situated and 8 embodied, not just in material space but also in individual, social and cultural contexts. Also, space can only be viewed in relation to its occupation, that is, as socio-spatial practice. 1.8 Purpose of the Study This study explores the notion of learning spaces and how they might be understood, used, and envisioned by the learners within the context of doctoral education. Proposing a conceptual framework and a methodology, this study evaluates learning spaces based on students’ experiences at UBC Okanagan campus and explores what lessons can be learned from imagining the future of learning spaces through prototyping. This research proceeded from the view that space is “socially constructed” (Lefebvre, 1991). It intended to systematically document, reflect on, and evaluate UBC Okanagan’s learning spaces in relation to doctoral students’ perceptions of the spaces and the influence of the provided spaces on their learning and research-related activities. The aim was to support more participation in learning space design and make students’ multiple voices heard. This study identifies the main conceptualizations of learning space from students’ points of views, which is a missing piece in the literature. To draw from this work, areas for further empirical studies will be identified and implications for future practices in learning spaces for doctoral students will be suggested, which can help doctoral education providers and stakeholders (universities, doctoral programs, space designers) act flexibly and creatively in adapting and transforming the learning spaces through time. Findings from this study identify areas for the future studies and actions to be taken by UBC and suggest implications for learning space studies for the U15 (Group of Canadian Research Universities) and U21 (the leading global network of research universities for the 21st century) in which UBC is a member. 1.9 Significance of the Study There has been an increasing interest in designing learning spaces by architects and designers over the past few decades; however, the key basic questions in relation to space and learning in higher education appear to remain unanswered (Boys, 2009). Also, power differences in designing learning spaces can be the case in higher education settings where 9 space is considered in strategic planning with dominantly concern of space utilization and financial effectiveness by institutions (Avery, 1994; HEFCE, 2000). From a different perspective, this research views space as a “socially constructed” entity (Lefebvre, 1991). Also, assuming that space cannot be separated from its occupants (Boddington & Boys, 2011), changing learning spaces for the better in doctoral education is about understanding and improving the socio-spatial practices of the space occupants. As an exploratory process, this study supports the development of domain theory (design principles) and design methodology (design procedure) based on Design-Based Research. Applying a participatory approach to explore learning spaces enabled creative and imaginative engagements with new learning scenarios. Sherringham and Stewart (2011) confirm in such exploratory process, a rich tapestry of socially constructed information is developed for designers to interpret and translate. While exploratory in nature, this study has implications for universities’ future decisions and practices with regard to learning space planning and assessment. Also, in addition to considering space usage, capacity and comfort, space providers and designers should consider student perceptions and experiences of learning spaces when planning university spaces. Students can provide important insight into the ways in which a space supports or does not support their learning and motivation. 1.10 Organization of the Dissertation Chapter 1 outlined the key elements of the study. In Chapter 2, I present a review of the literature that informed this study and the theoretical framework upon which the study was developed. The purpose of Chapter 2 is to review the theoretical, empirical, and methodological literature related to the field in order to identify potential gaps within the existing literature, which positions my research questions in the literature as a way of contributing to the field. In this research, I reviewed the literature in a flexible, recursive, and iterative process. The theoretical framework identified in Chapter 2 holds the emerging meaning throughout the study where I analyzed the data and discussed the findings. In Chapter 3, I present the methodology that I used in this study. I provide a rationale for my choice of methodology and explain the methods used to collect and analyze the data 10 for each phase. I also explain the limitations and the involving issues in each used method. At the end, I discuss trustworthiness and my role as researcher. In Chapter 4, I present the findings from the data gathered in this study. These findings are presented in relation to the themes that arose from my initial review of the literature and from my analysis. The various methods used to collect the data provided numerous opportunities to honour the participants’ voices and ensure triangulation and reliability of the findings. In Chapter 5, I provide a discussion based on the findings in Chapter 4 that connects the findings to the research questions. In Chapter 6, I explain the contribution of this study to the literature, the design principles (lessons learned), recommendations for future research as well as some contextual and practical recommendations. I close the chapter with looking back on my journey and some final comments. 11 Chapter 2: Conceptual Framework and Review of the Literature 2.1 Overview of Chapter 2 In this chapter, I present a review of the related literature in the field of learning spaces in higher educational setting with a specific focus on the spaces utilized by doctoral students. The purpose of this chapter is to review the theoretical, empirical, and methodological literature related to the field to identify potential gaps within the existing literature, and to address the philosophical frameworks that underpin the study, which positions my research questions in the literature as a way of contributing to the field. I reviewed the literature in a flexible, recursive, and iterative process. Literature review was not limited to chapter two; I conducted additional reviews based on the needs of study in different stages. However, the theoretical framework identified in this chapter holds the emerging meaning throughout the study where I analyze the data and discuss the findings. 2.2 Scope of the Review The literature informing learning spaces comes from a range of disciplinary and professional perspectives, including those related to architecture and design, learning, psychology, institutional identity, and student experience. In this study, the initial research questions confined the scope of the literature review. The review of the literature was framed between literature that engages “space” and “learning” within the transitioning doctoral education in twenty-first century. The review of the literature addresses the territory between two domains: education and architecture (design in general), to integrate them, to illustrate the field within the context of doctoral education, and to address a gap within the literature that became the focus of this study. Furthermore, through the perspectives of design and education, the review of the literature mapped the field based on the research questions and identified the underpinning theoretical and methodological framework of this research. 2.3 Changing Conceptions of Doctoral Education Doctoral programs have been essentially designed to train a doctoral student for a lifetime of intellectual inquiry through conducting original research within a Doctor of Philosophy program (Council of Graduate Schools, 2005). It is generally agreed that the purpose of such process is to educate scholars who are capable of producing original research creatively and independently. Considering the process of becoming an independent scholar 12 within the doctoral program, Gardner (2008) suggests that conducting doctoral research may involve student’s feelings of isolation, but at the same time the transition to become an independent scholar should be an integral part of the socialization process that occurs in graduate school. Hence, doctoral studies experience is considered as a contextual practice, which is influenced by the social practices of scholarly communities. The traditional approach of doctoral education sees the process of becoming an independent researcher based on an apprenticeship model, where a doctoral student learns from one master, who is the supervisor (Shulman, 2004; Kwiram 2006). But a closer look at current conceptual and empirical approaches to doctoral education (Flores, 2011; Nerad, 2012; Nerad & Heggelund, 2008) indicates the traditional apprenticeship model is too narrow to train the independent researchers for the twenty-first century. Kehm (2006) believes the traditional apprenticeship model can possibly cause problems such as creating a high degree dependence on the supervisor, resulting in a frequent lack of quality in supervision, causing high drop-out rates, spending a long period for degree, and lacking the development of required skills for the new age. Preparing the next generations of PhD graduates, individuals who are able to contribute to address and solve the twenty-first century’s complex problems, requires different approaches that go beyond the apprenticeship model (Austin, 2009; Pyhältö, Stubb & Lonka, 2009). Therefore, a paradigm shift has been occurring in doctoral education towards developing a learning process that can take place within different learning communities and learning environments. Austin (2009) suggests that applying a cognitive apprenticeship model can offer some practical response to some of the concerns involved with the traditional apprenticeship model. Drawing on this model, learners need to develop the relevant cognitive and meta-cognitive processes to see how experts of their field understand and address the problems. Pyhältö, Stubb, and Lonka (2009) confirm that providing students with the experience of being a member of scientific communities could support students’ doctoral studies experiences; they recognize an urgent need to foster PhD students’ active agency in scholarly communities. A scholarly community can be seen as a learning environment that integrates different elements such as supervision, knowledge, learning and assessment practices, as well as the learning environment (Gardner, 2007). There is a growing literature on the importance of 13 communities of practice within learning environments and their influence on students’ experiences, their professional identity, and their development of expertise in doctoral level (Austin, 2009; McAlpine & Norton, 2006; Pyhältö, Stubb & Lonka, 2009). However, learning spaces, as an important factor of a scholarly community, among others, and their relationships with other involving factors have not been explored enough (Boys, 2011a; Temple, 2007, 2008). Considering student’s experience of learning at its core and emphasizing the social and complex nature of learning in doctoral education (Bédard et al., 2000; Laurillard, 2002), McAlpine (2004) states the results of learning are often observable (e.g., attrition), but the processes are frequently invisible. Understanding students’ learning experiences within the existing spaces along with their perceptions and ideals of a learning space is critical to evaluate the spaces and identify their real needs. It can help “illuminate” our understanding of learning spaces (Parlett & Hamilton, 1972) to explore the potential possibilities to support students’ learning within communities of practice. 2.4 Opening up Two Points of View to Explore Learning Spaces Research on learning spaces has been conducted within the fields of architecture and design (Long & Ehrmann, 2005; Savin-Baden, 2007), teaching and learning (Bond & Goodchild, 2012; Parisio, 2013; Radcliffe, Wilson, Powell & Tibbetts, 2009) environmental behaviorism (Scott-Webber, 2004), and library sciences (Beatty, 2016; Elmborg, 2011). It has been situated within the scholarly publications associated with those disciplines; and as a result, there are a variety of resources to find scholarly studies on learning space. Historically, the study of learning spaces in higher education settings has not attracted a big deal of attention from scholars (Temple, 2008), but it has grown substantially in recent years. Gierdowski (2013) suggests a number of factors have brought learning space research to the forefront; twenty-first century’s technologies as well as teaching and learning trends such as social constructivist theory and active learning pedagogy (Brown, 2005; Chism, 2006; Scott-Webber, 2004) appear to have become among the most important factors in developing the learning space studies. It is worth mentioning that most of these studies that have been conducted in higher educational settings have focused more on undergraduate education (Ingram et al., 2013; Riddle & Souter, 2012; Temple, 2008). To satisfy the growing need for spaces more conducive to learning for undergraduate students, an array of 14 spaces for different purposes has been studied within the context of libraries; spaces such as: non-traditional facilities like cafés (Harrop & Turpin, 2013; Stewart, 2011), group study areas, (Dallis, 2016; Holder & Lange, 2014), social learning spaces (Bryant, Matthews, & Walton, 2009; Carpenter, 2011; Chan & Spodick, 2014), collaborative spaces (Booth, Schofield, & Tiffen, 2012; Cunningham &Walton, 2016), computer stations (Bailin, 2011; May & Swabey, 2015), individual study spaces (Lux, Snyder & Boff, 2016; Paretta & Catalno, 2013), as well as areas for solitude and quietness (Beard & Bawden, 2012; Cha & Kim, 2015; Massis, 2012). Despite the variety of studies on different aspects of doctoral education, its current situation and its potential possibilities for future, research into learning spaces in doctoral education seems to be missing in the spectrum of learning space research. In the context of higher education, a learning space can be different for each person in diverse situations of their lives. However, Savin-Baden (2007) suggests some common elements and overlaps of people’s experiences within academic contexts. The elements include: - Physical and/or psychological removal from the normal learning environment. For example, attending conferences, writing retreats, or working overseas. New environments often prompt new ways of seeing issues, providing opportunities for reflection and presenting challenges to current ways of thinking; - The creation of specific time for writing or reflection; - Using social learning spaces for dialogue and debate; - Accessing digital spaces for discussion and reflection with and through others (P.8). These common elements are helpful to confine a learning space to conceptual, personal, social, digital, and physical spaces. Giving a solid definition to a space for learning is problematic since it is an ambiguous and complicated notion due to the complicated relationship between learning and space. The concept of learning space simply expresses the idea that there are potential diverse forms of spaces in which learning can occur. However, there is a considerable complexity of interrelationships between learning and space (Boddington & Boys, 2011). To grapple with this complexity and avoid over-simplifying the notion of a learning space, 15 learning spaces should be seen from both architectural and educational angles through related theories and practices. In this study, I synthesize two different yet related perspectives to position learning spaces within doctoral education context. From the variety of resources on learning spaces, the literature related to students’ learning in doctoral education has been selected; moreover, considering the complexity of learning the resources that engage with space as a changing entity have been explored. In educational studies, space or environment is usually referred to the ways in which teaching and learning are conceptualized, designed, or organized, rather than to do with physical arrangements (Temple, 2008). In such cases physicality of the space usually is not considered as an important factor or evaluated. Considering the physical characteristics of space along with the pedagogical and conceptual considerations requires an integrated framework through which learning spaces can be understood, evaluated, and designed as a whole. In addition, there has been an increasing interest in designing learning spaces by architects and designers within the time of changing the landscape of education over the past few decades. However, Boys (2009) claims, despite of the increasing interest, the key basic questions in relation to space and learning in higher education (including doctoral education) remain unanswered and learning spaces of higher education setting remain under-researched. She remains concerned that contemporary debates of learning space design are often developed based on the assumption of a shift from formal to informal learning spaces. While many of the new flexible informal spaces —such as learning cafés or using bright colors, natural lighting, playful graphics, and soft furnishings— seem interesting, little is known about the underlying analysis of what is (or should be) changing in learning spaces, students’ experiences in such spaces, or the impact of space on students’ learning (Boys, 2009). Blackmore et al (2011) confirm the assumptions underpinning the principles of contemporary learning space design “are largely anticipated rather than empirically justified claims” (p.6). Simplifying learning spaces into a binary division of formal-informal spaces may give exciting additions to the learning spaces, while it seems metaphorical. Metaphorical approach to space design can give it the appearance of a commonly agreed reality, but this does not mean that the result is interpreted in the same way by space inhabitants. Boys 16 (2011a) criticizes metaphorical approach to learning space design and believes that it refuses the unremitting need for improvement of the formal leaning spaces and does not able to engage fully with the key issues within the paradigm shift of contemporary education. She declares that current theoretical debates from both architecture and education have been rarely integrated within the learning spaces literature. This issue sets a line of inquiry to explore how the recent theories and approaches of architecture and education could inform our engagement with learning spaces. Analyzing the existing learning environments and envisioning the future ones require developing an interdisciplinary conceptual framework and analysis, which can relate the space design to doctoral education’s distinctive characteristics for the new age. Reviewing the literature in this study, I propose an integrated framework of architecture and education, which guides the development and implementation of the study. Drawing on Soja’s (1989) definitions of space and place, this study distinguishes between place and space with the understanding that they both overlap and draw meaning from one another. In the context of this study, space is meaning making to address the social meanings that occur within material contexts, while place is defined as material to address the physical environments in which we live/work/study. As Kuntz (2012) clarifies, one’s workplace, for example, consists of both the material places in which one works and the social environments that draw meaning from such places. 2.4.1 Learning spaces from educational perspective: learning as a dynamic social process Scholarly investigations on the learning spaces of campuses have grown significantly in the recent years. The increasing shift to the network and knowledge-based society (Perkin, 2007) as well as the emergence of twenty-first century’s technologies (Scott-Webber, 2004) and consequently an underway paradigm shift in teaching and learning trends — moving from a transmission paradigm to a constructivist paradigm (Brown, 2005) — have all brought learning space research and design to a new position, which seems more considerable than the past. An important aspect of education is the discourse generated through interactions. Duggan (2011) states in a world where we can access information anytime and anywhere, institutions continue to build upon the enduring importance of people and place. Considering this distinction between the access to information and the process needed to make meaning 17 and create knowledge, higher educational institutions need to provide high quality learning experiences which are situated, embodied and social, make connections with their local communities, build learning groups through their academic programmes, and create communities through their research and enterprise initiatives. Learning space is not the only factor when it comes to student learning in higher education, but as Gierdowski (2013) mentions it is a critical variable in the equation. It is critical to consider learning spaces in relation to recent learning trends and students’ needs. McAlpine and Norton (2006) put students’ experiences of learning at the core and suggest possible changes can best be achieved through thinking and acting based on those experiences. On the other hand, learning, the act and the process of acquiring new or modifying and reinforcing existing knowledge, behaviors, skills or values (Gross, 2015), has a complex and social nature (Bédard et al, 2000; Laurillard, 2002). Emphasizing this characteristic acknowledges that students’ learning is situated within distinct and different academic communities (Becher & Trowler, 2001) in higher educational setting, which Lave and Wenger (1991) has already called it communities of practice. Delamont, Atkinson, and Perry (2000) mention that those who enter the communities of practice get distinct acculturation experiences in doctoral context; such communities can provide a potential learning environment for doctoral students within certain social practices. Tight (2008) states that if communities of practice are seen as structure, higher education is a series of somewhat overlapping communities of practice. Wisker, Robinson, and Shacham (2007) claim conducting doctoral thesis in isolation is the dominant problem of doctoral experience and being part of communities of practice has been seen to be helpful. Moreover, based on experiences of doctoral students, Lahenius (2012) claims communities of practice could have a positive effect on doctoral students’ study experiences and support their doctoral studies through providing students with the experience of being a member of a wider scientific community. Here, the assumption about learning is not only an instinctual process, which is practiced and applied by individuals; instead, learning is seen as a collaborative practice which can take place within communities of knowers. Wenger (1998) clarifies groups of people who share a concern to learn something and how to do it better as they interact regularly form communities of practice. He claims most learning takes place among the 18 members of such communities. Boys (2011a) supports communities of practice as an important concept to be considered in higher educational learning spaces. She believes learning in communities of knowers instills not just knowledge, but also a set of attitudes and culture. The importance of the learning context and communities of practice in promoting motivation and supporting learning (Lave & Wenger, 1991; Svinicki, 2004; Wenger, 1998) also aligns with cognitive apprenticeship approach in doctoral education, where learning can take place within different learning communities. The notion of community of practice has been developed based on the theory of Situated Learning, which views learning as a function of the activities, the context, and the culture in which learning is situated (Lave, 1988). It emphasizes learning as a meaning-making process by the learners and being supported within a community of practice in which they are engaged with others. Boys (2011a) claims considering the importance of communities of practice and the theory of Situated Learning (Lave & Wenger, 1991) in learning space debate offers a conceptual model of learning as a dynamic social process. This model is complex, non-binary, and situated; building on this theory enables us to investigate each specific learning environment as an intersection of the concepts that need to be taught and the underlying social and spatial conversations. Boys (2011a) clarifies: “[w]e need to explore how different learning spaces can make participants feel safe or uncomfortable, and the impact this can have on their learning” (p.46). 2.4.2 Learning spaces from architectural point of view: a dynamic interaction between space and occupants A growing debate on (re)designing the learning spaces in higher education has emerged over the past few years. More institutions have started designing and redesigning their campus learning spaces. Based on a Survey of Learning Space Design in Higher Education, conducted by the Society of College and University Planning (SCUP), 84% of the participants responded that the learning spaces of their campuses were undergoing significant construction or renovation (Vredevoogd & Grummon, 2009). Despite the growing constructions, Temple (2008) argues space is an under-researched topic in higher education settings because it has been rarely investigated as an integral part of teaching, learning, and research activities. There are other studies that indicate explicit links between space and learning theories remain poorly explored and at the same time, theories of learning themselves rarely emphasize the importance of space (Jamieson, 2003; Neary et al., 2010). In 19 a similar vein, Thomas (2010) argues “in short, our difficulty in understanding and articulating the nature of learning is partly brought about by our inability to articulate where learning takes place” (p. 502). In higher education institutions, consideration of space has commonly taken place either in the context of space planning, or as part of campus master-planning. Nevertheless, the campus master-planning of each institution can be informed by contextual research considering the relationship between students’ learning experiences and learning spaces. However, Boys (2011a) clarifies the new trend on developing learning spaces are mostly based on simplified notions of formal-informal learning spaces, which may offer exciting additions to the existing spaces, but they do not necessarily enable a better conceptual framework, appropriate research methods, or strategic critique to be developed. She argues that the area of learning spaces in higher education is “worryingly under-theorised” (p. 4). Tom, Voss, and Scheetz (2008) agree with her and note that many of the published reports on learning spaces contain positive “assertions of effectiveness rather than evidence” (p. 46). Within the learning space literature, there are also theories that guide the field of cognitive neuroscience and psychology on how learning occurs and how it may be influenced by environmental factors. However, I have considered these theories and literature to be generally beyond the scope of this study, which needs to be assessed within the appropriate framework from neuroscience and psychology. It is also worth mentioning that for many years behavioral and environmental psychologists have been attempting to study the different stimuli-response mechanisms such as comfort and quality of light, temperature, dimensions, ergonomics, etc. in architecture (Edgerton, Romice & Spencer, 2007). Such approaches are valuable to highlight the basic functional and psychological dimensions of built environment, but they have little impact on articulating the complexity of the everyday social and spatial practices of a community —here doctoral students— embedded in a situated context. Engaging with the functional and psychological needs of learning spaces remains important; as Boys (2011a) reminds us, these aspects should not be assumed as obvious and generic, but we should also be aware of the complex and situated spatial and social practices through which we learn. Focusing on this complexity and how space “works” in relation to its occupants, we need to frame learning spaces through contemporary theories of architecture. This frame can better inform our 20 understandings of learning spaces, especially in doctoral setting, where learning is embedded in communities of practice and the culture of such communities. There have been a growing number of scholarly investigations on learning spaces of campuses in the UK (Boys, 2011a; Pearshouse et al., 2007; Savin-Baden, 2007; Temple, 2007, 2008), Australia (Kennedy et al., 2013; Radcliffe, Wilson, Powell & Tibbetts, 2009;), and the United States (Carpenter, 2012; Ingram et el., 2013; Violette et al., 2012) to inform the future design of learning spaces within the campuses. Comparing the existing examples of the new developed spaces, Boys (2011a) points out that in the UK most of the examples concentrate on informal learning often connected to libraries and resource centers on campus, while in the United States and Australia there are examples related to creating new hybrid spaces, where different disciplines have the opportunity to collaborate; Stanford’s design school (d.school) is an important example of this category. Informal learning spaces offer physical arrangements towards more informal settings on a certain set of ideas such as active, social, or playful and with a tendency to use softer furniture, asymmetric layout, bright colors, and usually with the elements characterizing the space as “technology rich environment”. These types of spaces also are informing or being informed by other workplaces beyond campus (Myerson & Ross, 2006; Worthington, 2006) based on creativity and interactive information exchange through a more informal, playful design; Google, for example, has been at the forefront of such approach in playful workplace design (Boys, 2011a). In addition, focusing on academic workplaces, Harrison and Cairns (2008) indicate the informal open spaces seem to be beneficial encouraging collaboration and interaction based on experiences of a majority of users of such spaces. However, the authors learned that the open quality of space also brings the potential for disruption through noise and unplanned or unwanted meetings. Reviewing and evaluating the UK case studies of innovative academic environments, they have found that alongside the open informal spaces, academic offices still are being used as spaces for reflection, concentrated working, and meetings by academics. Despite the development of informal spaces for learning, there has been little research on the relationship between such representative and expressive spaces and their lived experience. Boys (2011a) argues despite the benefits reported in the literature, creating 21 informal spaces can be seen as simply translating ideas about learning or working into physical form through the mechanism of metaphor. She adds, we also need to have mechanisms of evaluating the effectiveness of different spaces on the quality of learning that take place in them. Jamieson et al. (2008) believe using metaphors can engage designers in the design process and create a common language; at the same time, it implies an obvious or a commonly agreed reality. In addition, all the users of the resulting space may not necessarily interpret it in the same way in everyday experience of the space. Contemporary architectural theories started since the 1980s have been challenging the underlying assumption that declares design intention correlates directly and obviously with the lived reality. Considering this historic shift in architectural theory, Boys (2011a) indicates that “new ideas about learning are still being translated into built form with little reference to the most developments in architectural theory” (p.28). The historic shift in architectural theory has been part of a wider paradigm shift from modernist thinking drawing on simple expressions of function, coherence, and order towards postmodernist concepts of hybridity and dynamism (Harvey, 1989; Jameson, 1992). Consequently, the contemporary understanding of space based on architectural theory has engaged with articulating relationships between space and occupants more as a dynamic interaction and less as a stimuli-response mechanism. In fact, the interaction between space and its occupants is a more complex and fluid than any cause-and-effect relationship. Boys (2011a) clarifies, moving away from modernist to postmodernist/post-structuralist assumption, space is understood as inherently performative and event-based not just a neutral container or setting into which we can pour behaviors. Thus, as space is seen as a relationship rather than just a setting, it can never exist in a meaningful way without the occupants, who inhabit it. This approach potentially can integrate with the contemporary theories of education —here, doctoral education— and inform the design of learning spaces. Intersection of architectural theories with re-conceptualization of doctoral education bundling as a social and spatial practice, which is open to transformation, enables us to build an integrated conceptual framework about spaces for learning in doctoral education. Obviously, the framework is not about developing a design guideline or offering any design solutions; it is more about finding the problems and 22 questions to ask within the complex relationship between space and the act of learning in this context, which can support and inform design of learning spaces in the future. 2.5 Connecting the Dots: Role of Design and Intentional Change to (Re)Imagine Learning Spaces 2.5.1 Why learning space? As mentioned before, doctoral education has been recently re-conceptualizing towards a learning process that can take place within different learning communities and learning spaces (Boyer, 1997; Porter & Phelps, 2 014; Shulman, 2004). Drawing on a cognitive apprenticeship model (Austin, 2009), learners can develop cognitive and meta-cognitive processes through observing how experts of their field understand and address a problem in a community of scholars since learning in doctorate level is situated and embodied in a variety of communities of practice. Students can be supported in their learning journeys within the communities and both conceptual and material space is implicated in the process. A learning space is an important element to support students’ learning experiences and to create a community of scholars in the context of doctoral education; it can be seen as the interaction between the occupants’ —doctoral students in this study— and social and individual practices within the provided spaces. If we view space in relation to its occupants and the socio-spatial practices take place in them, learning spaces will not be a matter of “aesthetics or innovative design” (Boddington & Boys, 2011, p.xiii) rather, they are about the processes of learning and the ways in which relationships between learning and space are connected. Boddington and Boys (2011) indicate that the design and development of learning spaces requires a relational understanding of individual and collective learning, within and beyond the physical boundaries and the role of different kinds of spaces (conceptual, personal, social, material, and digital) in this process. In addition, they remind us that learning space is the combination of the existing designed places, the socio-spatial practices occurring in them, the individual perceptions of both practices, and actual places alongside the institutional ideas within the changing landscape of higher education. 2.5.2 How Design can help re-negotiate learning spaces in the ever-changing times? Intention for change is the basic characteristic of design. The purpose of intentional change in design relates to the set of problems in our lives that require effective design 23 solutions. Rittel (1972) claims design problems have the nature of “wicked” rather than “tame”. Wicked problems are complex problems that are difficult to solve, and design tries to identify those problems and suggest novel solutions to them. Nelson and Stolterman )2014) explain that design starts with an ambiguous, complex, and integrated situation which they call it an analog reality. This situation ultimately ends up with the integration of innovative and analytical design into a reality which they call digital. Then, through a recursive approach, the digital needs to be transformed to analog. It means the outcome of each design continues to be experienced as a whole in the real world, evaluated, and redesigned if it is needed (the notion of reflection and iteration in design). As Latour (2004; 2008) argues, in the changing time that we are living through, where matters of fact reveal themselves as matters of concern, design plays a special role in helping us negotiate such matters. He terms design “a cautious Prometheus” a radically careful, and carefully radical, sensibility that brings to the task of making and re-making (Latour, 2008). Sherringham and Stewart (2011) confirm that changes and revolutions “de-naturalise previously unquestioned configurations of the world” (p.105); as a result, the robust orders of the world are newly revealed as “fragile constructions”. They argue, the re-negotiation of relationships within the emerging orders makes the previous orders fragile. Stakeholders struggle to conceive of how things could be done differently though identifying the existing arrangements’ failures. 2.5.2.1 Wicked problems in the throes of COVID-19 pandemic. The COVID-19 global pandemic in 2020 generated wicked problems in different contexts that were suddenly faced with potentially disastrous future. Cankurtaran and Beverland (2020) suggest wicked problems require tools that enable decision-makers to break out of preferred patterns of thinking. In a major conceptual review, Micheli et al. (2019) define the key attributes of design thinking as follows: creativity and innovation, user-centeredness and involvement, problem solving, iteration and experimentation, interdisciplinary collaboration, ability to visualize, reasoning, tolerance of ambiguity and failure, and blending analysis and intuition. Supported by using design thinking tools and methods such as brainstorming, prototyping and ethnographic methods, Beverland, Wilner, and Micheli (2015) state these attributes are believed to be especially valuable for addressing the type of wicked problems that COVID-19 has generated. The pandemic and the new ways of working, learning, and collaborating 24 has been an evolution that have emerged through shifting perspectives and enabling adaptability. While the last part of this study was conducted during the pandemic, further exploration on learning spaces in COVID and post-COVID times is beyond the scope of this study. A comprehensive set of answers as to how institutions should design physical and virtual learning spaces, digital tools and services, and the curricula to best prepare the graduates of the future has yet to appear from the literature. 2.5.3 Participatory design to view learning spaces as collective resources Participatory approaches in architecture and design emphasize the active participation of all the people who will ultimately benefit from the products of design. This approach is based on a contemporary shift in perspective at the collaborative domain of design and social science which Sanders (2013) calls it postdesign. It focuses on a co-design process, where people are invited to “play the game” through designing together and can provide a large set of ideas and opportunities. In fact, in this view, design is not seen as an essentially individual creative activity. Instead, it is being viewed, studied, and developed as a collective, collaborative, and even a community process. In this sense, Nelson and Stolterman (2014) introduce design as a form of democracy that embrace the diversity and complexity of human’s interests; it can be a democracy that provides possible solutions through which individual good can be considered within the common good. At a political and philosophical level, the roots of participatory design can be traced in postmodern tradition, phenomenology, Marxism, and feminist epistemologies (Frauenberger et al., 2015; Harrison, Sengers & Tatar, 2011). Participatory design originates in Scandinavian countries; from 1970s, a new design approach was developed based on the political claim for horizontality and participation (Muller, 2003) with the aim of understanding user’s needs. Interestingly, participatory design has rarely been used in developing learning spaces in higher educational setting. However, Sherringham and Stewart (2011) declare it has been used in developing educational environments typically in the context of school-based K-12 learning. There are a few participatory design tools specifically developed for higher education environments; for example, the Explore It Toolkit: Effective Spaces for Working in Higher Education (http://exploreacademicworkplace.com/) or the Learning Landscape project lead by Lincoln University partnering with design consultancy DEGW 25 (http://learninglandscapes.lincoln.ac.uk/). Drawing on the institution’s identity, aims, and values, these projects use evaluation, diagnostic, mapping, and charting tools to define shared parameters for expression and build models of learning and work as specific patterns of social and spatial organization. Implementing such approach in doctoral education requires developing models for enabling a collaborative and participatory process. At the same time, design education and learning how to think and act like a designer often is noted as a creative and innovative paradigm for contemporary learning (Boddington & Boys, 2011; Boys, 2009; Scheer, Noweski & Meinel, 2012). Design thinking is a set of mindset and techniques within a human-centered approach for conceptualizing and solving real-world and ill-defined problems in a creative way (Kelley & Kelley, 2013; Razzouk & Shute, 2012; Sanders, 2002). Design thinking naturally fits into the domains of design disciplines like architecture and industrial design, but it has the potential to add value to any process which requires creativity and innovation. Thus, it ties to the main aim of doctoral education and scholarly research (Rauth et al., 2010; Ulibarri et al, 2014) and its distinguished characteristics for the new age developing around multidisciplinary, collaborative work and self-reflective iteration. Design thinkers “have a methodology that enables us to come up with a design solution that nobody has before” (Tischler, 2009, p. 1); this is an essential ability for researchers who are producing original scholarship. Considering the potential values of design in education (Carroll et al., 2010; Kwek, 2011; Noweski et al., 2012), it can throw light on other disciplines because it emphasizes creativity (Anders, Elvidge, & Walsh, 2009; Ulibarri et al., 2014), which is considered of value in conducting innovative research. To address the philosophical frameworks that underpin the study, in the following sections, I explain the involving theories in this study based on Design-Based Research (DBR) approach, a research methodology upon which this study has been designed and developed. 2.6 Theoretical Framework This study draws on a Design-Based Research (DBR) approach, which will be explained in detail in Chapter 3. DBR has a pragmatic desire to create forms of learning practices and environments based on the related theories. The aim is to refine and improve the learning practices and environments in iterative cycles of design. Thus, DBR is theory-26 oriented and should be grounded in the relevant “research, theory and practice” (Wang & Hannafin, 2005). Identifying the philosophical theories through which the design can be developed and analyzed is important in DBR. However, the philosophical theories usually do not provide concrete indications to designing and implementing the practices. In fact, the critical question in using the philosophical theories is how the designer/researcher can put those kinds of theories in practice. diSessa (1991) argues that rather than fundamental theories, design experiments need intermediate theoretical scopes, because the philosophical theories might be difficult to project into specific realistic situations. To explain the involving theories that frame this study and their interconnection, first, I illustrate the scope of the framework and the concept of third space to develop a conceptual framework for this study. Then, drawing on a DBR approach, I explain the underlying philosophical theories within the domain of architecture (Lefebvre’s Production of Space, 1991) and education (Situated Learning – Lave & Wenger, 1991), and participatory design as a theory for action within the domain of design. 2.6.1 Scope of the framework: creating third space Learning spaces can be seen from different perspectives (Beatty, 2016; Bond & Goodchild, 2012; Elmborg, 2011; Long & Ehrmann, 2005; Parisio, 2013; Radcliffe, Wilson, Powell & Tibbetts, 2009; Savin-Baden, 2007; Scott-Webber, 2004). In this study, the research questions and accordingly the review of the literature facilitated determining the scope of the underpinning theoretical frameworks in this study. This study draws on the intersection of theories of space in architecture along with educational theories related to doctoral education hence, it has necessitated creating an “in-between” (Bhabha, 2012) conceptual framework, which enables sharing attributes of both fields. The conceptual framework of this study has been developed based on a recent work in cultural theory, which suggests that an in-between region or a third space (liminal space) can act as a fertile environment, where diverse knowledge and perspectives can be combined into new insights or/and plans for action (Bhabha, 2012). Creating such a third space and a more explicit conceptual framework for thinking about learning spaces can help better articulate the definition of space and explore the relationship between learning spaces and students’ learning experiences in doctoral education setting. Drawing from Bhabha’s (2012) argument, the developed theoretical framework initially appears to be a matter of moving across the 27 boundaries of education and design, rather than living within the boundaries. Incorporating a theory for action has made the integrated framework into a movable third space towards action. Such a framework enabled me to examine the active engagement of the learners in the process of designing/re-designing learning spaces within a participatory and human-centered approach. Figure 2.1 illustrates a schematic overview of different theories contributing to the structure of this study and their interconnection. Figure 2.1 Conceptual framework to study learning spaces in doctoral education 2.6.2 Complexity and ambiguity of space: framing learning spaces within Lefebvre’s Production of Space In the context of learning spaces, there is a considerable slippage in the use of terms between conceptual/imaginary space, institutional spaces (whether digital or physical), and personal and public realm. Sellers and Souter (2012) explain, Lefebvre’s explorations of space help us understand the complexity and ambiguity of space and why/how explore spaces affect and are affected by humans and the society through the interplay of these spaces. Articulating learning in a spatial context, this study is framed within the discourses of Lefebvre’s production of space (Lefebvre, 1991), where he proposes a spatial triad as a 28 means to conceptualizing the relationships between a space and its inhabitants; Lefebvre’s spatial triad includes: 1. Spatial practices or the perceived space: the ordinary, unconsidered experiences of everyday lives within a space; space as reproduced in everyday life or space as perceived through our senses; 2. Representations of space or the conceived space: the conceptualized space by planners which attempt to describe patterning of the social in space; space as developed cognitively; and 3. Representational space or the lived space: the space of the inhabitants and users that can be altered by ordinary people through their imagination towards transforming the space; complex ideational space. Lefebvre (1991) sees the societal production of space as a dialectical interaction between these three factors: physical, mental, and social space. He argues that “producers of space have always acted in accordance with a representation, [a theory]”, while the users of a space “passively experienced whatever was imposed upon them” (p. 43). One of the radical aims of Lefebvre’s theory is to see if it is possible for spaces to be “decoded” by their users and “read”. Lefebvre rejects space as an empty container and argues that “space does not exist in any such absolute, a priori form; it is not something that human activity fills up, but rather something that human activity produces” (Cohen 2007, p. 232). Lefebvre’s spatial triad provides a very helpful model to help us think through the complexity of how a space is produced and overcome binary thinking about space. As Nunes (2006) clarifies, based on Lefebvre’s model, “space is produced by and productive of a dynamic interplay of material, conceptual, and experiential processes.” (xxi). In other words, space is produced at the nexus where form, concept and practice intersect (Prey, 2015). As Sellers and Souter (2012) note, Lefebvre (1991) tries to understand a science of space through incorporating political (social), ideological (mental), and technological (physical) attributes towards a “unitary theory” (p. 11). Deleuze and Guattari’s (1988) ideas act as complement to Lefebvre’s theory by introducing various figurations of space such as striations and smoothness that have opened understandings about interactions in the space. Savin-Baden (2007) explains for Deleuze and Guattari (1988), the notion of smooth space focuses on becoming; it is a nomadic space where the movement is more important than the 29 arrival, whereas in a striated space, the focal point is one of arrival: “[i]n striated space, lines or trajectories tend to be subordinated to points: one goes from one point to another. In the smooth, it is the opposite: the points are subordinated to the trajectory” (Deleuze & Guattari, 1988, p. 478). The concepts of striations and smoothness do not mean to indicate an oppositional binary where one state is completely unlike the other. Rather, they emphasize a complex interrelationship between differences. Striated spaces are highly regulated and externally organized, while smooth spaces are available for free configuration. Acknowledging that both fluids and solids spaces can demonstrate smooth space within striated space, and vice versa, Sellers and Souter (2012) transfer these concepts into teaching and learning context; they explain, “active learning can be coextensive with the didactic paradigm, as can private spaces within the classroom…. the didactic acknowledges question/conversation/discussion and the classroom includes cafe/cushions and booths” (p.27). Framing the learning spaces within Lefebvre’s theory of space, a learning space cannot be seen as a container, where we can pour behaviors through a cause and effort relationship; instead, it can be perceived as fluid and event-based phenomena. In addition, based on learning sciences (Cormier, 2008), guided by post-structural thinking about education, learning is a complex process of sense-making to which each learner brings their own context and has their own needs; learning is not only designed around the content but is instead a social process where we learn with and from each other without considering pre-set limits and outcomes. Learning space, then, is not so much about providing design solutions as enabling the optimal conditions for learning (Boddington & Boys, 2011). What is presumably to be understood here is that designers of learning spaces may aim to reflect their own understandings of a space’s purpose in its apparent form. This form is then interpreted by observers and users of the spaces based on their own understandings, or through their skills in decoding the socially constructed meaning; the piece that is usually missing or less considered in developing learning spaces. Figures 2.2 and 2.3 respectively illustrate a schematic overview of Lefebvre’s (1991) spatial triad and its relationship with the research questions of this study. 30 Figure 2.2 Lefebvre’s (1991) spatial triad — Production of space Figure 2.3 Adapting Lefebvre’s (1991) production of space and research questions — Production of learning space Boys (2011a) suggests adaptation of Lefebvre’s theory could be beneficial when we are looking at something of experiences of students within the learning spaces, whereas Temple (2007) argues there is not any example of Lefebvre’s ideas being translated into practical applications of space design, specifically learning spaces. He mentions that there are 31 studies that question the users of buildings on how their surroundings affect them by applying some of Lefebvre’s theorizing. While space is an ambiguous and complicated notion, with the recent spatial turn in cultural theory (Deleuze & Guattari, 1988), it is increasingly used as a means to explore or communicate the ideas, what Boddington and Boys (2011) have called socio-spatial conceptualizations of learning. This approach to learning space is opening up debates in a potentially enlightening way if we are clear about how such spatial conceptualizations of learning connect with either actual material spaces, and individual and group embodied perceptions and experiences. As a result, creating learning spaces through intentional change and design (Nelson & Stolterman, 2014) requires detailed understanding of the contextual space and its occupants’ perceptions and experiences through an empathetic approach. 2.6.3 Situatedness and complexity of learning: framing learning spaces within Situated Learning theory Situated Learning theory and the concept of community of practice (Lave & Wenger 1991) have being applied to re-conceptualize doctoral education (Flores & Nerad, 2012; Nerad, 2012; McAlpine & Norton, 2006; Walker et al., 2009). Focusing on transformation of doctoral education, Nerad (2012) suggests Situated Learning theory can widen our perspective and help us better understand learning as a function of the activity, context, and culture in which learning is situated. Situated Learning theory (Lave & Wenger, 1991) draws on Vygotsky’s (1980) theory of social cognition and conceptualizes social knowledge and could have an important contribution to the learning space concept. It conceives learning as a transaction between a person and the social environment, and it can contribute strongly to support learning space research. A learning space based on Situated Learning theory may include the physical spaces, but it is not necessarily limited to physical places; instead, it constructs of the person’s experience in the social environment (Kolb & Kolb, 2005). These experiences are embedded in the communities of practice that have a “history, norms, tools, and traditions of practice” (p. 200). From this point of view, knowledge is created in the communities of practice and thus learning is a process of becoming a member of a community of practice through a legitimate peripheral participation (e.g., apprenticeship) (Lave & Wenger, 1991). Austin (2009) clarifies Situated Learning theory emphasizes that learning can be improved 32 when students make their learning meaningful to themselves and when they are supported in their learning through being part of a community of practice. Experiencing Situated Learning in a community of scholars ties also to the cognitive apprenticeship model in the context of doctoral education aiming at educating the independent researchers for the twenty-first century, who are capable of producing original research creatively and independently. Austin (2009) clarifies learning through cognitive apprenticeship can be enhanced through “participation in a community of scholars and by experiencing Situated Learning” (p. 179). Communities of scholars are seen as a number of relationships that might result from tracking the shared scholarly interests (Lahenius, 2012). In such a context, learning should be supported as a process that can take place within a series of learning environments. Situated Learning theory enriches the learning space concept in doctoral education context by reminding us that learning spaces include socialization into a wider community of practice that involving “membership, identity formation, transitioning from novice to expert through mentorship, and experience in the activities of the practice”, as well as “the reproduction and development of the community of practice itself as newcomers replace old-timers” (Kolb & Kolb, 2005, p. 200). Considering that doctoral experience is influenced by the social practices of the scholarly communities, learning space can be seen as a socially constructed and a collective resource, which aligns with Lefebvre’s (1991) conceptualization of space (explained previously). Participatory design takes Lefebvre’s theory and Situated Learning, as philosophical theories upon which this study was developed, a step further toward action. Drawing from a DBR approach, I address it as the intermediate scope of theory, and I explain it below. 2.6.4 Process to re-creating the learning spaces: [participatory] design Learning in doctoral education is experiencing revolutionary change (Flores & Nerad, 2012; Nerad, 2012; McAlpine & Norton, 2006; Walker et al., 2009). Sherringham and Stewart (2011) claim this revolutionary change is taking place within the significant changes in higher education context driven by new digital technologies alongside the new conceptions about learning, which have posed challenges to both institutional ideas about the nature of learning, and learners’ assumptions about the authority and role of learning institutions. Meanwhile, Burrowes (2001) describes this change in higher education “as dramatic and 33 significant as the scientific and industrial revolutions of the eighteenth and nineteenth centuries” (p. 105). Latour (2004; 2008) declares that in these changing times, “the artefacts or spaces that seem solid disclose themselves as contradictory issues” (p. 4); in this context, he argues, matters of fact reveal themselves to be matters of concern and design plays an important role to help us cautiously negotiate such matters. To Latour (2004), design in twenty-first century belongs more to the context of collaborative and participatory design than to the heroic stances of design in the twentieth century (Fry, 2002; Loewy, 1950, 2007), where designers position themselves as celebrities. Participatory design developed since the 1990s, (Blomberg & Kensing, 1998; Muller, 1991, 2003; Sanders,1993; Schuler & Namioka, 1993) is suggesting a way to actively involve all stakeholders in the design process to ensure the product of design meet their needs. Through participatory process stakeholders are invited “to play, to spin webs of meaning, of action, of affectation, and of embodied knowing” (Sherringham & Stewart, 2011, p.112). The creative processes of participatory design engage stakeholders in design through framing and re-framing perspectives and understandings and co-generating a design relevant to them and to the educational requirements of the contemporary education when we frame it in the learning space context. Participatory form of design in the context of learning spaces can create opportunities for learning by doing through making and interpretation, which combines verbal and non-verbal communication. Boys (2011a) believes learning by designing can offer the potential for richer forms of describing and analyzing learning spaces. Development of innovative and appropriate design tools/models/processes within doctoral education contexts could be beneficial not just for learning space design scenarios but can be typical for any complex setting where change is being collaboratively negotiated. Participatory design has been developed as a strategy over the past two decades to address the needs of such settings. Sherringham and Stewart (2011) suggest that a playful, visual stimuli, and guiding framework for engagement would enable communication to hear different voices and inform the future of learning space design. As an exploratory process, applying participatory design in learning spaces enables creative and imaginative engagements with new learning scenarios. Sherringham and Stewart (2011) confirm in such exploratory process, a rich 34 tapestry of socially constructed information is developed for the designer to interpret and translate. 2.6.4.1 Making/prototyping to explore the future possibilities. Sanders and Stappers (2014) report a rapid adoption of methods of doing research into design processes. In their research (Sanders & Stappers, 2008), reviewing the emerging landscape of design research and practice, they note that a wide spectrum of approaches has been emerging on the “roles of users (sometime the objects of study and at other times becoming active co-designers)”, as well as the “types of research methods involved (ranging from traditional scientific to designerly)” (p.5). Integrating the designerly ways of doing research is that they involve creative acts of making. Supporting this idea, Sanders and Stappers (2014) explain in the process of making, designers/researchers create probe packages and toolkits while respondents create interpretations of ambiguous questions and through making expressive artefacts and discussing those. In this context, making is not “just a performative act of reproduction, but a creative act which involves construction and transformation of meaning” (p.6). Making or prototyping activities can help make sense of the future. In other words, Sanders and Stappers (2014) explicate, they can be used as vehicles to explore the future ways of living. Brandt, Binder, and Sanders (2012) remark “making of things as a means of design participation” (p.155) explaining when we make something in the form of artefacts, we use our hands for externalizing and embodying; such artefacts might describe future objects or provide views on future ways of living. Sanders (2000) also advises that making artefacts should be used together with other methods in a converging approach that “draws simultaneously from marketing research ('what people say'), applied anthropology ('what people do') and participatory design ('what people make')” (p. 7). Participatory prototyping, generative tools, and probes have evolved as three distinct (yet are not mutually exclusive) approaches for making over time (Brandt, Binder, & Sanders, 2012). Participatory prototyping with the longest history was introduced in the early 1980s (e.g., Bødker et al. 1987; Ehn 1988). Generative tools and probes were introduced in the same year (Gaver, Dunne & Pacenti, 1999; Sanders 1999). Participatory prototyping using mock-ups often are used in the early stages of the established design process in order to help us make sense of the future and collectively explore the future ways of living. 35 Generative tools are used to help non-designers imagine and express their own ideas about how they want to live, work, and play in the future (Sanders & Stappers, 2008). Gaver, Dunne & Pacenti (1999) describe probes as a design-led approach that invite people to reflect on their experiences and attitudes that provide inspiration for designers. Sanders and Stappers (2014) clarify “probes originated in the design-led and expert-driven corner of the map whereas generative toolkits originated in the design-led and participatory corner of the map” (p. 7). 2.6.4.2 Designing a generative toolkit drawing on participatory and human-centered approach to design. Kemmis, McTaggert, and Nixon (2013) declare participatory methodologies are particularly beneficial in the contexts where significant power differences exist. Power differences in designing learning spaces can be the case in higher education settings where space is considered in strategic planning with dominantly concern of space utilization and financial effectiveness by institutions (Avery, 1994; HEFCE, 2000). In the recent decades, the organizational nature of higher education has been changing through taking into consideration the relations with students, research relating to how students learn, and factors influencing the learning process. Yet, as Temple and Fillippakou (2007) report, there has been relatively little consideration of the ways in which space is seen as a site of learning. They acknowledge universities seem to put little attention into understandings and functions of space in relation to students’ learning; the control of space and the way in which it is valued and represented basically takes place through organizational practices. Savin-Baden (2007) confirms this approach tends to believe the way that university learning spaces should shape student learning. It also appears to contradict the very nature of space itself, as Lefebvre argues: “(social) space is a (social) product” (Lefebvre, 1991, p.324) or a complex social construction based on values, and the social production of meanings which affects spatial practices and perceptions. Drawing on this view, space is a tool of thought and of action. Lefebvre (1991) believes “in addition that it is a means of production, it can also be a means of control, and hence domination, of power; yet that as such escapes in part from those who would make use of it” (p. 26). This study aimed at developing a theory of action using a combination of generative toolkits (Brandt, Binder, & Sanders, 2012; Sanders & Stappers, 2014) within the domain of participatory design with human-centered design, which “helps us keep people—not the 36 latest technology—in the forefront of design decisions” (Brown & Long, 2006, p. 10). Developing such framework within a participatory and human-centered process using design thinking strategy can engage students and encourage them in open-ended exploration of innovative possibilities –in this case, for future of learning spaces for doctoral students. Design thinking is a set of mindset and techniques within a human-centered approach for conceptualizing and solving real-world and ill-defined problems in a creative way (Kelley & Kelley, 2013; Razzouk & Shute, 2012; Sanders, 2002). The human-centered focus of design (thinking) and the collaborations that define the process provide a deeply social process for learning and addressing the problems. It encompasses active problem finding and problem solving by engaging with (Dewey, 1916), and changing the world. 37 Chapter 3: Methodology and Research Design 3.1 Overview of Chapter 3 In Chapter 3, I present the research questions for this study, explain Design-Based Research (DBR) as the underpinning research methodology, and provide the rationale for the study design as well as the approach to the implementation of the design. A secondary aim is to explain how DBR is interrelated with the tenets of the study as well as the research questions. In this chapter, I also provide an explanation of the relationship between DBR and participatory design to develop domain theory and design methodology. Then, I describe the procedures of collecting and analyzing data within the framework of the methodology. At the end of the chapter, I address ethics management and trustworthiness that I considered in conducting this research. I close the chapter with explaining my role as a researcher. The research methodology provides a process through which perceptions, experiences, and imaginations of doctoral students at UBC Okanagan in relation to their learning spaces are examined; it also creates an avenue where students can address the problems and formulate new visions for the future in a participatory manner, which can lead to more understanding and ultimately to change in UBC Okanagan’s future strategies in relation to those spaces. Research methodology is derived from the theoretical framework of the study as well as the specific research questions that this study sought to address. Focusing on the research design, this chapter also addresses ethical considerations and study limitations in each phase, which are standard elements of a research study design (Creswell, 2007). The use of visuals incorporated in this chapter (and other chapters) were used to allow for a better understanding and facilitate capturing the complexities. Jongeward (2009) confirms visual images in qualitative research can be used “as a vehicle for discovering and communicating meanings that emerge in the research process” (p. 240). Knowles and Cole (2008) even go deeper in arts-informed research and believe using visuals in qualitative scholarly work provides a context for promoting innovative research and advancing 38 knowledge. Creating the visuals also helped me to conceptualize my thoughts and better understand the abstract concepts. 3.2 Research Questions and An Overview of the Research The research questions of this study reflect both theoretical and practical aims, which were refined through the conduct of the study. The iterative development of the research questions aligns with a qualitative approach to research design (Creswell, 2007, p. 43) and Design-Based Research framework (Joseph, 2004). The intention of the questions was twofold. The first aim was to unravel what matters about learning space in graduate programs and its relationship with learning and research practices from doctoral students’ perspectives. The second aim was to create a case for a participatory design process, where students, who identified that area of the issue(s) in their learning spaces, can imagine possible design solutions to meet their needs. This study addresses and answers the following research questions: 1. How do doctoral students perceive a “learning space” and its intended use(s)? 2. What is the relationship, if any, between the university provided learning spaces and students’ identified spaces? 3. How might doctoral students envision the future of their learning spaces? To answer the research questions, I developed a multi-phased research through three sequential phases, and accordingly, I used different methods of data collection and analysis for each phase. Data from the questionnaires addresses subjective aspect of learning spaces (first question), Photovoice plus semi-structured interviews address objective aspect of learning spaces (second question), and participatory prototyping informs co-constructed aspect of learning space (third question). Table 3.1 summarizes the data sources as well as the collection and analysis methods related to each phase of the study and the research question. I will elaborate each phase in relation to its data collection method and the analysis strategy subsequently. Doctoral students and alumni from UBC Okanagan participated in this research. Thirty-eight individuals accepted the recruitment invitation and participated in the first phase. Participants of the second and third phase, eleven and twelve people, respectively, were emanated from the original thirty-eight. In Section 3.13.1, the recruitment process will be explained. Also, participants of each phase will be presented in Sections 3.10.2, 3.11.2, and 39 3.12.2. Table 3.2 shows a demographic of participants in three phases of the study, which I will cite them throughout the analysis process. The abbreviations used in the tables have been listed in the List of Abbreviations at the very beginning of this dissertation. Table 3.1 Summary of research questions and methods of data collection and analysis Phase Research Question Data Collection Method Analysis Method General Strategy Complimentary Strategy One How do doctoral students perceive a “learning space” and its intended use(s)? Questionnaire Reflexive Thematic Analysis (Inductive & deductive) Reflexive iteration Axial coding Two What is the relationship, if any, between the university’s provided learning spaces and students’ identified spaces? Photovoice Semi-structured interviews Reflexive Thematic Analysis (Deductive, latent & inductive) Reflexive iteration Axial coding Art-informed approach Three How might doctoral students envision the future of their learning spaces? Participatory Prototyping Notes, Sketches, Prototypes Reflexive Thematic Analysis (Latent, & inductive) Reflexive iteration Art-informed approach A combination of interconnected strategies for analyzing the data was applied in this study. While Thematic Analysis (TA) (Boyatzis, 1998; Roulston, 2001; Braun & Clarke, 2006), as the general method, informed the data analysis process at all stages, complimentary strategies were integrated to each phase when needed (see Table 3.1). The benefits of using such an eclectic approach included cross-disciplinary non-linear investigation, creating a complete picture of participants’ knowledge obtained in different levels, enhancement of trustworthiness and rigor, and building a creative medium to interpret the data. In the 40 following sections, I elaborate on data collection and analysis procedures after I explain DBR as the underpinning methodology of this study and its interconnectedness to this study. Table 3.2 Demographic of participants First phase: 38 participants (P1-P38) Second phase: 11 participants (P1-P11) Third phase: 12 participants (P1-P12) Age No Participant Description Participant Description 25-34 18 P1 25-34, 1st year, Electrical Engineering, SOE International, no office P1 25-34, 1st year, Electrical Engineering, SOE International, no office 35-44 12 45-54 5 55-64 3 Program P2 25-34, 1st year, IGS, FCCS, International, no office P2 25-34, 1st year, IGS, FCCS, International, no office Engineering 10 IGS 18 Communications 4 Chemistry 1 P 3 55-64, +4th year, IGS, OSE, Domestic, with office P3 55-64, +4th year, IGS, OSE, Domestic, with office Psychology 2 Health and exercise sciences 1 Philosophy 1 Biology 1 P4 35-44, 3rd year, IGS, FCCS, International, with office P4 35-44, 3rd year, IGS, FCCS, International, with office Stage No First year 8 Second year 18 Third year 4 Fourth year 6 P5 25-34, +4th year, Civil Engineering, SOE International, with office P5 25-34, +4th year, Civil Engineering, SOE International, with office More 6 Graduated 4 41 Table 3.2 (Cont.) Demographic of participants First phase: 38 participants (P1-P38) Second phase: 11 participants (P1-P11) Third phase: 12 participants (P1-P12) Participant Description Participant Description Student Status P6 35-44, 3rd year, Psychology, IKBSAS, Domestic, with office P6 35-44, 3rd year, Psychology, IKBSAS, Domestic, with office International 18 Domestic 20 Department SOE 10 P7 45-54, 2nd year, IGS (Communications), FCCS, Domestic, no office P7 45-54, 2nd year, IGS (Communications), FCCS, Domestic, no office FCCS 15 FHSD 3 OSE 6 IKBSAS 4 P8 35-44, Graduated, IGS, FCCS, International, no office P8 35-44, Graduated, IGS, FCCS, International, no office If provided with a space YES 21 NO 13 P9 35-44, Graduated, Mechanical Engineering, SOE, International, with office P9 35-44, Graduated, Mechanical Engineering, SOE, International, with office P10 35-44, 2nd, IGS, IKBSAS International, with office P10 35-44, 2nd, IGS, IKBSAS International, with office P11 55-64, 3rd year, IGS, OSE, Domestic, with office P11 55-64, 3rd year, IGS, OSE, Domestic, with office P12 25-34, Graduated, Civil Engineering, SOE, International, with office 42 3.3 Design-Based Research (DBR) Methodology and the Tenets of the Study This study was conducted within the framework of Design-Based Research (DBR). DBR seeks to increase the impact of education research into further and better practice through generating “new theories, artifacts, and practices” (Barab & Squire, 2004, p.2), in iterative cycles of designing, evaluating, and re-designing. DBR is grounded in the mindset and act of designing and includes aspects of design domain. It has roots in educational technology research, and it is also related to practice and research of engineering and architecture/design. In fact, it is involved with finding a design problem and offering design solutions through a flexible and iterative process. Edelson (2002) clarifies that DBR is the combination of theory development, design process, and the design solution. The cycles of analysis, design, evaluation, and revision are iterated until “a satisfying balance between ideals and realization has been achieved” (Plomp, 2007, p.13). The first question in this research study was how doctoral students perceive a “learning space” and its intended uses, and the second question explored the relationship between the university’s provided learning spaces and students’ identified spaces. These two phases helped identifying the area of the problem in relation to learning spaces and formed a pre-design research (Sanders & Stappers, 2014) while a constant literature review was conducted throughout the process. Being guided by the pre-design research, the third research question, which had a pragmatic orientation, explored how doctoral students might envision the future of their learning spaces. The iterative cycle of analysis in the pre-design research explored the stories, perceptions, and experiences of doctoral students in relation to their learning spaces while the prototypes in the next phase were the physical embodiments of the desired experiences. Analysis of participatory prototyping activities that took place later explored the artifact(s) in relation to the stories. The evaluation of the whole process took place at the end of the study; Sanders and Stappers (2014) call this stage post-design research, which may lead to revision. Although the DBR approach addresses a variety of educational problems in different settings, it contains distinctive qualities that can be found in a variety of situations. Wang and Hannafin (2005) assign the basic characteristics of DBR as: pragmatic, grounded, interactive, 43 iterative and flexible, integrative, and contextual. The distinctive attributes of DBR are interrelated with the tenets of this study as follows: 3.3.1. Having a pragmatic stand DBR takes a pragmatic stance (Barab & Squire, 2004; Juuti & Lavonen, 2006) and aims to link the gap between educational research and practice by providing new possibilities in learning environments. It incorporates an educational artifact, which is grounded in relevant theories, research, and practice, and tries to refine both theory and practice continuously (Cobb et al., 2003). Deriving from an integrated theoretical and methodological framework to link education and design, a participatory model for doctoral education’s learning spaces has been developed in this study. Development of the theory and practice has been on an ongoing pragmatic basis to explore how learning spaces are understood, experienced, and envisioned as a whole. The implicit epistemological assumption in this context draws on the view that one can know about the reality (in this case learning spaces), the problem(s), and the possible design solution(s) by experimenting in real settings. Schuh and Barab (2008) clarify this view, suggesting that knowledge can be derived from interaction among people and the artifacts in their environment; together they create a reality. 3.3.2. Grounding in theory and real practice DBR is grounded in theories as well as real-world educational contexts (Brown & Campione, 1996; Wang & Hannafin, 2005). This study has been grounded in lived experiences of doctoral students’ experiences and practices framed by the relevant theories in doctoral education and architecture (explained in theoretical framework of the study). Developing an integrated theoretical framework, learning space has been seen from both architectural and educational angles regarding the related theories and practices. This study opened up and synthesized two different yet related perspectives to view learning spaces in doctoral education context; the integrated theory-driven perspective guided the study through a process/model, which was participatory, pragmatic, and learner-centered. 3.3.3. Conducting iterative and flexible process DBR is an interactive process in which researchers/designers are working in collaboration with the practitioners. They work together to identify problems, give possible design solutions, and improve the existing principles through iterative cycles of design, implementation, analysis, and re-design (Design-Based Research Collective, 2003). In this 44 study, data was collected through sequential phases based on the needs of study, questionnaire to address subjective aspect, Photovoice and plus semi-structured interviews to address objective aspect, and participatory prototyping to address co-constructed aspect of learning spaces. The data analysis was conducted through an iterative cycle; coding and re-coding of data have been done according to the information interpreted and the themes that emerged from the data. Analysis of data in each phase guided the study the next phase. Also, data analysis was conducted through a retrospective and cross-iteration approach. This study follows a flexible research strategy and multiple methods have been used for collecting data as new needs emerged. The recursive movement that ensued within the design process allowed flexibility; moving from analysis-to-design-to-reflection-and-re-design created room for continual refinement. Iterative and flexible structure allowed interaction and deliberation (Design-Based Research Collective, 2003). 3.3.4 Using multiple perspectives to ensure integration of data sources In DBR approach, multiple perspectives ensure integration of data sources, methods of data collection, and analysis of the procedures, which are interdependent with the needs (Wang & Hannafin, 2005). I developed a multi-phased research through three sequential phases and accordingly, I used different methods of data collection and analysis for each phase (see Table 3.1). The collected data from the questionnaires, Photovoice, and participatory prototyping addressed subjective, objective, and co-constructed aspect of learning space, respectively. 3.3.5 Connecting to the context Drawing from DBR approach, research findings and results relate to the research context, and with the design process through which findings are generated (Design-Based Research Collective, 2003; van den Akker, 1999; Wang & Hannafin, 2005). Therefore, documentation of the design process and reflection upon it play an important role in providing evidence, claims, and guidance for researchers in order to develop new cycles of design. This study is situated at the University of British Columbia’s Okanagan campus, a relatively new, and somewhat independent campus within the UBC system. Moreover, this research proceeded from the view that space is seen as socially constructed (Lefebvre, 1991). It intended to systematically document, reflect on, and evaluate UBC Okanagan’s learning spaces in relation to doctoral students’ perceptions, experiences, and imaginations of the 45 spaces and the influence of the provided spaces on their learning and research-related activities. Findings from this study identify areas for the future studies and actions to be taken by UBC and suggest implications for learning space studies for the U15 (Group of Canadian Research Universities) and U21 (the leading global network of research universities for the 21st century) in which UBC is a member. It is important to note that findings cannot be generalized; they must be tested through iterations in a second, third or more cases with the purpose that the same results should occur (Yin, 2003). Findings from this study can be also examined and adapted to other contexts for their own purposes. 3.4 Design-Based Research and its Interrelationship to the Research Questions Design-Based Research is conducted in iterative cycles of designing and refinement. Thus, conducting a systematic documentation and reflection upon design in each cycle is necessary to improve the design. Plomp (2007) believes the twofold product of DBR includes “research-based interventions as well as knowledge about them” (p.13). As a result, systematic reflection and documentation as the continuous activities should take place during the cycles of DBR. Based on the DBR literature, Plomp (2007) concludes that DBR experiences is comprised of the following three stages: Preliminary research: includes needs and context analysis, literature review, and development of a theoretical framework for the study; Prototyping phase: includes iterative design phase, each being a micro-cycle of research with formative evaluation intends to improve and refine the intervention; and, Assessment phase: includes evaluation to conclude whether the solution or intervention meets the pre-determined characteristics. Linking the three stages by Plomp (2007) to the first and second research questions, exploring students’ perceptions about learning spaces and the influence on their learning along with the reviewing of the related literature fit in the preliminary research stage; this stage also can be addressed as pre-design (Sanders & Stappers, 2014) or pre-intervention research in DBR. This stage ended up with identifying the problem(s) in relation to learning space and refining the research questions. Based on the findings from the first stage and the emerging identified problem(s) drawing on students’ experiences within the learning spaces, the third research question explores the lessons that can be learned from a participatory prototyping involving doctoral 46 students of UBC Okanagan; the participatory process within the micro-cycle of design of this study connected to intervention research in DBR. This stage of the study corresponded to the prototyping phase in Plomp’s (2007) identified stages and aimed at designing and developing a participatory design process to envision doctoral education’s learning spaces. Finally, exploring students’ experiences after the process fits in the assessment phase (Plomp, 2007). The assessment phase included the post-intervention research, which was a (semi-) summative evaluation to “conclude whether the intervention meets the predetermined specification” (P.15). Findings from this stage addressed students’ and researcher’s learning of the participatory prototyping process and helped generate design principles for the future iterations. Figure 3.1 illustrates a schematic overview of Plomp’s (2007) stages of DBR and their linkages to the research questions in this study. Figure 3.1 DBR stages by Plomp (2007) and their interrelationship to the research questions 47 3.5 DBR and Participatory Design to Develop Domain Theories and Design Methodology DBR offers opportunities for development of theories through constructing problem analyses, design procedures, and design solutions to develop useful theories. Edelson (2002) calls these theories respectively domain theories, design methodology, and design frameworks. This study supported the development of domain theory and design methodology. As Edelson (2002) clarifies, a domain theory might be about learning environments and how they influence teaching and learning. The aim of the first and second phase in this study was to address subjective and objective aspects of learning spaces through exploring how students have perceived, identified, and experienced a “learning space” and the relationship between the university’s provided spaces and students’ identified learning spaces. The first phase corresponds with perceived space identified in Lefebvre’s (1991) spatial triad, which includes the ordinary and unconsidered experiences of everyday lives within a space. On the other hand, the second question investigated the conceived space (Lefebvre’s, 1991), which is the conceptualized space by planners to pattern the social in space and the way people interact with the space. The domain theory emerged from these phases included a descriptive analysis of the area of the problem. Edelson (2002) confirms that a domain theory is descriptive, not prescriptive. The problem analysis must characterize, not just the challenges, but also the outcomes of implementing the design. Thus, the domain theory characterizes a set of outcomes associated with some intervention. Emphasizing understanding of the desired outcomes, Edelson (2002) suggests developing a process that can make the design happen is essential. Therefore, the problem analysis must characterize the desired outcomes and the ways to achieve them. The aim of the third phase, participatory prototyping, was to address the co-constructed aspect of learning spaces as the desired outcome of problem analysis. The third phase also aligns with Lefebvre’s (1991) lived space or complex ideational space which is the space of the inhabitants that can be altered through their imagination towards transformation. Participatory prototyping was applied as the orienting theoretical framework in this study; developing a design process guided by the findings from the first and second phases supported the development of theoretical assertions about using a participatory approach in 48 learning spaces design as well as theoretical assertions about if the process supports learning in doctoral education. Within the discipline of design, participatory design offers promise for the learning sciences because of its aligned goals for engaging in the real-world situations as well as its democratic values (DiSalvo & DiSalvo, 2014). DBR ties to the diverse continuum of participatory research methodologies which are informed by a theory of knowledge. The theory holds the emerging meaning through the co-participation of researchers and participants in social and cultural contexts. Participatory design and inviting participants to contribute to the designing and making process in educational setting is seen as a concrete example of DBR within its diverse continuum, which is the focus of this study. According to Edelson (2002), a design methodology is a design procedure, which provides guidelines for the process rather than the product. The procedure developed in this study included the pre-design, design, and post-design stages and aimed to address subjective, objective, and co-constructed aspects of learning spaces in doctoral education. The purpose was to reach areas connected to understandings, experiences, and imaginations of doctoral students about learning spaces. The design procedure drew on the concept of different degrees of users’ knowledge in Design Research Methods including what people say, what people do, and what people make (Sawhney, Prandelli & Verona, 2003), which correspond respectively to explicit, tacit (observable), and latent knowledge (Figures 3.3 & 3.4). In the succeeding sections, I will elaborate the design process developed based on this concept of Design Research Methods. Figure 3.2 illustrates the development of design adapting a diagram by Reeves (2006), which demonstrates the iterative development of the process within a DBR approach. Figure 3.2 also summarizes how implementing pre-design, design, and post-design explorations lead to development of domain theory and design methodology. The pre-design stage identifies the area of the problem through exploring the first and second research questions and addresses the perceived and conceived spaces in Lefebvre’s (1991) spatial triad. The design stage characterizes a set of intervention, as the desired outcome through prototyping process, and addresses lived space (Lefebvre’s, 1991). These stages along with documentation, reflection, and evaluation of the process along the way and at the end of the process, created a complete picture of the spatial triad (Lefebvre’s 1991) and provided 49 guidelines for the process of a participatory approach to learning space in doctoral education context. Figure 3.2 DBR and participatory design to develop domain theories and design methodology 3.6 Research Design within a DBR Framework Wang and Hannafin (2005) state that methods of data collection and analysis of the procedures in a DBR approach are interdependent with the needs of research design. Drawing on this approach, the development of the design and selection of data collection methods as well as data analysis strategies for this research study were built upon the research questions and the theoretical framework of the study. In this research, multiple research methods were used systematically and purposefully based on the needs of design in three sequential phases, which will be explained later in this chapter; they included: 1) questionnaires, 2) Photovoice plus semi-structured interviews, and 3) participatory prototyping. The purpose was to reach areas connected to understandings, emotions, memories, experiences, and ideals of participants about learning spaces. With this purpose in mind, I drew from the concept of different degrees of users’ knowledge in Design Research Methods including what people say, what people do, and what people make (Sawhney, Prandelli & Verona, 2003), which correspond respectively to explicit, tacit (observable), and latent 50 knowledge of the participants. Dell'Era and Landoni (2014) explicate what people do underlines the actual situation, what people say reveals the past and the immediate future and what people make stimulates the researcher to investigate the remote past (memory) and the most distant future (dreams). Figure 3.3 illustrates Design Research Methods based on different levels of user’s knowledge adapted from Sanders (2002) in relation to the selected data collection method for each level in this study. Figure 3.3 Design Research Methods based on Different Levels of User’s Knowledge adapted from Sanders (2002) There has been a paradigm shift from design for users to design with users in the domain of design (Sanders, 2002). During the early 1980s, many designers, sociologists, and anthropologists collaborated on analyzing the users’ needs, but as Dell'Era and Landoni (2014) confirm this type of approach presented limitations since it did not reach areas connected to emotions, actual experiences, and ideals/imaginations. In this study, explicit needs of students regarding their learning spaces were identified by “what they said” while keeping in mind that they might reveal only what they wanted to or what they remembered in the time of answering the questions. Consequently, their responses guided the direction of the analysis towards “what they do” in everyday basis. However, analyzing what students did and how they used the provided learning spaces were insufficient because this approach only noticed observable needs and skipped the unexplored area related to what they knew, felt, and dreamt regarding their learning spaces. The investigation of students’ knowledge and 51 convictions revealed some indications about their perceptions of reality, their experiences, and indicated their ideals about learning spaces and how they liked the future to be. 3.7 Decision on Data Collection Methods Drawing on a DBR approach, this study is a qualitative study using multiple data collection methods in sequential phases. Continuous documentation occurred throughout the study, and the collected data from each stage analyzed in order to refine the needs of study and select the appropriate method for collecting data in the subsequent phase. Shavelson et al. (2003) suggest continuous documentation is needed throughout the study to conduct retrospective analysis in DBR. Data was collected based on the research question and the needs of design in each phase. Figure 3.4 illustrates the sequential phases of data collection drawing on Design Research Methods, which explained previously. Sequential phases of data collection methods included: - Questionnaires to address subjective aspect of learning spaces; - Photovoice plus semi-structured interviews to address objective aspect of learning spaces; and - Participatory prototyping to address co-constructed aspect of learning spaces. Figure 3.4 Sequential phases of data collection drawing on Design Research Methods 52 Figure 3.5 demonstrates the research questions in relation to DBR stages (Reeves, 2006), which explained previously, along with different levels of user’s knowledge in Design Research Methods (Sanders, 2002) connecting the selected data collection method for each phase. Figure 3.5 DBR (Reeves, 2006), Design Research Methods (Sanders, 2002), and data collection methods 3.8 Constructing an Eclectic Thematic Analysis-Informed Approach for Data Analysis The organization of this study drew on the logic of DBR, which allows employing different data analysis strategies based on the collected data (Wang & Hannafin, 2005) in order to explore the phenomenon in its complexity. DBR created an opportunity for an exploratory and retrospective process. The dialogic approach to data collection and analysis highlighted the complicated relationship between the literature and data. Within this flexible design, the research process was not totally sequential involving linear procedures, but instead it was dialogic through the iterative and continuous interactions with the data to accomplish the research objectives. 53 Each set of data, that collected through a specific method throughout the study, required appropriate data analysis strategies. As a result, data in each phase was analyzed through an expedient method of analysis to respond to the specific need of the study and guide the study to the next step. This flexible approach was adopted from DBR and provided an opportunity to see areas in which I lacked needed data realizing that my data had gaps. A combination of interconnected strategies for analyzing the data was applied in this study. While Thematic Analysis (TA) (Braun & Clarke, 2006; Boyatzis, 1998; Roulston, 2001), as the general method, informed the data analysis process at all stages, complimentary strategies were integrated to each phase when needed; reflexive iteration and axial coding in questionnaires analysis, reflexive iteration, axial coding, and art-informed approach in Photovoice, and reflexive iteration and art-informed approach in participatory prototyping. The benefits of using such an eclectic approach included cross-disciplinary non-linear investigation, creating a complete picture of participants’ knowledge obtained in different levels, enhancement of trustworthiness and rigor, and building a creative medium to interpret the data. Thematic Analysis is a widely used method in qualitative research for identifying, analyzing, and reporting patterns (themes) within the data. It has the potential to minimally organize and describe a data set in detail while, as Boyatzis (1998) mentions, it goes further and interprets various aspects of the research topic. Through its theoretical freedom, it provides a flexible approach that can be modified for the needs of many studies (Nowell et al., 2017). 3.8.1 Why not Grounded Theory? Considering the similarities of Thematic Analysis (TA) to some aspects of Grounded Theory (Charmaz 2006; Glaser, 1998; Strauss & Corbin, 1998), Braun and Clarke (2015) admit TA as a “grounded theory-lite” (p.12), which involves using the techniques of Grounded Theory for the development of categories and concepts. However, they suggest using TA when applying methods other than interviewing and when exploring research questions that are not focused on influencing factors. Since this study involved multiple data collection methods and it explored perceptions, experiences, and imaginations of doctoral students in relation to their learning spaces rather than any influencing factor, I decided to draw on Thematic Analysis. However, I incorporated coding strategies from grounded theory 54 (Boeije, 2010; Charmaz, 2006; Glaser, 1978; Glaser & Strauss, 1967; Strauss, 1987; Strauss & Corbin, 1998) to organize thematic relationships. Grounded theory coding strategies enabled establishing deeper patterns of connection throughout the study; through axial coding in Grounded Theory, I explored how the existing and emerging themes relate to each other within different phases of the study. 3.8.2 Reflexive Thematic Analysis The multiple-phased study exploring there different, yet related, research questions required an eclectic method of data analysis. Reflexive version of TA (Braun & Clarke, 2006) was used as a guiding framework to analyze the data set in each phase and the data corpus. “Data corpus refers to all data collected for a particular research project, while data set refers to all the data from the corpus that are being used for a particular analysis” (Braun & Clarke, 2006, p. 79). One of the advantages of using reflexive TA was that it is theoretically flexible. This means it can be used within different frameworks and to answer different types of research questions. According to Braun and Clarke (2015), it suits questions related to people’s perceptions, experiences, representation, and construction of meaning, which aligns well with aims of the three phases of this study. In addition, using reflexive Thematic Analysis allowed me to flexibly analyze each data set with an integrated approach as needed. Different approaches of Thematic Analysis (Braun & Clarke, 2015) that I applied included: inductive, deductive, and latent approach, which will be explained for each phase in detail later in this chapter. At the same time, as Braun and Clarke (2015) remind us, the separation of these approaches is not always that rigid. Therefore, I tried to keep the analysis theoretically coherent and consistent while I applied such an integrated approach. A quick overview of three approaches of Thematic Analysis and their relation to each phase are as follow: 1. A combination of inductive and deductive approach for the first phase, questionnaire. Coding and theme development were directed by existing concepts in the literature, however, there was room for coding directed by the content of the data in the open-ended questions. 2. A combination of inductive, deductive, and latent approach for the second phase, Photovoice (photographs taken by participants plus semi-structured interviews to reflect on their photos). Coding was directed by the existing ideas from the previous phase as well as 55 the literature with an open mind view to explore themes in the content of the data and the assumptions underpinning the data. 3. A combination of inductive, deductive, and latent way for the third phase, participatory prototyping (sketches, two- and three-dimension prototypes, notes, photos). Coding was directed by the existing ideas from the previous phases as well as the literature while discovering themes and the assumptions underpinning the data. In this research, data was collected and analyzed within three sequential phases. The qualitative analysis through Thematic Analysis did not proceed in a linear manner but was instead recursive; the recursive movement allowed flexibility (Design-Based Research Collective, 2003) moving from analysis-to-design-to-reflection-and-re-design, which created room for continual refinement. Moreover, findings are not intended as generalizable to wider social groups, but rather convey a narrative of individual experiences and commonalities of participants that may reflect wider trends. It is worth mentioning that the procedure of data collection and analysis drawing on the framework of DBR was not as linear as it is illustrated in Table 3.1. The procedure followed a flexible, recursive, and iterative flow allowing interaction and deliberation. Each phase was designed overlapped with the next and/or previous phase as follows: 1. Data from questionnaire intended to answer the first research question concerning students’ perceptions of learning spaces however, data from Photovoice and participatory prototyping was used as complimentary source for verification, clarification, and explanation. 2. Data from Photovoice supported answering the second question concerning students’ experience and interactions with their learning spaces. Data from questionnaire and participatory prototyping also added explanation to what students disclosed in the interviews and their photos. 3. Data from participatory prototyping was expected to answer the third question regarding students’ ideals and imaginations of their future learning spaces. What they said in the questionnaires and the interviews as well as how they interacted with their spaces indicated in their photos added indicators of how they wished their spaces to be. Following this iterative approach helped creating a more comprehensive picture of the situation of UBC Okanagan’s doctoral students’ experiences, needs, and ideals in relation 56 to their learning spaces. In Figure 3.6, I illustrated a schematic overview of the sequential yet overlapped phases of data collection as well as the retrospective and iterative analysis. Figure 3.6 A schematic overview of the sequential yet overlapped phases of the study 3.8.3 Coding the data As Saldana (2013) notes, coding is a heuristic process that allows for fluidity ensuring the process is alive and organic. Through this process, I considered the possibility of various understandings emerging from reading the data and reflecting on existing themes and ideas based on theoretical framework. At the same time, I attuned the emerging themes to my personal interpretations of what I was reading. This approach, which is inherent of qualitative analysis, influenced how I noticed the patterns shaping analysis of the data (Charmaz, 2006; Saldana, 2013; Stake, 1995). The process of analyzing the collected data was carried out using various coding procedures which made up “the analytic processes through which data are fractured, conceptualized, and integrated” (Matavire & Brown, 2008, p. 140). The analytic process consisted of different iterative stages. Being informed by Thematic Analysis, data from each phase was analyzed through iterative cycles of coding, going back to the data and re-coding 57 based on emerging codes, albeit Srivastava and Hopwood (2009) reminded us that codes and themes do not emerge on their own. They are driven by what we, as investigators, want to know and how we interpret the data based on theoretical framework, our ontological and epistemological assumptions, our subjective perspectives, and our intuitive understanding of the field. Similarly, Ely et al. (1997) declare “[i]f themes reside anywhere, they reside in our heads from our thinking about our data and creating links as we understand them” (pp.205-6). To code, I followed Saldaña’s (2009) recommendation to approach coding method choices with “pragmatic eclecticism” (p. 47). I let the initial data collection and review occur before deciding on which coding method(s) to use. The prescribed methods of coding seemed “destructive” toward meaning making (Packer, 2011, pp. 79, 325) and did not align with the exploratory nature of the study. After the first cycles of coding in each phase, axial coding as a second cycle method was employed to find bigger-picture ideas through concepts that link across the data sets (Strauss, 1987; Strauss & Corbin, 1998). Through axial coding, I explored how the existing and emerging themes relate to each other within different phases of the study. Boeije (2010) explains that the purpose of axial coding is “to determine which [codes] in the research are the dominant ones and which are the less important ones … [and to] reorganize the data set: synonyms are crossed out, redundant codes are removed, and the best representative codes are selected” (p. 109). Saldaña (2009) adds axial coding is appropriate for studies employing a wide variety of data forms, which is the case in this multi-phased study. Reflexive iteration (Srivastava & Hopwood, 2009) was incorporated to Thematic Analysis as an applied strategy through visiting and re-visiting the data and connecting the emerged codes with the insights, thus leading to refined understanding. The role of reflexive iteration analysis was not seen as a repetitive task but as a reflexive process; as Srivastava and Hopwood (2009) note, “[as a] key to sparking insight and developing meaning” (p.76). In order to explicitly engage with the analyzing the data, I used a framework (Srivastava & 58 Hopwood, 2009) comprising three basic questions as the specific reference points. The questions included: 1. What are the data telling me? (Explicitly engaging with theoretical, subjective, ontological, epistemological, and field understandings); 2. What I want to know? (According to research objectives, questions, and theoretical points of interest); and 3. What is the dialectical relationship between what the data are telling me and what I want to know? (Refining the focus and linking back to research (p.78). Writing the results conducted also in reflective and iterative cycle. As the findings were written up, analysis continued with reflection on the results, returning to the analysis, writing up some of the findings, reflecting to the results, and so on. Braun and Clarke (2006) support this approach within Thematic Analysis and consider writing as an integral part of analysis, not something that takes place at the end, it does with statistical analyses. 3.9 Iterative Cycles of Reviewing the Related Literature In contrast to classic Grounded Theory (Glaser & Strauss, 1967), in Thematic Analysis, some engagement with the literature is required to develop the research proposal and research questions. In Grounded Theory, reviewing the literature in the area of the study is avoided in order to keep the process of theory generation free from preconceived ideas. The fear comes from the idea that the researcher might be caught up in forcing the data to fit the ideas in the literature. Thematic Analysis approach aligns with DBR’s Preliminary research (Plomp, 2007) conducted as an initial literature review in this study, which was tentative and provisional. Since literature of learning spaces comes from a range of disciplinary and professional perspectives, I needed to confine the scope of the literature review based on the objectives of the study. The Preliminary research involved an initial literature review on learning spaces, which helped me refine the research questions, identify the underpinning theoretical and methodological frameworks, and develop my doctoral research proposal, as a requirement of the doctoral program to proceed to comprehensive exam and candidacy. The reviewed literature also supported designing the questionnaire through providing theoretical directions. 59 Strauss and Corbin (1998) recommend inclusion of an initial literature review because of its ability to stimulate theoretical sensitivity, its usefulness in raising questions and its ability to provide supplementary vitality. Other than the initial literature review conducted at the very beginning of the study, there were several rounds of reviewing the literature based on the needs of the study in different stages. Literature review was a continuous and iterative process throughout the study. Findings from each phase guided the study to the next phase, which required exploring the relevant concepts in the literature. Findings from each phase was compared to the literature to explore similarities, differences, and tensions. This approach made room for new aspects of learning space to emerge. In the next sections, each phase will be explained in relation to its data collection method to answer the relevant research questions, the design of the process, data analysis strategy, and the involving issues/limitations. 3.10 First Phase, Questionnaires The aim of this research is to provide information that might be used to improve the quality of learning spaces and students’ learning in doctoral education. How students perceive their learning environments has long been accepted as having a significant influence on the quality of the students' learning in different educational settings from elementary to post-secondary level (e.g., Doyle, 1977; Fraser, 1989; Fraser and Walberg, 1991; Marsh, 1981; Ramsden, 1988). Reviewing the literature on students’ perceptions of learning environment, Clarke (1995) comes up with the idea that most higher education institutions have an institutionally approved questionnaire or use universal instruments such as College and Tertiary Students’ Perceptions of their Learning Environments Inventory (CUCEI) (Fraser & Tregaust, 1986), the Students’ Evaluation of Educational Quality (SEEQ) (Marsh, 1981), and the Cognitive Holding Power Questionnaire (CHPQ) (Stevenson, 1990). Many of these instruments, particularly the universal ones, are “psychometrically sound” (Clarke, 1995, p. 2). Clarke (1995) addresses a few limitations of these instruments: first, there is always the concern of using a priori set of statements to which individuals respond a forced-choice format and it does not necessarily allow the students to indicate what is salient to them; second, the instruments focus on either just one type of learning environment (e.g., CUCEI is designed to be used with seminar groups up to 25), and third, these instruments do not investigate why students perceive their learning spaces the way they do. Moreover, 60 considering the distinguished characteristics and aims of doctoral education, I did not find any specifically designed instrument to explore doctoral students’ perceptions on learning spaces. In the first phase of this study, I designed a questionnaire using a semi-structured open-ended approach, a combination of Likert Scale questions and open-ended format, to gather students’ perceptions on the multi-layered learning spaces that they might have already used and/or any other spaces that mean a space for learning to them. The aim was to understand how they identify different aspects of learning spaces along with the reason(s) of why they think the way they do. This approach allowed students to choose not only a particular learning space but also allowed them to write about why and what was important to them. I collected multiple narratives of doctoral students’ perceptions and experiences on learning spaces over time beginning with the questionnaire and followed by Photovoice and participatory prototyping. The questionnaire acknowledged the significant value of students’ views on their learning spaces. It captured students’ perceptions of learning spaces and addressed the complex relationship between space and learning in doctoral education through: - allowing complexity of doctoral studies and different aspects of learning spaces to be explored; - allowing students’ choices in indicating the spaces and the factors that were important to them; and - investigating why students hold the perceptions they hold (Clarke, 1995). 3.10.1 Questionnaires to address subjective aspect of learning spaces This phase aimed at reaching the area corresponds to the explicit knowledge (Sawhney, Prandelli & Verona, 2003) of doctoral students on learning spaces and the objective was to explore how they perceive, identify, and interact with their learning spaces —including conceptual, personal, social, virtual, and material spaces. This phase corresponds to the first research question, how do doctoral students perceive a “learning space” and its intended use(s)? It also ties to perceived space (Lefebvre, 1991), the spatial practices or the ordinary, unconsidered experiences of everyday lives within a space. Students’ daily routines are embedded in space and time. An adaptation of Lefebvre’s (1991) perceived space in this 61 phase was helpful in capturing something of perceptions and experiences of students in relation to their learning spaces during their doctoral experience. It helped unravel the intersections between the social and spatial practices of doctoral education and what the students each brought to the situation. Investigation of students’ explicit knowledge (Sawhney, Prandelli & Verona, 2003), what they said about their learning spaces, revealed some indications of the multi-layered definition of learning space in doctoral education and guided the study toward the next phase, where I went deeper and explored students’ experiences of the identified spaces. The next phase corresponded to the tacit knowledge (Sawhney, Prandelli & Verona, 2003) of doctoral students on learning spaces, where they negotiated their relationships with the spaces and revealed deeper explanations and detailed aspects of how they interacted with the spaces. 3.10.2 Participants in questionnaires Doctoral students and alumni of UBC Okanagan from different disciplines took part in this phase of the study. In Section 3.13.1, I explain the recruitment process of participants. Also, Table 3.2 shows the detailed information about participants demographic. Thirty-eight individuals completed the questionnaire. Three questionnaires were excluded from the study since they were left incomplete. Participants from different departments/faculties reflected on the role of different formal spaces they had already experienced through a wide range of pedagogical approaches (from traditional lectures to problem-based laboratories) as well as informal learning spaces such as public spaces, graduate students’ collegium, and coffee shops, where they spent their time reading, writing, and reflecting on their work. 3.10.3 Questionnaire design As Boddington and Boys (2011) explain, learning space brings together the designed spaces, the existing socio-spatial practices, and individual perceptions of both practices and actual places alongside the institutional aims. In this context, design and development of learning spaces necessitates a relational understanding of individual and collective learning, within and beyond the physicality of any institution. Boddington and Boys (2011) remind us exploring learning spaces are therefore not about only seeking singular design solutions to 62 particular problems. Instead, it is about the development of knowledge as a generative and shared activity and the role of different kinds of spaces in this process. The questionnaire was the first phase of this multi-phased study exploring doctoral students’ perceptions on diverse range of spaces within and beyond UBC Okanagan’s campus and their intended uses (Appendix D). It was designed using Survey Tool (FluidSurveys), which was available to UBC students. The questions were designed to support answering the first research question. Many qualitative researchers who tend to identify qualitative research with inductive/open-ended surveys (Jansen, 2010), exclude pre-structured questions in qualitative questionnaires. However, in this qualitative study, I included pre-structured/deductive statements into the area of qualitative questionnaire as they were concerned with diversity as opposed to numerical distribution. The complex multi-layered definition of learning space in the context of doctoral education did not allow to start with open-ended questions to explore students’ perceptions of learning spaces; participants needed some clues to start thinking about the concept. The open-ended question after each statement provided an opportunity for participants to clarify and/or justify their responses. The questionnaire also included open-ended questions for additional thoughts and comments. It is worth mentioning that in this qualitative study, the aim of the questionnaire was not establishing frequencies, means, or other parameters but determining the diversity of the choices within the given population. Jansen (2010) calls this method qualitative survey and explains, “[t]his type of survey does not count the number of people with the same characteristic (value of variable) but it establishes the meaningful variation (relevant dimensions and values) within that population” (p.3). The questionnaire was designed in five sections: 1) Demographic section. It included background and demographic questions to help determine certain aspects of doctoral students at UBC Okanagan. The demographic questions included program of study and department/faculty, stage of doctoral program, if the participant is an international or domestic student, and if their supervisor provided a specific workspace during their PhD (see Table 3.2). 2) Questions concerning participants’ perceptions of learning spaces in relation to their doctoral studies. These questions were designed drawing on the key concepts related to the notion of learning spaces including conceptual, personal, social, digital, and 63 physical spaces (Boys, 2011a; Savin-Baden, 2007; Temple, 2008), and learners’ perceptions and experiences of such spaces. This set of questions was designed in the format of seven-point Likert Scale where the students were asked to indicate how much they agree/disagree with the presented statements; they had the option to briefly explain why they agree or disagree at the end of each statement. The aim was to elicit more in-depth responses about the spaces and the events that they feel help or hinder their learning. Likert Scale was used as a tool to examine perceptions and experiences of doctoral students on the notion of learning space. As this type of measure does not require participants to provide a concrete yes-no answer through the black-and-white view, it made answering easier to respondents. It also allowed them to respond quickly and efficiently in seven degree of disagree/agree spectrum. They could offer neutral feelings too. Furthermore, they were provided with a blank space to provide an explanation for their response to each statement. At the end of this section, they were asked to add any other space that means a “space for learning” to them. 3) Questions concerning participants’ experiences with UBC Okanagan’s spaces in relation to their studies. This set of questions in combination with the campus map inventoried the existing spaces on campus. They gave participants an opportunity to reflect on UBC Okanagan’s different spaces. 4) Campus map. In this section, participants provided with a UBC Okanagan map to indicate their favorite spaces that they had most used during their PhD and write the purpose for each. 5) Open-ended questions. Two open-ended questions including “If you can change one thing in your existing learning spaces, what would it be?” and “What is the ideal learning space for doctoral students at UBC Okanagan?” were asked at the end of the survey. The purpose was to reach students’ ideals and imaginations at this stage of the study; the responses guided the study towards the subsequent phases, Photovoice and participatory prototyping, where I explored students’ experiences and interactions with the existing spaces as well as their ideals and imaginations to envision future spaces. 3.10.4 Questionnaire analysis In the first phase of this study, participants completed a questionnaire in the format of a Likert Scale and answered to the open-ended questions. The objective was to go back to the 64 basics and to unravel what matters about learning space in the context of doctoral education. Drawing on an integrated theoretical framework and the liminal space between education and architecture in the context of doctoral education, this phase of the study aimed at exploring the conceptualization of learning spaces based on doctoral students’ perceptions; the range of spaces that students perceive as spaces for learning. In this phase, reflexive Thematic Analysis was adopted to inform data analysis decisions. It enabled me to generate and integrate two set of themes: themes directed by existing concepts in the literature, and the themes emerged from the content of the data. Through a deductive approach in TA (Braun & Clarke, 2015), data was fractured, conceptualized, and integrated to explore participants’ perceptions of learning spaces in relation to their doctoral studies and their experiences with UBC Okanagan’s spaces. The process was guided by the key concepts related to the notion of learning spaces including conceptual, personal, social, digital, and physical spaces (Boys, 2011a; Savin-Baden, 2007; Temple, 2008). The second set of themes were related to data from the open-ended questions in the questionnaire analysing through inductive approach in TA (Braun & Clarke, 2015). During the process of analyzing the data, I tried to organize words and the meanings that they imply (Miles et al., 1994). In order to sort the data gathered into themes, which then were fed into descriptions, I used coding looking for similarities and differences. To code, data was broken down, compared, and then placed in similar categories, and different data created new categories; all together, they enabled constructing themes and descriptions (Walker & Myrick, 2006). In order to verify and saturate the categories, I conducted iterative process of reviewing the data, coding, and comparing the emerged codes with the literature. Comparing the codes and categories with the relevant literature in every stage of the process enabled constant moving between inductive and deductive thinking; there was a constant interplay between checking and proposing based on literature . Data from this phase was visualized quantitatively through simple sunburst graphs and bar charts in order to summarize the findings, and then, the charts were interpreted and described qualitatively. Sandiford and Ap (2003) clarify if we consider participants to respond to qualitative options, words that best match their opinions, feelings, experiences, or their attitudes, the nature of Likert data must be seen as a quantitative representation of a qualitative notion. Johns and Lee-Ross (1998) confirm in such case, any analysis of the 65 Likert Scale data should be conducted with care and recognizing the importance of its qualitative aspects. Elaborating qualitative survey research in social research methods, Jansen (2010) explains, “qualitative-versus-quantitative nature of data is established in the analysis. It is not inherent ontology but analysis which determines whether a study is qualitative or quantitative” (p.4). The charts also provided a bird’s eye view of the students’ perceptions of learning space; the in-depth interviews in the next phase provided a narrative and detailed account of the data from this phase. Findings from this phase of the study answered the first research question, how do doctoral students perceive a “learning space” and its intended use(s)? and guided the study to the next phase making room for new codes and categories. In the next chapter, data from this phase will be presented and discussed. 3.10.5 Questionnaire issues/limitations The qualitative nature of this study and the relatively subjective nature of data from this phase, exploring students’ perceptions of learning spaces, makes the analyses methodologically questionable. Sandiford and Ap (2003) confirm data from Likert Scale questionnaires are often subjected to this problem. Although I incorporated open-ended questions to certain number of statements in the questionnaire, there was little chance for conversation and allowing the participants to make meaning of why they agree or disagree with the statements. This issue somehow resolved with the participants who participated in the semi-structured interviews in the next phase. In the interviews, I went back to the questionnaires and asked participants for more explanations when needed. Jansen (2010) confirms well-performed interviews or observations may produce valuable knowledge by validity checking through replicating or triangulating. Confronting this issue, the resultant data from the participants who did not participate in the next phases could hardly be seen reliable. This study was situated in UBC Okanagan with a small number of voluntary participants, which therefore limits the types of generalizations that can be made. Thirty-eight doctoral students/alumni from different disciplines at UBC Okanagan participated in the first phase. Participants of the second and third phase emanated from the original thirty-eight, eleven doctoral students in Photovoice and twelve in participatory prototyping. Moreover, any educational institution is part of a wider, dynamic web of cultural and social 66 aspects which requires contextual investigation to unravel the complex relationship of space and learning in each context. Theoretical and methodological process of this study could be used as a guideline for other institutions’ explorations rather than the findings. Another limitation was that the study engaged a limited number of doctoral students who decided to participate in this research. Thus, the assertions made in answering the study questions were limited to my interpretation of how and why the involved participants perceive and use the existing spaces and identify them as their learning spaces. If any of the students had not participated in the study, the findings would be different. From the same perspective, the inclusion of other participants from other universities would have changed the study findings as they have different perception and experiences in relation to their learning spaces. In this regard, the findings from this study cannot be presumed to be reflective of the broader perspective of doctoral students within UBC Okanagan or beyond. Luborsky and Rubinstein (1995) describe this issue as a common concern in qualitative research discovering the scope and nature of the universe to be sampled. In this study, all doctoral students at UBC Okanagan at the time of data collection were invited to complete the questionnaire. There was no chance to select a sample that represents the diversity of participants coming from different departments and fields of study, or cultural background (e.g., domestic or international students). Luckily, students who participated in this phase were from different departments and included both domestic and international students. However, considering the number of doctoral students doing a PHD in different fields, this sample may not represent the existing doctoral student population. There was still room to purposively select a diversity sample with the aim to cover all varieties, but time limitation and ethical consideration in recruiting participants did not allow to go further. Another issue relates to coding and analyzing the data from questionnaires. There are guidelines for coding provided by qualitative researchers in the literature (e.g., Glaser & Strauss, 1967; Miles et al., 1994; Boyatzis, 1998), which have been helpful technically. However, as Jansen (2010) declares, the quality of coding is not a technical methodological issue; it involves theoretical sensibility and creativity, which is subjective to the researcher. The question arises here is that at what point does the researcher’s techniques and interpretations force, instead of allowing for emergence? This study and the research 67 questions reflect my personal interests and motives. Similar to any other qualitative study, my worldview, values, and perspectives have influenced the interpretation of findings. Another limitations exists for all doctoral studies because of its nature; data were coded, and themes identified in the data by one person and the analysis then discussed with a supervisory committee. Although this process allows consistency in the method, but it fails to provide multiple perspectives from a variety of people with differing expertise/perspectives. When using this method for any other studies in the future, the coding of data should involve several individuals with themes’ being developed using discussions with other researchers. 3.11 Second Phase, Photovoice Photovoice is a participatory approach to collecting data that actively engages individuals or groups in the production and interpretation of personal or collective perspectives through photography (Wang & Burris, 1997). Originally developed by Wang and Burris (1997), the goal of Photovoice is to enable people to record, reflect on collective concerns, and promote critical dialog about important issues through discussions of the photographs produced by participants. Photovoice has been successfully implemented with diverse populations and used to assess and evaluate a wide range of issues, from exploration of health issues of minority populations to evaluations of education techniques (Evans-Agnew, Boutain, & Rosemberg, 2016; Leipert & Anderson, 2012; Moffitt & Vollman, 2004). Advantages of Photovoice include the ability to explore perceptions and experiences through visual images, evaluate program goals, and enable participants to express their personal explanations, ideas, and stories (Catalani & Minkler, 2010; Hergenrather et al., 2009; Horwitz, 2012; Leipert & Anderson, 2012). The use of photography is a creative approach to data collection that can promote understanding of the human experience through the generation of substantive data and knowledge that otherwise might be difficult to construct (Balmer, Griffiths, & Dunn, 2015). To avoid a researcher-centered approach in this phase, I applied Photovoice as a visual storytelling method through which participants reflected on the problems and strengths of their learning spaces that might have been difficult to conceptualize or express in the questionnaires. It provided a chance for participants to express their experiences in relation to their learning space visually and verbally through taking photographs and reflecting on the photos in the subsequent interviews. In this project, the use of photography helped me 68 explore students’ perceptions and experiences of the spaces in which they learn; it also provided me with an opportunity to gain a more complex view of the spaces that research participants have been experiencing. As an implication of participatory design (Sanoff, 2011), second phase of this study emphasizes on learners’ experiences and the range of spaces they require. It characterized by 1) an emphasis on experiences of doctoral students in relation to their identified learning spaces; 2) a focus on the relationship between space and learning; 3) an emphasis on raising consciousness among participants; and 4) social change as an integral aspect of social science research and the main aim of design. Wang and Burris (1997) confirm that Photovoice provides an opportunity for community members to creatively document their concerns and simultaneously act as “catalysts for change” (p. 369). McIntyre (2003) adds, Photovoice could be an opportunity for people to express themselves in new and imaginative ways; they can increase their knowledge about the issues that most affect them through taking photographs, enrich their understandings of their lives within a particular community and have fun. In this phase, Photovoice was applied as a methodology that 1) enabled students to record aspects of their doctoral experience; 2) provided opportunities for doctoral students to reflect on their photographs that mirror the realities of their learning spaces influencing their doctoral experiences; and 3) used photography to catalogue doctoral students’ learning spaces issues at UBC Okanagan in the hope of influencing university’s informed and principled decisions in the future. Photovoice enabled the participants to tell visual stories about their spaces. In turn, those stories became points of entry into seeing beneath surface issues and the extent to which space influences doctoral education. 3.11.1 Photovoice plus semi-structured interviews to address objective aspect of learning spaces This phase supports answering the second research question; it explored the relationship between the university’s provided spaces and students’ identified learning spaces and the way that they interacted with them. This phase aimed at reaching the areas connected to students’ tacit knowledge on learning spaces and how they use the existing provided 69 spaces in everyday basis. It also corresponds to conceived space (Lefebvre, 1991), the conceptualized space by planners which attempt to describe patterning of the social in space. In this phase, participants took photos of what they identified as their learning/research spaces and provided a brief written description for each photo. Then, they were invited to a semi-structured interview to explain more about their photos. Typically, in a Photovoice project, all participants should be provided with digital cameras. Since providing cameras was not possible for me and all participants had personal mobile cellular devices, I asked them to use their own devices. 3.11.2 Participants in Photovoice Data collection in DBR is often limited to small samples (Van den Akker, 2007). The number of participants who involved in this study was small but purposive. Thirty-eight doctoral students/alumni from different disciplines at UBC Okanagan participated in the first phase. Eleven doctoral students from the first phase continued participating in the second phase. Braun and Clarke (2015) clarify the size of the sample does depend on the size and scope of the project; since Thematic Analysis focuses on the identification of patterns across data, they recommend a sample size of: “6-10 [detailed] interviews for a small TA project” (p. 15). 3.11.3 Photovoice procedure design Combining Wang’s (1999) approach and Goodhart’s et al. (2006) suggested steps for Photovoice projects, I facilitated a process through which participants could reflect on their learning spaces within the context of UBC Okanagan. The process involved a series of steps as follows: 3.11.3.1 Recruiting a group of Photovoice participants. To select the potential participants, I checked the “consent section” in the surveys and contacted the students/alumni who expressed their interest to continue participating in the study. I received consent from eleven existing doctoral students and three alumni who were interested to participate. They were from different disciplines across the campus, and it was a good opportunity to hear diverse voices. Three of them dropped in the middle of the Photovoice process. 3.11.3.2 Introducing Photovoice methodology to participants. I sent an invitation email to all students and alumni who expressed their interest to participate in Photovoice and provided me with their email address. I scheduled a “training” session at their convenient 70 time after they got back to me via email. Due to conflict in participants’ schedules, I had to arrange several sessions to clarify the process for the participants (Photovoice Training Agenda, Appendix F). At each session, I explained a brief description of the process, where they needed to take photos of their identified learning spaces using their phones or any other device that they have and write a caption/brief description for each photograph. I clarified that there was no limit on the number of photos that they wish to take; it was only important to reflect on their experiences on what they have identified as their learning spaces (on campus or off campus) through a selection of photos that they wish to share. I also reminded them that after they took their photos and sent them to me, they would be invited to a 45-minutes interview, which would be a reflection session to debrief their photos. The introductory session followed by an introduction to Photovoice discussing what is expected from the participants, ethical considerations, and how to obtain consent. Participants were provided with a written document explaining Photovoice and its ethical consideration for their reference during the project (Appendix G). 3.11.3.3 Obtaining informed consent. The following documents were attached to the invitation email that needed to be reviewed and signed by participants: 1) Information Sheet and Informed Consent for Participating in Photovoice (Appendix E); 2) Consent to Use of Image Form (Appendix H); and 3) Photo Release Form (Appendix I). Participants were asked to sign two copies of the consent forms, one for their own record and one to be sent to me. 3.11.3.4 Providing time to participants to take photos. Participants were given four weeks to review the documents and take their photos after the training session. However, I only got back from two participants within the given time. After sending reminders, all participants (except one) sent their photos and signed consent forms followed by scheduling an interview time. This process took about four months since it turned to summertime and participants were not available for the interview. Three students dropped from the study in this phase. What participants needed to do in the Photovoice included: 1) Reviewing the Information Sheet and Informed Consent which included a brief explanation of purpose of the study and research procedure as well as the benefits and risks of the study and confidentiality. They needed to sign the forms and send a copy back to me via email; 2) 71 Reviewing the Instructions for Photovoice participants which provided information about Photovoice, ethical considerations, and how to safely conduct the Photovoice; 3) Taking their photos and writing descriptions/captions. Guidelines for creating captions included the following: a) What is happening in this situation? What were you looking to illustrate when you took the picture? b) What do you want me to know about this situation? c) What does this have to do with learning spaces? d) What do you like and dislike about this situation? and e) What can be done to improve the situation? Moreover, it was clarified that their photos may include either themselves as research participants, and/or other people; in order to respect the privacy of people in public spaces, anyone who has a photo taken has to complete the Consent to Use of Image Form (Appendix H); 4) Completing the Photo Release Form (Appendix I) considering the number of the selected photos for the interview sessions; and 5) Taking part in the interview, which was scheduled at their convenient time. 3.11.3.5 Meeting to discuss photographs. The interviews were scheduled based on students’ convenient time and took place in a booked room on campus. One interview took place in Okanagan College in Vernon, where one of the participants had chosen to write her dissertation there and she did not have time to come to campus. In addition, two interviews with UBC Okanagan alumni took place in Vancouver, one in UBC Vancouver and the other in a coffee-shop’s booked room in downtown Vancouver. I conducted four interviews via Skype and WhatsApp since I was overseas during the available time of the participants and I could not do face to face interviews with participants. The Skype interview arrangements took place the same as face-to-face interviews. 3.11.3.6 Engaging decision-makers (action). The last step of any Photovoice project is to inform the involving decision-makers about the issues through showcasing the photographs with the hope of influencing principled decisions. Since Photovoice was conducted as a part of my doctoral dissertation, there was no chance to invite university officials and display/discuss photos during the Photovoice project. Findings from Photovoice did not provide a thorough account of participants’ ideas about learning spaces. The entire dissertation including a synthesized discussion about doctoral students’ perceptions, 72 experiences, and imaginations will be sent to the College of Graduate Studies at UBC Okanagan to be reviewed by responsible university officials. 3.11.4 Semi-structured interviews In this study, I incorporated Photovoice with individual interviews. The semi-structured interviews, subsequent to photos taken by students, helped as a complementary source of data to explore participants’ understandings on using of learning spaces. Visual, textual, and oral descriptions through Photovoice method gave voice to students and allowed them to record and reflect on their learning spaces. Castleden and Garvin (2008) confirm that Photovoice method can also empower research participants since it gives voice both individually to participants through taking photographs and collectively through discussions related to photographs. Dempsey and Tucker (1994) support this assertion noting that using visual methods in research can be used to stimulate and verify perceptions, and to explore similarities and differences of participants’ perceptions within a group. The interviews were conducted to give an explanatory picture of the situation and to provide the study with in-depth understandings of doctoral students' experiences about their learning spaces. 3.11.4.1 Interview protocol. The interview protocol was developed to ensure that interview questions align with second research question, investigating the relationship between students’ identified learning spaces — Lefebvre’s (1991) perceived space— and the university’s learning spaces — Lefebvre’s (1991) conceived spaces, and to construct an inquiry-based conversation (Castillo-Montoya, 2016). Creswell’s (2007) approach in qualitative inquiry along with Horwitz’s (2012) work with Photovoice were integrated to design a draft of open-ended questions for the semi-structured interviews and facilitate a process of thinking through which photographs reflected participants’ experiences within their learning spaces. In addition, participants’ comments and written explanations in the surveys created a context and guided asking the interview questions. The emerged themes from the first phase facilitated the discussion in the semi-structured interviews. Creswell (2007) suggests four types of questions to design the skeleton of a semi-structure interviews: 1) introductory questions, 2) transition questions, 3) key questions, and 4) closing questions. Introductory questions were general questions and questions based on 73 the demographic section of the surveys to open the conversation. For instance, “You told that you are a PhD student in Interdisciplinary Graduate Studies in the Faculty of Creative and Critical Studies; what is the area of your research? how long have you been working on this topic? Transition questions linked the introductory question to the key questions to be asked. For instance, “what kind of spaces do you need to conduct such research”, “how long do you usually spend time in the lab to do your experiments?” Key questions were mostly related to the photos they had taken; I asked the key questions drawing on Horwitz’s (2012) suggested framework for generating Photovoice questions, which spell out the acronym PHOTO. P: Describe your photo? H: What is Happening in your picture? O: Why did you take a picture of this? T: What does this picture tell us about your life? O: How can this picture provide opportunities for us to improve life (in this case, learning spaces)? I conducted the interviews in a manner that they could add, modify, or reconfigure the questions in ways that would facilitate the overall interpretative process. While I used this framework, I did not enforce in order to maintain the natural progression of the conversation and to maintain freedom of expression. Those participants who chose not to follow the framework, addressed the framework’s questions in their own way and they still provided rich descriptions for their photographs. After discussing each photograph, I asked each participant whether they would like to add anything else about the photograph. I also had one participant who decided to lay out all the photographs she had taken on the screen, think about what the photographs meant to them and say something meaningful about the photos. 3.11.5 Photovoice analysis Capous-Desyllas and Bromfield (2018) explain in traditional Photovoice studies, a participatory approach is taken both in data collection and analysis process. After participants take their photographs, they engage in a group conversation session to discuss their photographs and collectively identify themes that emerge from their photos. The second phase of this study was a Photovoice study, but it did not follow the traditional approach in collecting and analyzing the data. This phase of the study engaged with individual dialogue sessions (interviews) with eleven doctoral students and alumni, who took photographs of their lived experiences in relation to their learning spaces. Avoiding a researcher-centered approach and involving the participants more in the research process, the purpose of this phase was to gain a deeper, and more complex 74 understanding of participants’ perceptions and experiences on their learning spaces through the medium of photography and conversation. Photovoice, as a visual storytelling method, enabled participants to reflect on the problems and strengths of their learning spaces that might be difficult to conceptualize or express in the questionnaires. According to Latz (2017), Photovoice data analysis typically includes traditional qualitative methods such as Thematic Analysis. Many researchers rely on standard forms of qualitative data analysis to analyze the transcript data (Castleden & Garvin, 2008; Catalani & Minkler, 2010; Goodhart et al., 2006; Horwitz, 2012). Capous-Desyllas and Bromfield (2018) discuss in such cases photographs are usually added as “afterthought” to the reports of the findings. Considering the fact that photographs as visual data included in the data set in this phase, there was a potential for gaining a deeper, embodied, and more nuanced understanding of the research data through incorporating the arts in the analysis process. Similar to other Photovoice projects, Thematic Analysis (Boyatzis, 1998; Braun & Clarke, 2006; Roulston, 2001), as the general method, informed the data analysis process. However, drawing on Design-Based Research as the underpinning research methodology of this study, data collection and analysis of procedures were interdependent with the needs of the design (Design-Based Research Collective, 2003; van den Akker, 1999; Wang & Hannafin, 2005). As a result, complimentary analysis strategies were incorporated to each phase as needed. Given that this phase explored experiences of doctoral students in relation to their learning spaces, as expressed through their photographs and the interviews, a variety of techniques were used from reflexive Thematic Analysis (Braun & Clarke, 2006) as general strategy as well as reflexive iteration (Srivastava & Hopwood, 2009) as a complimentary applied strategy to analyze the transcript data from the individual dialogue sessions. From an art-informed approach (Capous-Desyllas & Bromfield, 2018), the process also included the creation of collages/infographics as a technique to “conceptualize a phenomenon by fleshing out different facets in order to get a nuanced understanding of it” (Butler-Kisber & Poldma, 2010, p. 4). Discussing the contributions of the arts to knowledge, Eisner (2008) affirms the arts offer new ways in which to perceive and interpret the world that would otherwise go unknown. Within research context, art can be a representation, a process, and a form of 75 inquiry and analysis (Capous-Desyllas & Bromfield, 2018). Incorporating art into the analysis stage of research had the potential to offer ways of revisioning the process, which was not simply possible through descriptive linear language. Gerstenblatt (2013) confirms how such a tactile process of creating visual art involves a distinct “multisensory experience and offers creative latitude for the researcher, informant and academic community” (pp. 11, 12). Borrowing Capous-Desyllas and Bromfield’s (2018) major levels of analysis, data from this phase was analyzed through three major levels: 1) an analysis of each participant’s transcript, 2) a cross-case analysis comparing all transcripts together, and 3) creating visual art to gain a deeper understanding of the transcript data and corresponding photographs. To analyze the collected data from the second phase, first, I matched caption(s) with its related photo and archived them in files. Then, I transcribed all the interviews. There are software and programs to convert audio to texts automatically, but I manually transcribed all the interviews. There were two reasons for doing so: first, transcription was a process of familiarizing myself with the data (Braun & Clarke, 2006; Riessman 1993) and reflecting on them while I was typing. Layder (1998) calls this process pre-coding, the process of circling, bolding, and color-coding the significant quotes from participants. Similarly, Boyatzis (1998) acknowledges this process as codable moments worthy of attention. Further, Bird (2005) even argues it should be “a key phase of data analysis within interpretative qualitative methodology” (p 227). The second reason for transcribing all the interviews was because of the small size of the study; this study did not engage with a large amount of data, and interviewees were only eleven people. Thus, time for transcribing the interviews was not a big issue. An interplay of inductive, latent, and deductive approach informed the analysis of the data. Through an inductive or bottom-up approach (e.g., Frith & Gleeson, 2004), which is more data-driven, themes were identified in relation to the data themselves (Patton, 2002). In this approach, the themes identified were not necessarily reflected in the specific questions that I asked participants in the interviews. They also were not controlled by my theoretical assumptions and interest in the area of the topic. Nevertheless, as Braun and Clarke (2006) remind us, data cannot be coded in an “epistemological vacuum” (p. 84) and the researchers cannot free themselves of their theoretical and epistemological commitments. Analysis was 76 therefore a process of coding the data without trying to fit them it into the pre-existing coding frame from the questionnaires, or/and the theoretical framework of the study. As mentioned earlier, I drew from the concept of different degrees of users’ knowledge in Design Research Methods including what people say, what people do, and what people make (Sawhney, Prandelli & Verona, 2003), which correspond respectively to explicit, tacit (observable), and latent knowledge of the participants about their learning space. When it came to analysis of the data from “what participants said” in the interviews and “what they did” reflected in their photos, I incorporated a latent approach borrowed from Thematic Analysis to identify the underlying assumptions and conceptualizations that shaped the surface data. Braun and Clarke (2006) explicate, “for latent Thematic Analysis, the development of the themes themselves involves interpretative work, and the analysis that is produced is not just description but is already theorized” (p.84). In addition, a deductive or top-down approach (e.g., Boyatzis, 1998; Hayes, 1997) was applied in analyzing the data from Photovoice. The emerged codes from previous as well as the key guiding categories from the literature direct the process of coding. I conducted iterative process of reviewing the data, coding, and comparing the emerged codes with the literature. Comparing the codes and themes with the relevant literature enabled constant moving between inductive and deductive thinking. I read each transcript, focusing on one participant at a time, with attention to the related photo(s) to generate codes and themes. What was significant or interesting was noted to create codes, which then clustered into themes. In order to explicitly engage with the analyzing the data, I used the reflexive iteration’s framework (Srivastava & Hopwood, 2009), which enabled visiting and re-visiting the data, connecting them with the insights, and leading to refined understanding. Drawing on reflexive iteration, questions in Table 3.3 were asked for each photo that corresponded with each participant’s transcript. 77 Table 3.3 The Analysis procedure for each photo drawing on reflexive iteration Reflexive Iteration What are the data telling me? (Explicitly engaging with theoretical, subjective, ontological, epistemological, and field understandings What I want to know? (According to research objectives, questions, and theoretical points of interest) What is the dialectical relationship between what the data are telling me and what I want to know? (Refining the focus and linking back to research The emerged codes from questionnaires in the previous phase were also used as guides in the coding process. Drawing on Saldaña (2009) suggested strategy, I tried to summarize, distil, and condense the data, not simply reduce them. Madden (2010) confirms that such analytic act does not diminish but “value adds” to the research story (p. 10). Then, I started searching for themes and collating codes into potential themes. Hatch’s (2002) characterization of theme was used as a guideline including: similarity, difference, frequency, sequence, correspondence (they happen in relation to other activities or events), and causation (one appears to cause another). Research participants came from different disciplines, departments, and even different cultural backgrounds and had different individual perceptions, values, and experiences about their learning spaces. When I searched for themes and patterns in the coded data, I took into account that I could group things together not only because they are alike, but because they might also have something in common. As Saldaña (2009) notes “even if, paradoxically, that commonality consists of differences” (p.6). I also acknowledged Braun and Clarke’s (2006) attention that the “key-ness” of a theme is not necessarily dependent on quantity, but rather on whether it captures something important in relation to the research question. 3.11.6 Photovoice issues Wang and Burris (1997) note like any other methodologies, Photovoice hides as well as discloses. The post-modern scrutiny issues potentially exist in Photovoice; for example, who used the camera, what the user photographed, what the user chose not to photograph, who selected which photograph to discuss, and who recorded whose and what thoughts about whose and which photographs. Wang and Burris (1997) mention methodological ideals may 78 not coincide with reality and be practically possible to uphold in a Photovoice project; for instance, participants may not want to display their images. Similar to other qualitative studies, where we bring “our subjectivities, our personalities, our predispositions, [and] our quirks” to the process (Sipe & Ghiso, 2004, p. 482), my level of personal involvement in the research as a doctoral student at UBC Okanagan has filtered how I perceived, documented, and coded the data. So do the types of questions that I asked during the interviews and the types of responses that I received (Kvale & Brinkmann, 2009), the detail and structuring of my coded data (Emerson, Fretz, & Shaw, 2011), the gender, social class, and ethnicity of my participants and myself (Behar & Gordon, 1995; Stanfield & Dennis, 1993). Ethical concerns are the most challenging aspect of this method which was considered through the required ethics application approved by UBC’s Behavioral Research Ethics Board (BREB). The detailed ethical considerations will be explained in Recruitment and Ethics Management section of this chapter. See Appendix A for the Behavioral Research Ethics Board Certificate of Approval. Other dilemmas arise when using Photovoice as a tool to evaluate community assets and address their needs. As Wang and Burris (1997) note, photographs are easy to gather but difficult to analyze and summarize because they provide a very large quantity of complex data that can be difficult to digest. In order to create a more comprehensible data and ensure as much validity as possible and to gain as much insight as possible, triangulation, or “using multiple data collection strategies” (Gay, Mills, & Airasian, 2012, p.393) was applied in this phase. Triangulation was achieved by employing the two research instruments, questionnaire and the semi-structured interviews. Overlapping the data collection and analysis method allowed verification of data. Comments that provided in the previous phase by each participant was verified and discussed in the semi-structure interviews. Meanwhile, exploring choices in taking photos in Photovoice phase led to new areas for dialogue as well as production and exchange of ideas in the next stage. Not surprisingly, scheduling the Photovoice sessions was a challenging aspect of conducting this Photovoice project, a frequently noted concern in participatory research (Madrigal et al., 2014; Morales-Campos, Parra-Medina, & Esparza, 2015). The original plan was to schedule one training session to introduce the project, explain about the ethical 79 considerations in taking photos, and distribute the documents including informed consent forms, photo release forms, and written instructions for participants’ reference. The intention of training session was also to create a discussion space for participant students. However, schedule conflicts resulted in having several individual sessions, which did not provide the opportunity for students’ engagement; it turned to a session where I only convey some practical considerations. Time intensity was another issue. The whole process of Photovoice lasted four months while it was thought to take one month. Moreover, participation involves time, and some participants may not have much time to give. McKim (1980) in her book, Experiences in Visual Thinking, reminds us that “[s]eeing fully takes time” (p. 67). Social change is a slow and difficult process and Photovoice, as a research methodology, may not be viewed as a legitimate approach by decision-makers, community members, researchers, or even participants themselves. Small number of participants was another involving issue in this project; more research at UBC Okanagan and other context with larger number of participants is needed to explore doctoral students’ experiences and needs of learning spaces in a larger scale. 3.12 Third Phase, Participatory Prototyping Since the 1970s, there have been attempts to include users and other stakeholders in the design process, which have given rise to several approaches commonly called co-design (Sanders & Stappers, 2008) ranging from research-oriented (e.g., applied ethnography) to design-oriented strategies (e.g., using generative tools) (Steen, 2013). Co-design often builds on the tradition of (Scandinavian) participatory design. However, Sanders and Stappers (2008) refer co-design to “any act of collective creativity, i.e., creativity that is shared by two or more people” or “the creativity of designers and people not trained in design working together in the design development process” (p.6). Steen (2013) mentions co-design approaches may focus on user involvement, where researchers and designers move toward users (e.g., usability testing) or emphasize the role of users in which users move toward researchers and designers (e.g., participatory design). This study is positioned in participatory design spectrum, which aims to invite doctoral students with little or no experience in design and provide the necessary tools for them to collaborate 80 and make meaningful contributions to the design and research process through making rapid prototypes. As Reay et al. (2017) mention, understanding of design as a collaborative process engaging end-user to meet their needs is by no means new. What is relatively new, they said, is addressing Wicked Problems (Rittel, 1972) through collective problem-solving emphasizing on rapid prototyping. A prototype can be a sketch or a two- or three- dimensional model made from diverse materials. The premise in prototyping is to encourage open dialogue (Smith 2012) and explore ideas primarily through the act of making. Condon (2012) clarifies the act of making allows participants to make better sense of the real-world practicalities of proposed concepts rather than being confined to abstract ideas. Sanders (2013) proposes prototypes as an important means of bringing ideas into the world through different forms. Similarly, Brandt, Binder, and Sanders (2012) note “when making we use our hands for externalizing and embodying thoughts and ideas in the form of (physical) artefacts. Such artefacts might describe future objects or provide views on future ways of living” (p.155). Based on the impact of prototyping in research through design (Stappers, 2013), which is the aim of this phase, prototyping played several roles including: - It evoked a focused discussion as the phenomenon is “on the table”; - It confronted the world since the theory was not hidden in abstraction; - It confronted theories considering several overlapping perspectives; and - It allowed students to experience a situation that did not exist before. Following questionnaires and Photovoice phases, the third phase of this study emphasizes ideals and the range of spaces that participant students envision for doctoral education through participatory prototyping. As argued by Sanders (2002), participatory approach to design allows the investigation of latent needs. Adapting this approach in a small-scale research in this multi-phased study, the responsibility for creation was shared between participants led by me as facilitator of the co-creation process. Participatory prototyping as a method in this stage of the study allowed an exploration of latent needs of 81 doctoral students in relation to their learning spaces, however, it revealed some aspects of their observable and tacit needs that were missed in the previous phases. In this phase, participatory design was applied as a user-centric research methodology for sensing, prototyping, and refining complex design solutions in an evolving real-life context (learning spaces). Co-prototyping aimed to 1) enable doctoral students to take an active part in the research and innovation process, 2) identify latent needs of doctoral students in relation to their learning spaces, and 3) let the participants leverage on their imaginations and experiences to proactively propose potential design solution(s), which has to be translated into suggestions and principles and ultimately address the needs of doctoral students’ community at UBC Okanagan. 3.12.1 Participatory prototyping to address co-constructed aspect of learning spaces This phase supports answering the third research question exploring how doctoral students might envision the future of their learning spaces through prototyping. Buchenau and Suri (2000) describe a prototype as “practice and object orientated, [that] can range from a sketch to a virtual or physical model at different stages of development –from what a design object looks like, behaves like, to works like” (p. 424). Typically, a prototype is concerned with developing “an idea about a product, system, or service to meet human needs and devising a plan for executing that idea” (Binder et al., 2011, p.68; see also Boradkar & Dhadphale, 2020). Rapid prototyping emerged in the 1990s as an approximate way to engage with ideas using basic materials and tools, and became associated with design thinking, “a human-centered design process to problem solving, change or idea-generation” (Jewitt et al., 2019. P.3). Dunne and Raby (2013) suggest rapid prototyping for thinking with your hands quickly and practically to explore a concept. Co-prototyping, as the last phase of this multi-phased research, aimed at reaching the areas connected to students’ latent knowledge on learning spaces and how they might imagine the future of learning spaces. It also corresponds to ideational space (Lefebvre, 1991), the space of the inhabitants and users that can be altered by ordinary people through their imagination towards transforming the space. What Lefebvre (1991) calls ideational space or representational space, is the space(s) where we attempt to “intervene in and adapt existing material spaces to our own requirements” (Boys, 2011b, p. 55). For Lefebvre, ideational space is articulated most strongly as “a grassroots political act” (p.55), where 82 ordinary people seek to transform the normative representations of space made by architects and others in power. Drawing on Lefebvre’s (1991) proposed spatial triad (perceived space, conceived space, and ideational space) as a means to conceptualizing the relationships between a space and its inhabitants, I have opened up both analysis and debate by exploring learning spaces through three parts: 1) The complex and non-linear intersections between ordinary routines (socio-spatial practices) and students’ perceptions, which was considered in the questionnaires, 2) The interactions and experiences of students with the designed environments inquired in Photovoice, and 3) Participants’ perceptions of and engagements with the learning spaces explored in participatory prototyping. This research proceeded from the view that space is a socially constructed and collective resource (Lefebvre, 1991). It also follows Situated Learning theory (Lave & Wenger, 1991), which views learning in doctoral education situated and embodied in communities of practice. In this context, learning is a function of the activities, the context, and the culture in which learning is situated (Lave, 1988). Participatory prototyping took these philosophical views a step further toward action; it provided an opportunity to creative and imaginative engagement of students in the design process and make their voices heard. As Sherringham and Stewart (2011) confirm, in such exploratory process, a rich tapestry of socially constructed information is developed for interpretation and translation. Proposing a framework to help organize the tools, techniques and methods of participatory design, Sanders, Brandt and Binder (2010) clarify the tools and techniques should be used to serve a specific purpose in any participatory design project. They categorize four dimensions of participatory design: 1) for probing participants, 2) for priming participants in order to immerse them in the domain of interest, 3) to get a better understanding of their current experience or, 4) 83 the generation of ideas or design concepts for the future, for instance by creating and exploring future scenarios. (p.2). The authors explain by clarifying the purpose of any participatory design project, we should describe why specific tools and techniques are being used. Aligning with the third and fourth categories mentioned, the purpose of conducting a participatory prototyping in this phase was to explore future scenarios and capture a deeper understanding of students’ experiences as a complementary source of data to the Photovoice data. 3.12.2 Participants in participatory prototyping In this phase, I invited doctoral students to tinker with ideas and materials as they prototype possible design solution(s) to the given design challenge through creating descriptive artifacts (low-tech prototypes). Brown and Duguid (2000) describe tinkering as constructing, playing, transforming, and personalizing them for one’s own learning and practice (Brown & Duguid, 2000). Participatory design processes usually involve people with different backgrounds, experiences, and interests. In addition, an important challenge was to find appropriate ways for engaging and involving people in the activities. Based on the research design, participants from each phase were asked if they were interested to continue participating in the subsequent phases of the study. Considering consent as a layered and an ongoing process allowed me to proceed with the study and invite potential participants from previous phases; I re-confirmed the consent in each phase through an informed consent form. This approach helped to invite people who had been already involved in the research process and were familiar with the context of the study. Moreover, it provided the data with consistency since the same people participated in all three phases of the study. Twelve doctoral students continued participating in prototyping. The only issue in this approach to recruit participants was that the number of participants in each phase gradually declined and the students/alumni sample was obtained only by approaching the remaining participants. 3.12.3 COVID-19 and virtual prototyping studio At the time of organizing the participatory prototyping session(s), COVID-19 (Coronavirus) as a pandemic was spreading globally. Accordingly, countries around the world, including Canada, were working to contain the current outbreak of coronavirus 84 (COVID-19). UBC took direction from the British Columbia Provincial Government to consider cancelling the social events. As such, the circumstances impacted the design and development of participatory prototyping process at this stage. Considering safety of participants and social distancing regulations, I considered adapting the prototyping process into a co-prototyping virtual studio through creating an online space. The approved ethical considerations for the face-to-face studio were considered and adapted into the virtual studio. Although in-person ideation and prototyping were preferable and considered in the research design, I designed an idea generation process and a space for remote ideation to open up more options and explore effectiveness of virtual collaboration. Articulating the changing conception of doctoral education and the issue of mobility in the increasingly globalized academic context, I have already discussed the spatial implications of the change in doctoral education and importance of emerging virtual learning spaces and their influence on the contemporary learning environments (Chapter 2). In addition, drawing on a social constructivist paradigm in learning and the notion that learning is embedded in communities of practice in doctoral undertaking, the potential of digital technologies to develop virtual communities of practice has been discussed previously. Framing the above concepts of learning space within the changing doctoral education, designing and exploring a virtual ideation space in this phase can help to better understand different aspects of learning spaces in the increasingly globalized academic world and specifically in unpredictable situations like COVID-19 outbreak; the potential possibilities and the shortcomings of the virtual spaces were identified in this exploration. 3.12.4 Design and development of virtual co-prototyping studio The idea of co-prototyping virtual studio was to benefit from technologies to create a digital environment in which participants’ imaginations and ideas can be captured, synthesized, and discussed in order that their ideas might propose (design) responses to meet needs and aspirations. Brown (2009) argues, “what needed most nowadays is a comprehensive thinking method, done collaboratively, and oriented towards human needs aimed at innovation to ensure its sustainability”. Since design thinking aimed at innovation, Brown (2009) made three spaces to ensure innovation process worked: inspiration space for identifying problems; ideation space, where ideas will find their form through prototyping, and implementation space to design a comprehensive scheme of production to deliver the 85 innovation for its targeted user or societies. This study focused on inspiration and ideation elements though conducting three sequential phases: questionnaire, Photovoice, and generative toolkits within the domain of participatory prototyping. To avoid the tricky scheduling issues, I considered an asynchronous process which did not occur at a specific time, but instead allowed participants to view and contribute to a shared digital space whenever they chose over a longer period of time. Participants could work around their own schedules while still being able to participate in their preferred time. 3.12.4.1 Form, purpose, and context. To design and develop the participatory prototyping process, I drew from a framework suggested by Sanders, Brandt, and Binder (2010), which includes three dimensions: form, purpose, and context. Form describes the action that took place, and, in this case, it is described as making and/or telling/writing. Purpose describes why the tools and techniques are being used. As explained earlier, the purpose of prototyping was to get a better understanding of participants’ current experience and to generate ideas/explore future scenarios. Context describes where and how the tools and techniques are used. The prototyping process took place in a format of online studio adopting an open approach to innovation. Similar to larger scale initiatives called “social innovation labs”, the prototyping process aimed to address a complex problem through rapid prototyping. The overall mindset with which the participatory prototyping is conducted characterized by the belief that all people are creative (Sanders, Brandt & Binder, 2010). 3.12.4.2 Virtual studio: method, tools, and techniques. As mentioned earlier, the restrictions caused by COVID-19 affected conducting the prototyping process. As a result, I developed a virtual studio, an online version of a design studio, instead of the expected face-to-face prototyping session. Studio is an environment where participants are introduced to a design problem then, they work individually or collaboratively to solve the given problem. There are no lectures in studios instead, facilitator(s) lead the process (Cennamo et al., 2011). Crowther (2013) believes studio is the “signature pedagogy” of design education. In developing the virtual studio, 1) the studio was designed to allow participants prototype without me being present; and 2) the materials were prepared in a way that could be used in multiple modes and formats. As Sanders (2000) says, a toolkit is specific to its purpose and creating and refining generative toolkits is a design process by itself. Brandt, Binder, and Sanders (2012) explain, 86 components of generative tools can be a combination of visual and verbal in an infinite variety of meaningful ways, however, the components are predominantly visual, as opposed to verbal. The components are put together into toolkits and participants select from them in order to make prototypes/artefacts that express their thoughts and ideas. “The resulting artefacts might be collages, maps, stories, plans, and/or memories. The stuff that dreams are made of is often difficult to express in words but may be imaginable as pictures in your head” (p.160). Sanders and Stappers (2014) note generative toolkits are typically used in facilitated collaborative activities, and their results can be analyzed to find underlying patterns. Based on the framework upon which the virtual prototyping was developed, I designed a method and a toolkit considering the entire experience that the participants were going to go through. As Sanders, Brandt, and Binder (2010) explain, “[a] method is a combination of tools and techniques that have been strategically put together to serve a specific purpose” (p.4). I organized a toolkit, a collection of tools and techniques, and explained how the tools could be put into action. Participants were provided with flexibility to sort, categorize, and prioritized the tools and techniques to make rapid prototypes. To explain how to participate in prototyping and prime participants to execute the activity, I created a video using VideoScribe, which is a software for making whiteboard animations. Using a whiteboard-like surface and liven hand-drawn illustrations along with my simultaneous narration, this software helped me create a form of narrative storytelling, commonly known as “narrative visualization” (Segel & Heer, 2010). Lee, Kazi, and Smith (2013) confirm, “as an emerging medium, narrative visualization can borrow techniques from existing sources (e.g., comics, posters, etc.) and extend them to develop a more engaging form of storytelling” (p. 2416). I used Padlet, which is an online post-it board/platform to share ideas and collaborate. Some of the affordances of this technology that was helpful for this project include: - enabling collaboration and knowledge sharing for online activities - enabling collaboration both asynchronously and synchronously - storing ideas and activities for future reference - works on any internet enabled device - no sign up required 87 - instant view of others’ posts - participants can only edit their own posts - privacy settings can restrict the wall to certain users - drag and drop documents from desktop - add different media to your comments (e.g. podcasts, video, images, texts) - layout posts in a variety of forms - copies of walls can be shared or exported in a variety formats - fairly user-friendly and free. I shared the Padlet link with the participants allowing them to insert ideas/photos of their prototypes anonymously or with their names. In the video, I also explained how to share materials and interact with others. After they open the Padlet link, they could simply double click anywhere on the board and post. They could upload their photos or videos of their prototypes along with notes, sketches, and voices for explanation or clarification. They could also comment on other participants’ works or ask questions. I reminded them that it was a private space and only they were given access to it as co-researchers. The video consisted of two main sections: 1) A recorded video of me introducing myself and inviting doctoral students/alumni of UBC Okanagan to participate in virtual prototyping. Potential participants in this stage had already contributed to this research in the questionnaire and Photovoice; in the introduction video, I thanked them for their contribution, reminded them of the context of the study, and invited them to participate in the last stage of the study, and 2) A narrative visualization video, which started right after the introduction video. In a whiteboard animation format, I employed appropriate icons/images and short key words along with my simultaneous narration to briefly explain: a) The context: learning spaces and the contemporary approaches in design emphasizing the active participation of the space occupants in design process, b) Mindset of design thinking; I explained, “in this process, we are going from ideation to prototyping. We developed an understanding of the challenge based on what you shared in the questionnaires and Photovoice. What is important now at 88 this stage is to brainstorm potential design solutions and make your thinking visible through making prototypes”, c) The design challenge: “how might we design learning spaces to create better learning experiences for doctoral students?”, d) Definition of a prototype: prototyping is a rough and rapid portion of the design process, preliminary version of a design. The prototype can be a sketch or a two- or three- dimensional model made from diverse materials, e) Potential tools and materials for rapid prototyping and digital prototyping: paper and pencils/pens, cardboard, scissors, and, duct tape, recycling simple found items (buttons, sticks, fabric, toothpicks, straws, etc.) for rapid prototyping, and Tinkercad for digital prototyping. Tinkercad is a free, online 3D modeling program that is known for its simplicity and ease of use. I reminded them that they can use whatever works for them or mix and match the methods and materials, f) The possible ways to create prototypes and multiple forms of prototypes; I provided a few examples of different kinds of prototypes to clarify how might a prototype look like. I also emphasized that their prototypes did not necessarily need to look good; it just had to make their thinking visible, g) Four rules to consider for prototyping: 1) no judgements, 2) think freely, 3) big numbers (quantity of the ideas), 4) many heads are better than one, h) How to share prototypes on Padlet, and i) A brief synthesized review of participants’ experiences with their learning spaces from Photovoice data Figure 3.7 shows a few captured screens of VideoScribe video that I created to explain the process. 89 Figure 3.7 Captured screens from VideoScribe, whiteboard animation video In the invitation email that I sent to participants, I clarified if they agreed to participate, they needed to: 1) Watch the video 2) Prototype (based on the explanations provided in the video) 3) Share their thoughts, ideas, and prototypes in the Padlet board, which was also explained how to do it in the video. I also provided them with my rough minimum estimation of the time that they needed to participate: 7.30 minutes to watch the instruction video, 30 minutes to make prototype(s) and share them on Padlet. 3.12.5 Participatory prototyping analysis In the virtual studio the generative tools were provided to participants to help them imagine and express their own ideas about how they want their learning spaces to be in the future. Sanders and Stappers (2014) suggest generative toolkits describe a participatory design language that can be used by non-designers (i.e., future users)” (p. 7). Authors add that generative toolkits’ results including the artefacts and the related descriptions can be analyzed to find underlying patterns. Having said that, Malinverni, Mora-Guiard and Pares (2016) claim methodological weaknesses in the analysis of the participatory design’s results hinder the effectiveness of design contributions of the participants. To address this issue, they propose the use of a framework derived from multimodal analysis (Jewitt, 2013; Kress, 90 2010) to collect and interpret participants’ contributions. Their proposed framework helped as a guideline to analyze the findings from participatory prototyping in this phase. Jewitt (2013) describes multimodality as an interdisciplinary approach to analyze different resources that people use to construct meaning. At a theoretical level, he claims, multimodality is grounded in the key concept of mode, which incorporates a set of resources for making meaning, for instance the ensemble of writing and images on a page. According to this framework, each mode has a set of modal affordances, which refers to what is possible to express easily with the resources of each mode and what is impossible or less straightforward (Kress, 2010). In this context, Jewit (2013) suggests, meaning is created in the iterative connection between the affordances of a material artifact, the affordances of the socio-cultural environment, and the knowledge that people bring to the event. This approach has been applied in a wide range of contexts, including the analysis of workplace interactions (Hindmarsh & Pilnick, 2002), classroom interactions (Bezemer, 2008), and playgrounds (Goodwin, 2000). Streeck, Goodwin, and LeBaron (2011) clarify multimodal analysis is a situated and embodied meaning making. Multimodal analysis in this study stems from acknowledging that participants used multiple ways to construct meaning considering the specificities of the context (UBC Okanagan campus) and the proposed activities (virtual prototyping). I focused the analysis on participants explorations of space (conceptual, physical, virtual). Multimodal analysis allowed identifying the dominant themes and underlying values and integrating both textual and tangible outcomes in a structured process. As such, through iterative reading and examining the data, I identified thematic elements in the artifacts and texts applying Thematic Analysis (Braun & Clarke, 2006). The analysis consisted of two main interrelated steps: participants’ productions (two- and three-dimensional prototypes) and their associated narratives. The aim was to include participants’ contributions from a perspective that goes beyond the limits of verbal language (Jewitt, 2013; Malinverni, Schaper & Pares, 2019) and to better understand the meaning of what participants created using different resources and materials. An interplay of inductive and latent approach to Thematic Analysis informed the analysis of the data. Through an inductive (bottom-up) approach I identified the codes and themes in relation to the data themselves (Patton, 2002). In this approach, the themes were 91 not controlled by my theoretical assumptions in the context of learning spaces. Analysis therefore took place in a process of coding the data without trying to fit them it into the pre-existing coding frame from the previous phases, or/and the theoretical framework of the study. I began by reading the descriptions and observing the corresponding visuals. Then, I studied each participant’s contribution one-at-a-time actively engaging with open coding. Visiting and revisiting the whole data, reflexive iteration’s framework (Srivastava & Hopwood, 2009) enabled me connecting and clustering the emerged themes. Similar to the last phase, Photovoice, I incorporated an art-informed approach (Capous-Desyllas & Bromfield, 2018) by creating collages/infographics using the emerged codes and themes. 3.12.6 Participatory prototyping issues/limitations Despite the contribution, I acknowledge the limitations of participatory prototyping and the use of generative tools in the context of this study. Given these limitations, I am cautious in generalizing the findings of this study. Political, theoretical, and practical aspects of participatory design involve issues and concerns that have been addressed in the related literature. Kensing and Blomberg (1998) explain that three main issues have dominated the discourse in the participatory design context: the politics of design, the nature of participation, and methods, tools, and techniques for carrying out design projects. Robertson and Simonsen (2012) note participatory design is a political process involving different conflicts and dilemmas. Similarly, Halskov and Hansen (2015) consider politics as one of the fundamental aspects of participation, which involve conflict perspective reflecting the opposing interests of participants and the ones on power. But, as also pointed out by Muller and Druin (2012), in contemporary participatory design, the conflict perspective has been challenged by a “poly-voiced perspective”. Meanwhile, “participants might have first-, second, and third-hand knowledge of the processes” (Robertson & Simonsen, 2012, p.3). Considering the political issues involved in participatory design in different levels, engaging students in experimental practices of innovation and future making in learning space context can bring new meanings and forms of students’ involvement in the ongoing process of learning space development. In this study, experimental practices of innovation based on the core values and ideals of participatory design was explored. The aim was to explore the democratic engagement and open-ended 92 design processes in the context of learning spaces, which allows decision-making in contentious explorations of sustainable change to be evolved constantly. Theoretical aspect of participatory design involves issues regarding “the choice of user participants and the form of participation” (Kensing & Blomberg, 1998, p. 173) which must be carefully considered in every participatory design project. Ethical considerations in recruiting participants in this phase of the study and turning the prototyping process into a virtual one, due to COVID-19 restrictions, limited the number of participants. This issue impacted the study since some voices from different departments/schools across the campus were missed. Moreover, practical concerns and limitations of participatory design including the used tools, techniques, and methods (Kensing & Blomberg, 1998) impacted this phase of the study. This study aimed at using the provided generative tools to seed a mindset of collective creativity. Participants did not have a chance to work/play together simultaneously and exchange their ideas/imaginations/dreams. Visual toolkits allowed them the time to prototype individually, but they did not engage in the virtual space (Padlet) to listen to each other's ideas and dreams, thereby the situation restricted facilitating more effective collaboration. Also, participants were not requested to reflect on the design process, and refine the process and the prototypes, which is an important principle of any design process (Cobb et al., 2003; Nelson & Stolterman, 2014). As Sanders (2000) confirms, “the transformation that takes place when a group of people goes from a verbal exchange of ideas to a collective and visually expressive mode is remarkable.” In the virtual studio the generative tools were not used for collaborative thinking, mapping, dreaming and storytelling as they were designed. Meanwhile, a collection of ideas emerged and synthesized, which will be uncover in the next chapter. Participatory design is an eclectic and multidisciplinary approach (Greenwood, Whyte, & Harkavy, 1993). McIntyre (2003) confirms that the nature of the process is an iterative and collaborative exploration for the purpose of knowledge creation. The aim of participatory process in this study was to create a collaborative space for doctoral students to discuss, ideate, make, and reflect on their prototypes together. As COVID-19 restrictions impacted the design and development of the process, in the asynchronous process, I was not 93 able to engage participants as co-researchers in the synthesis/analysis of what they had created. 3.13 Recruitment and Ethics Management Given the involvement of human subjects in this study, I submitted requests for ethics approval to UBC’s Behavioral Research Ethics Board (BREB), where I conducted this study, and got approval to conduct this research. The Ethics Board assessed the study to be minimal risk to participants and approved the protocol for the research project after I conducted some minor revisions (Appendix A). Following the BREB approval, I sent the link of the UBC Survey Tool including the Information Sheet and Initial Consent Form (Appendix C) and the questionnaire (Appendix D) to the University's Graduate Community facilitators and the Alumni Association representatives at UBC Okanagan to be distributed to all doctoral students and the alumni of the UBC Okanagan. I intended to include doctoral students’ multiple voices from different departments and disciplines; so, I sent the questionnaire to all the potential participants, doctoral students and alumni of UBC Okanagan. For Photovoice and prototyping phases, I invited participants who had already been involved in the research process and were familiar with the context of the study. This approach provided the data with consistency since the same people participated in all three phases of the study. The Information Sheet and Initial Consent Form outlined a brief explanation of purpose of the study, and research procedure as well as the benefits and risks of the study, confidentiality, the anticipated required time, and contact to provide more information about the study plus an initial consent offering the potential participants to say “Yes” or “No” to participate in any or all the next phases of the study. The majority of the participants completed the survey within the given time, fifteen days. But there were three participants that completed the survey after they received reminders after the given time. Consent was considered as a layered and an ongoing process; this means the initial consent in this survey allowed me to proceed with the study, but I re-confirmed the consent in the next phases through an informed consent form related to each phase, one for Photovoice (Appendix E) and one for participatory prototyping (Appendix K). I also reminded the participants that at any level, they could withdraw any time from the study without any repercussions. 94 3.13.1 Participants recruitment I invited doctoral students and alumni of UBC Okanagan to take part in this phase of the study by sending a link, which included an invitation letter, a consent form, and the questionnaire. The invitation letter outlined an explanation of purpose of the study, and research procedure as well as the benefits and risks of the study. The University's Graduate Community Facilitators and the Alumni Association representatives distributed the link to the potential participants via their email lists and their LinkedIn private groups. Sending out up to three follow-up emails, thirty-eight participants including thirty doctoral students and eight alumni agreed to participate in the first phase of the study through completing the questionnaire. In the first phase, I did not know the identity of the participants. Only the participants who chose to get involved in the next phases consented to add their email contact in the “consent section” of the questionnaire which is kept confidential. The demographic section of the questionnaire was not able to identify the research participants who had not chosen to participate in the next phases. For selecting participants for Photovoice, second phase, I checked the “consent section” in the surveys and selected the interested doctoral students/alumni for the next phase. I sent them a detailed explanation of the Photovoice process and requested their consent to conduct a semi-structured interview after they completed taking photos of their learning spaces (Appendix E). I recorded the interviews with research participants using my cellphone. While the initial letter of invitation explained the interviews would be electronically recorded, I confirmed study participants’ consent for recording the conversation at the beginning of each interview. I conducted six interviews in person and all the other interviews via WhatsApp or Skype, depending on the preference of the participant. The interview transcripts were sent to the interviewees to be verified. I ensured them that all conversations and discussions that are a part of the study will be kept confidential. I also reminded them that they own the authorship of their photos and have the right to remove any of the photos they contribute at any point during the project. Among participants of the first phase, twelve doctoral students and alumni participated in the next phase, participatory prototyping, which was conducted virtually on Padlet platform. I explained to participants that they can post photos of their prototypes, sketches, and notes anonymously or they can choose to put their names through logging in to 95 the platform. Similar to the previous phase, I reminded them of their authorship of their photos, prototypes, and sketches. 3.13.2 Security of data during the study Confidentiality has been maintained in all phases of the study. The UBC Survey Tool was used in phase one of the study, which is a Canadian-hosted survey solution complying with the BC Freedom of Information and Protection of Privacy Act. Participants’ identities have been kept strictly confidential in all phases. They have not been identified by name as they will be assigned a pseudonym. Computer data including questionnaires, interview recordings and transcripts, photographs taken by participants, participants’ sketches, notes, and prototypes have been password protected and will be kept for a period of five years. When those five years are past, all documents will be destroyed. 3.14 Trustworthiness Considering the interpretive nature of qualitative research, establishing a set of characteristics capable of evaluating this type of exploration remains an ongoing challenge (Denzin & Lincoln, 2008). Developing a strong level of trustworthiness has become a guiding feature for qualitative studies evaluation (Bloomberg & Volpe, 2012; Stake, 1995). Lincoln and Guba (1985) explain trustworthiness is a way that researchers can persuade themselves and the readers that the procedure and findings of the conducted study are worthy of attention. Merriam (1988) suggests conducting early efforts in research design to establish validity and reliability; she recommends conducting strategies such as triangulating the data. Addressing the issues of rigor and trustworthiness in qualitative research, Nowell et al. (2017) focus on data analysis in Thematic Analysis procedure to ensure trustworthiness; they declare the inquirer must demonstrate data analysis has been conducted in a precise, systematic, and consistent manner through “disclosing the methods of analysis with enough detail to enable the reader to determine whether the process is credible” (p. 1). If readers are not clear about the underpinning assumptions of the researcher and the way that researchers analyzed the data, evaluating the trustworthiness of the research process will be difficult. In developing and designing this study, I tried to establish a congruent methodological process connecting the research questions, the methodology, the data collection, and analysis, which can offer support the overall trustworthiness of the study (Bloomberg & Volpe, 2012; Creswell, 2003; Stake, 1995). In order to ensure as much 96 validity as possible and to gain as much insight as possible, triangulation, or the “using multiple data collection strategies” (Gay, Mills, & Airasian, 2012, p.393) was applied. Triangulation was achieved by employing multiple research instruments and cross-checking different sets of data: semi-structured questionnaires in the first phase, photographs, and the scripts from interviews in the second phase as well as notes, photographs, sketches, and prototypes in the third phase. I conducted Thematic Analysis driven by Braun and Clarke’s (2006) six-phased approach as well as Lincoln and Guba’s (1985) criteria for trustworthiness during each phase. Table 3.4 highlights the multi-phased process as well as the way that I addressed the criteria for trustworthiness during several phases of Thematic Analysis. Findings from this study do not produce a complete account of learning space design, but it developed and tested a new framework and methodology for data gathering and knowledge creation about learning space design for doctoral education through a participatory approach. This is what Edelson (2002) calls a design methodology, among other potential outputs of DBR, which provides guidelines for the process rather than the product. The exploratory character of the study cannot allow generalizing the findings; what the outcome can offer is design principles (lessons learned) within a small-scale context. Findings represent a vision, a beginning base to take action based on students’ experiences about learning space in doctoral studies. Future research is needed to enlarge the sample and test the methodology. Drawing from DBR approach, findings can be examined and adapted to other contexts for their own purposes; generalization of the findings increases when they are tested and validated in more cycles of design in more contexts. Design principles generated from this study can be examined and tested in the same context for local conditions. Also, it can be used as “working hypothesis” (Cronbach, 1975, p 125) in other contexts, rather than conclusion. It is also important to expand the information by including the perspectives of other involving stakeholders (undergraduate students, professors, staff, and graduate program providers) in future work. 97 Table 3.4 Establishing trustworthiness during each phase of thematic analysis, adapted from Nowell et al. (2017) Phases of Thematic Analysis Means of Establishing Trustworthiness Phase 1: Familiarizing with data Extend engagement with data through transcription of the interviews, comments, etc. Document thoughts about potential codes/themes Keep records of all data field notes, transcripts, and reflexive journal Phase 2: Generating initial codes Conduct pragmatic eclecticism allowing the initial data collection and review occur before deciding on which coding method(s) to use (Saldaña, 2009) Employ complementary strategies to coding (reflexive iteration, art-informed approach) Use of a coding framework, a combination of inductive, deductive, and latent coding (Braun & Clarke, 2015) Audit trail of code generation Phase 3: Searching for themes Diagramming to make sense of theme connections Keep detailed notes about development of themes Phase 4: Reviewing themes Recursive approach and cross-iteration comparisons to gain as much insight as possible on the topic Phase 5: Defining and naming themes Clearly describe the scope and content of each theme Employ further refinement before moving on to the next phase Phase 6: Producing the report Describing process of coding and analysis in sufficient details Thick descriptions of context Report on reasons for theoretical, methodological, and analytical choices throughout the entire study 3.15 My Role as a Researcher In this section, I describe the ways my values, worldview, and experiences influenced my role as a researcher. My role as a researcher was to design the study, complete the ethics applications, introduce photovoice and prototyping to participants and collect the data, conduct the interviews, analyze and interpret the data, draw conclusions, and provide recommendations. My perceptions and experiences of learning spaces as a doctoral student, 98 my previous beliefs about participants’ perspectives, and my own understandings and beliefs about learning spaces all contributed to my interpretations. My doctoral research built upon my interest, educational background, and work experiences in Education (MA) and Design (BA, MA). This research highlights my exploration in the intersection of both domains. Design thinking as a creative mindset and Design-Based Research (DBR) as an iterative and flexible research methodology guided me during the design and development of this research. I built upon my prior knowledge about DBR and design thinking from my master’s research in Education, where I explored the impact of a Maker Day on teachers’ conceptualizations of design thinking. At the Maker Day, educators had experienced design thinking and making as creative mindsets that support constructionist learning and can be integrated to the curriculum to re-conceptualise 21st century’s education. During my PhD, I had the opportunity to attend a few design thinking workshops at Stanford’s d.school, which were valuable experiences to explore design thinking potential possibilities as a human-centred approach to tackle real world problems. As a visiting student, I also audited the History of Universities seminars in the Graduate School of Education at Stanford University, which helped me better understand that educational institutions are part of a wider, dynamic web of cultural, social, and historical contexts. My role as a doctoral student in this study set limitation due to the researcher subjectivity and potential bias. I maintained a reflective journal where I explored the collected data, took notes about my own challenges and uncertainties, and made comments. This reflective process provided me the space for making changes in the analysis to reflect participants’ experiences and values more closely, rather than my own. At the same time, I recognize my role as a doctoral student on the same campus as a benefit, since I was familiar with the different departments’ cultures and the physical spaces that participants referred. In addition, my multilingual and multicultural identity has helped me develop more empathy for diverse perspectives, which could position my work well within the multicultural context of higher education. This ability aligns with human-centered approach to design, which suggests the process of design begins with gaining empathy through observing and listening to stories (Stanford, 2009). However, my role within this qualitative study required ongoing reflexivity to negotiate the differences between the participants’ 99 perceptions, lived experiences, and imaginations —obtained from questionnaires, interviews, photos, notes, sketches, and prototypes— and my interpretation and presentation of those stories in ways that make sense of the research questions. I took care to use active listening skills in the interviews, which allowed me to identify whether my early interpretations of what was said reflected the participants’ perspectives. The study findings, while supported by quotes from study participants, nonetheless reflect my construction of perspectives. In the previous section, Trustworthiness, I explained my approach to design and development of this research to ensure as much as validity as possible. Also, in Sections 3.10.5, 3.11.6, and 3.12.6, I explained the involving issues and limitations in sequential phases of the study. 100 Chapter 4: Analyzing the Data 4.1 Overview of Chapter 4 Chapter 4 presents data from the sequential research phases and the findings obtained from each phase, which inform answers to the research questions of this study: 1. How do doctoral students perceive a “learning space” and its intended use(s)? 2. What is the relationship, if any, between the university’s provided learning spaces and students’ identified spaces? 3. How might doctoral students envision the future of their learning spaces? Within the framework of Design-Based Research (DBR), continuous documentation (Shavelson et al., 2003) has been conducted throughout the study to conduct retrospective and cross-iteration (Cobb et al., 2003) analysis. Doctoral students and alumni of UBC Okanagan participated in this multi-phased study; they completed a questionnaire, conducted Photovoice activities, and participated in participatory prototyping. The collected data from each phase was analyzed in order to answer the related research question, refine the needs of study, and guide the study to the next phase. The aim of this approach was to place students’ perspectives and their participation as central to the research approach. Drawing on the flexibility of DBR, certain research methods were included rather than others: questionnaires including structured and open-ended questions, Photovoice plus semi-structured interviews, and prototyping including drawings, two- and three-dimension models, and participants’ notes. The qualitative approaches overlapped in three sequential phases of the study and allowed a flexible and in-depth interpretation of the meanings and understandings. This research explored three research questions, probing doctoral students’ perceptions and experiences of their learning spaces as well as their imaginations of ideal spaces. It generated responses to the questions, and also developed an interdisciplinary theoretical framework and a methodological approach to study learning spaces in other education settings. Chapter 4 presents the finding during various stages of the research as 101 well as the analysis and reflection process. To grapple with “how” of qualitative analysis (Maguire & Delahunt, 2017), I explicitly articulate the process of analysis. 4.2. Data from Questionnaires Data from questionnaires intended to answer the first research question, how do doctoral students perceive a “learning space” and its intended use(s). Data from the subsequent phases was used as complimentary source for verification, clarification, and more explanation. The objective of the questionnaire was to reach the area corresponds to the explicit knowledge of doctoral students on learning spaces and to explore how they perceive, identify, and interact with their learning spaces. This phase corresponds to perceived space in Lefebvre’s (1991) space triad, the spatial practices, or the ordinary unconsidered experiences of everyday lives within a space. The perceived space, the various spatial practices within the built environments, are under constant changes and the usages are subjected to the social practices, experiences, and interpretations of the users. Investigating students’ explicit knowledge (what they said about their learning spaces) revealed some indications of the multi-layered definition of learning space in doctoral education and guided the study toward the next phase, where I explored students’ lived experiences of the identified spaces. The questionnaire was designed in five sections, which was explained in Section 3.10.3. 4.2.1 First section of questionnaire, demographic questions In the questionnaire, participants were asked nine demographic questions including age, program of study and department/faculty, stage of doctoral program, if their supervisor had provided a specific workspace and if yes, had they used it during their doctoral studies (Table 3.2). The questionnaire’s demographic questions were asked to help determine the certain aspects of doctoral students at UBC Okanagan. Participants’ identities were anonymous in the surveys; from the demographic section, I was only able to identify the research participants that had chosen to participate in the next phases and put their emails for future contact. 4.2.2 Data from second section of questionnaire Responses to the questionnaires were analyzed thematically. Drawing on a reflexive approach to Thematic Analysis (Braun & Clarke, 2006), patterns of meaning were identified 102 across the data. In reflexive Thematic Analysis patterns were identified through a rigorous process of data familiarization, data coding, theme development, and revision. A combination of two categories was applied to generate codes: theory-driven and data-driven/ prior-research-driven (Boyatzis, 1998; Jansen, 2010), which respectively align with deductive and inductive coding in Thematic Analysis. Considering the complexity of learning space definition in doctoral education, I had incorporated a pre-structured inventory of concepts in the questionnaire based on the related literature (e.g., Boys, 2011a; Savin-Baden, 2007; Temple, 2008). These concepts were embedded in the statements, giving clues and a context to participants about different aspects of learning spaces. Then, after each statement they had a chance to explain why they agree or disagree with the statement. To analyze the responses, I used a deductive approach of Thematic Analysis (Braun & Clarke, 2006; Nowell et al., 2017), where coding and theme development were guided by existing concepts or ideas; at the same time, I kept the coding open-ended exploring the codes emerge from the data. I also incorporated axial coding (Strauss & Corbin, 1998) to explore how the existing codes and emerging ones related to each other. To analyze the open-ended question, I drew on inductive Thematic Analysis, where coding and theme development are directed by the content of the data (Braun & Clarke, 2006; Boyatzis, 1998). Inductive Thematic Analysis took the study into unforeseen areas, which helped refine the next phase of the study. During iterative reading of data, I remained open to all possible directions emerged from the data. As Charmaz (2006) explicates, coding makes us think about the content of the data in new ways that might be even differ from the research participants' interpretations. She adds, by studying the data, the explorer can make the processes explicit, render hidden assumptions visible, and give the participants new insights. Thomas (1993) confirms that “a researcher must take the familiar, routine, and mundane and make it unfamiliar and new” (p.55). The analysis of the open-ended questions of the questionnaire was also important for guiding the development of the topics for conversations in the photovoice interviews. 103 Figure 4.1 illustrates how reflexive Thematic Analysis informed analyzing the data through inductive, deductive, and axial coding in order to develop themes. Figure 4.1. Coding strategies and development of themes drawing on Thematic Analysis The second section of the questionnaire included questions concerning participants’ perceptions of learning spaces in relation to their doctoral studies. Data from this section were tabulated for descriptive and graphical analysis by Microsoft Excel. Table 4.1 summarizes the data from second section of the questionnaire including each statement along with the participants’ responses summarized in bar charts. I considered a pictogram icon for each statement. Data from Table 4.1 will be discussed in the following sections. 104 Table 4.1 Summarized data from questionnaire’s second section Statement Bar chart Learning space is a formal setting of a classroom Learning space is the creation of specific individualized space and time for writing and/or reflection. Learning space is using social learning environments for dialogue and conversation with peers Learning space is accessing digital environments for discussion and reflection with and/or through others Learning space is a less structured and a more flexible environment for exploration 105 Table 4.1 (Cont.) Summarized data from questionnaire’s second section Statement Bar chart Learning space is physical or psychological removal from everyday experiences, for example: attending conferences, workshops Learning space is a new environment, which prompts new ways of seeing issues and challenges the current ways of thinking Learning space is a physical environment designed by architects and equipped with furniture Students can change the learning spaces within the existing spaces in order to meet their needs 106 4.2.3 What mattered most? Comparing participants’ responses to different layers of learning spaces in doctoral education illustrated in the bar charts, social learning environments for dialogue and conversation ranked the highest aspect among others. All participants gave the highest degree of importance to social learning environments, where they can meet peers and trade off ideas through productive conversation. Digital environments and individualized spaces received the next rating followed respectively by new environments to challenge assumptions, flexible spaces, attending conferences, and formal setting of the classrooms. Table 4.2 shows different aspects of learning spaces incorporated in the statements and their degree of the importance based on students’ (agree or disagree) responses to the statements. Table 4.2 Different aspects of learning spaces and their degree of importance to doctoral students in questionnaire Space Number of Agree Responses Social learning environments for dialogue and conversation 31 out of 31 participants (100%) Digital environments for discussion 28 out of 31 participants (90.32%) Individualized space 28 out of 31 participants (90.32%) A new environment, which prompts new ways of seeing 27 out of 30 participants (87.09%) flexible environment for exploration 27 out of 31 participants (87.09%) Attending conferences, workshops 23 out of 30 participants (74.19%) Formal setting of a classroom 14 out of 32 participants (45.16%) The first set of statements followed by an open-ended question asking participants whether they perceive any other spaces as their learning space other than the ones mentioned in the statements. Applying inductive Thematic Analysis, I coded participants’ responses to this question. Tables 4.3 summarizes the codes and related themes arose from the comments provided by participants. 107 Table 4.3 Codes and themes regarding additional spaces participants considered as learning space (questionnaire) Codes Theme Rest and come back to work with a fresh mind (P15) Land, water, sweat lodge, canoe, traditional ceremony, indigenous places (P 4) Nature to foster Well-being Quiet, comfortable (P1) Conducive to learning (P5) Kitchen and gathering traditional foods and medicines (P4) Access to my elders for advice and guidance (P27) Home-like A quiet room (P3) Read and take notes (P7) Meditative space/no cell phone reception (P18) Solitude and reflection Airports, gyms, etc. (P9) As an international student, any space can turn into a learning space when necessary (P14) reading or listening to an audiobook while exercising (P 37) Making space everywhere 4.2.4 Beyond physicality After the first cycles of coding, I employed axial coding to explore how the existing codes and emerging ones relate to each other, and to find bigger-picture ideas through concepts that link across the data set (Strauss, 1987; Strauss & Corbin, 1998). Table 4.4 shows the synthesis of the overlapping pre-established and emerged codes from the second section of the questionnaire. I collected and combined the pre-existing categories and the emerged codes. Data allowed dividing the codes into two main categories: physical space and conceptual space. Under each division there are three sub-categories: individual, social, and digital. 108 Table 4.4 Synthesis of pre-established categories and emerged codes into themes (questionnaire) Physical Space Conceptual Space Individual Social Digital Individual Social Digital Beyond formal physical settings (P5) Supervisor’s office (P17) Access to literature/ publications (P4, P7, P9) Outdoor spaces (P3) Meeting with supervisor (P3), a sense of support (P6) Spaces free from cell phones (P5, P15) Individualized space for writing and reflection (P16) Common/shared spaces on campus (P20) Skype meetings with supervisor (P6) Time to reflect (P26) Directed study courses with small number of graduate students (P1, P9) To tackle loneliness (P7, P5, P34) Library (P38) Library (P22) Library (P19) Walking/moving in order to contemplate and reflect (P11) To foster mood (P2) Knowing people in field, (P23) Offices for graduate students (P8) Collaborative workspace (P36) Ability to change the space over time (P4) To stimulate productivity (P1) Offers threads of ideas (P6) Any available/free space to use on campus (P 36) Needs to be designed in consultation with the graduate community (P33) Less structured space to challenge assumptions & foster creative and critical thinking (P2) To fulfill the working standards (P35) Laboratories/clinics/ hands-on practices (P 34) Move between structured and flexible spaces (P6) To share thoughts/solving problems (P14) 109 Table 4.4 (Cont.) Synthesis of pre-established categories and emerged codes into themes (questionnaire) Physical Space Conceptual Space Individual Social Digital Individual Social Digital Off-campus public spaces/ Coffeeshops (P9) psychological & emotional need (P4) Conferences/ motivating (P15) & inspiring (P33) Beyond function and aesthetics (P 10) Wherever we engage in dialogue with others (P1) Spiritual and emotional needs (P4) New environments to get new perspectives/ challenge assumptions (P2) Nature Spaces for solitude (P8) Meditative space/no cell phone reception (P4) New environments may limit learning due to stress triggers (P6) A place to "plant" one’s self (P11) To improve well-being, which in-turn impacts learning (e.g. Indigenous ceremonial learning) (P4) Wherever access new knowledge (P35) psychological &social needs (P 17) In addition to different layers of a learning space organized in Table 4.4, there were other concepts that emerged from the comments of participants in the second section of the questionnaire. Incorporating inductive approach (Braun & Clarke, 2015) and reflexive 110 iteration (Srivastava & Hopwood, 2009) assisted visit and re-visit the data, connect them with the insights and refine the themes. In Table 4.5, I summarized the additional codes that emerged from the data displaying participants’ perceptions of learning spaces. Table 4.5 Combining the emerged codes into themes: participants’ perceptions of learning spaces (questionnaire) Codes Theme Lectures/classrooms as primary source (Psychology), P6; Library (FCCS), P38; Outside box of a room (Philosophy), P35; Data collection in a laboratory, P5; Reading/studying in office (FHSD), P10; Real and virtual spaces (OSE), P3 Blended online + onsite (OSE), P3; Psychology clinic, hands-on practices (Psychology), P6; Directed study courses with a few students (OSE & SOE), P3 & P19 Discipline-dependent spaces No cell-phone place, P4; Creation of space, P4; Space needs change based on need (writing, reflection, etc.), P2; Pre-defined vs personally created/adapted, P8; Availability, P7; Modify my office, P10; Adaptability, P11; Change without impeding on other people's spaces, P8 Potential for choice Learning is more than writing and reading, P8; Many other tasks involved with learning, P6; Writing and reflection are not the only learning components, P22 Complexity of learning Walking/standing, P23; Ability to move, P11; Architects only look at function; physical needs & visual aesthetics not purpose, P4 Physically flexible Being in the mood when you write/reflect, P15; Loneliness, P1; Alone-time in writing and reading, P18; Spiritual/emotional needs, P4; Motivation, P33; Inspiration, P23; Free of emotional, psychological, and technological distractions, P5; Engaging with my Indigenous community, P4; Space for solitude, P8; One-ness feel with nature, P11; Well-being, P8; A place to "plant" one’s self, P11; Natural space to inspire, P2; Creates a positive response in an individual, P30; Could be a beach or the forest, p28 Emotional needs Well-being Missing academic community while working abroad, P6; Imperative to form a community, P2; Graduate community to stimulate productivity, P3; Getting inspired and motivated, P17; Trade off ideas, P3; Hard to engage in communities, P15; Difficult to connect with peers in PhD/lack of such community, P8; Conferences to meet people in field, P38 Graduate communities 111 Table 4.5 (Cont.) Combining the emerged codes into themes: participants’ perceptions of learning spaces (questionnaire) Codes Theme Peer-review, P2; Discussion with supervisor to conceptualize ideas, P73; Challenge assumptions/unknown bias, P2, P11; Discussing with friends in the lab/office to gain insights, P3; Meaning making in conversation, P27; Peer engagement is crucial and often missing, P34; Meetings for dialogue, P30 Peer communication Accommodating, P17; Flexible, P19; Keep you on track, P8; Fulfill the working standards, P22; Comfortable, P5; Skype meetings, P6; Having access to scientific publications, P4, P7, P9, P34; Not to be crowded by people, P10; Making the space comfortable for one's self, P34; Different sensitivities to environmental noise, P8; adaptable and reconfigurable, P4; Furniture and creature comforts to make a space usable, P14 Space Affordances Student rights to make change, P7; power inequality, P22; Policies and the support of university, P7; Agreement to change, P28; Collective consent, P9 Students’ Right Any space can turn into a learning space. P2, 4, 6, 8, 9, 12, 15, 17, 44 & 35. Any space can become a learning space. P1, P14, P10, P33, P34 & P36. Gym, airport, etc., P1 (international students); Dining table as my desk, P11 Turning a space into a place 4.2.5 General comments on doctoral students’ perceptions of learning spaces To analyze the data from the questionnaire, it was important to understand its nature as a qualitative tool not quantitative; the qualitative data was collected from a small sample of doctoral students. The statements did not intend to reflect any value-judgement, instead, the objective was to create a context for different aspects of learning spaces for participants to express their agreement or disagreement and share their ideas on each statement. The written comments by participants varied in length and complexity. Although the richness and uniqueness of the individual comments might have been lost in aggregating, to present the qualitative data in a meaningful but concise way, some aggregation of data had to occur. Consequently, findings from this section of questionnaire can only provide, at best, a general overview of student perceptions. Semi-structured interviews in the next phase provided deeper understanding of 112 students’ perceptions of their learning spaces. Data from the next phase used as complimentary data to explore participants’ perceptions of their learning spaces. 4.2.6 Specific comments on doctoral students’ perceptions of learning spaces 4.2.6.1 Discipline-dependent. Doctoral students who participated in this phase of study and completed the questionnaire came from different departments across the campus. Their perception on learning spaces and their priorities were different and discipline dependent. For example, formal setting of classroom was perceived as a “primary source” for a Psychology student while it was the last priority for an Engineering student. The consensus among doctoral student participants from different disciplines was that “learning happens everywhere”. A third-year PhD student from Health and Exercise Science (P17) clarified: [l]earning most definitely takes place in a formal classroom setting; however, much learning also takes place during visits to a supervisor’s office, during data collection as well as during independent reading/studying in one's office. Learning can really occur in any space. Identically, a third-year doctoral student in Interdisciplinary Graduate Studies in Faculty of Creative and Critical Studies (P4) said formal learning spaces were not that much influential on his PhD experience; he added: “[t]his situation does not always hold true; especially if there is no designated learning space for the graduate student. Then, the formal setting can become the supervisor's office or anywhere on campus that is available for use.” 4.2.6.2 Physical and conceptual entity. Doctoral students perceived a learning space beyond its physicality; a learning space to participants was understood both as a physical and a conceptual entity, each included individual, social, and virtual properties (see Table 4.4). Among these components, students rated social learning spaces for dialogue and conversation as the most important needed aspect reported throughout the data set (see Table 4.2). Doctoral students felt a crucial need to form and engage in graduate/academic communities and peer communications in order to “stay motivated”, “get inspired”, “trade off ideas”, and tackle “isolation” during doctoral studies. They collectively expressed that being part of scholarly communities is important during their doctoral journey. Participant 8, for example, noted that “it has been so influential to learn from others and conceptualize my 113 ideas”. Reflecting on her experiences, Participant 10 suggested, “social learning environments are very important within the learning experience. Having the opportunity for peer review as well as discussions with supervisors and laypersons were reported as “very useful” strategies in getting different perspectives and additional information (P2). Participants also found it imperative to form a community within doctoral studies, especially since there has been a lot of alone time in writing and/or reading (P18). 4.2.6.3 Individualized space. Individualized space for reading and writing was the next most frequent layer of space that students perceived as their learning space during their PhD experience. It has been an “important” space during their studies since they spent a lot of time writing, thinking, and analyzing. Except three participants, among thirty-eight, who were satisfied with the offices that they were provided by their departments or their supervisors, other participants expressed their dissatisfaction about not being provided a space or a desk or the quality of their individual spaces. 4.2.6.4 Digital space. Quality internet and digital spaces in order to access the literature and publications of the field was reported frequently as a learning space for doctoral students (P4, P7 & P9). A participant in second year of IGS program (P4) noted: [i]n today's age we have access to billions of other people and their thoughts, opinions, and knowledge we should be able to access that without restriction. For example, I know of only one other person in the world doing the same or similar work I am doing. If it weren't for digital environments, we never would have known of each other. Participants, however, did not perceive or use virtual spaces to create communities to discuss with peers. They only mentioned that they used Skype for meetings with supervisors whenever one of them were not available on campus (P6). There were even participants who found it difficult to engage in virtual discussions and prefer face to face conversations; they believe “digital threads can only offer learning spaces where threads of ideas might be woven 114 through reflection” (P8). I have to mention that questionnaires were distributed and analyzed in pre-COVID-19 time, when virtual spaces were not used as much as in COVID time. 4.2.6.5 Well-being. Emotional needs and well-being of students were imperative factors that must be considered in learning spaces according to students’ comments. Having access to “spaces for solitude” (P8), “engaging with their Indigenous communities” (P4) and having a “one-ness feel with the nature”, (P11), and “free of technological distractions” (P5) were experiences that students found helpful to boost their well-being. 4.2.6.6 Affordances. Offering/action possibilities in the environment were reported as elements of students’ perceived learning spaces. Affordances which provide students with flexibility and comfort, included access to kitchenettes (P4), natural light (P2), free Wi-Fi (P1, P3, P4, P5, P8 & P10), writing surfaces, and sofas. Participants of this study valued comfort (P3, P1, P7, P12, P14) in learning spaces and the necessary affordances such as Wi-Fi, ease of access to furniture and above all, “a friendly and reconfigurable space” (P2). 4.2.6.7 Potential for choice. Participants preferred potential for choice; emphasizing the complexity of learning, they tended to see a learning space as a changing entity. They were interested in flexibility of the spaces in order to reconfigure them themselves based on their changing needs. International doctoral students claimed they have learned to turn any space into a space for learning. Drawing on students’ perceptions, the notion of learning space is a maze of different spaces that is continually unfolding and changing based on different situations and needs, which make them grapple to navigate and negotiate with the provided opportunities. Participant 2 explained, The main characteristic of a learning space, for me, is it's adaptability: as everyone's experience and needs are different, their approach to physical, mental, and digital spaces is necessarily different and might require different uses which may be individual without impeding on other people's spaces. Another doctoral student (P19) added, Within the context of doctoral education, it must be accounted for that learning takes place across a wide range of forms of interaction and activity. Each of these spaces in 115 questions 10-18 provide the diversity of opportunities required for growth through a combination of experiential, contemplative, and challenging learning environments. 4.2.7 Data from third section of questionnaire The third section of the questionnaire comprised statements concerning participants’ experiences with UBC Okanagan’s spaces in relation to their studies. This set of statements in combination with the campus map inventoried the existing spaces on campus. They gave participants an opportunity to reflect on UBC Okanagan’s different spaces. The bar charts in the following page summarize the data from each statement in this section of the questionnaire. Data from this section was used as a first move to transition into the next phase and as an additional data to the interviews in Photovoice phase, where I explored how doctoral students interact with UBC’s provided spaces. Since there was little chance for commenting on the statements by participants in this section, it was hardly possible to make meaning of the data without participants’ comments of why they agree or disagree with the statements. I included an open-ended question at the end of this section to provide participants an opportunity to add any comments regarding the UBC Okanagan spaces in relation to their PhD experience. This was an issue related to questionnaire design that I identified in the analysis process. This issue was somehow resolved with the participants who participated in the semi-structured interviews in the next phase. In the interviews, I referred to the questionnaires and asked participants for more explanations when needed. Figures 4.2- 4.14 summarize the data from questionnaire’s third section statements, which are discussed later. 116 Figure 4.2 Classrooms have been the most important learning spaces during my studies. Figure 4.3 Most of my learning takes place in the labs, which are typically assigned to a specific department or program. Figure 4.4 Campus library is a motivating learning space. Figure 4.5 I have found the Graduate Collegium a productive learning space Figure 4.6 Bookable Student Study Spaces on campus (for example in EME building) have been useful as individualized spaces for writing and reflection. Figure 4.7 The graduate office provided by my supervisor/program has been an important space in my PhD program. 117 Figure 4.8 I prefer doing my studies off campus in informal spaces such as coffee shops Figure 4.9 I would rather work from home whenever it is possible. Figure 4.10 If I have access to a quality internet and online resources, I can be anywhere to do my work. Figure 4.11 Social spaces that foster conversations with scholarly communities have been important during my PhD experience. Figure 4.12 I have done [part of] my PhD in an interdisciplinary environment interacting with peers from different backgrounds and I have found it productive. Figure 4.13 Being a member of a wider scientific community on campus has helped me dealing with isolation in my PhD Figure 4.14 Available physical spaces on campus have been sufficient and helpful to conduct my PhD. 118 4.2.8 What needed most? Comparing the bar charts, which represent usage of different types of spaces, social space captured the most attention through agreement of participants to the suggested statements with twenty-five out of thirty-one participants. It followed by having access to a quality internet and online resources with twenty-three out of thirty-one participants. Doctoral students agreed (in different levels) that providing social spaces that foster conversation with scholarly communities is an important component of learning space in doctoral studies. At the same time, in the comments, they complained despite the importance of such social spaces, engaging in such social spaces and scholarly communities has not been part of their PhD experience. Participants also declared if they have access to a quality internet and online resources, they can be anywhere to do their work. Graduate offices provided by departments or supervisors obtained the next frequent use of space as an important learning space in their PhD journey. Twenty-two out of thirty respondents agreed that the graduate office provided by their supervisors/program has been an important space in their PhD experience, whereas twenty out of thirty-one participants disagreed that available physical spaces on campus have been insufficient. Table 4.6 demonstrates the statements of Section three along with participants’ agreement to each statement, which are arranged in order from the highest to lowest degree of agreement. 119 Table 4.6 Participants’ degree of agreement with the statements in the third section of the questionnaire Statement Participants’ agreement Social spaces that foster conversations with scholarly communities have been important during my PhD experience. 25/31 If I have access to a quality internet and online resources, I can be anywhere to do my work. 23/31 The graduate office provided by my supervisor/program has been an important space in my PhD program. 22/30 I would rather work from home whenever it is possible. 21/31 I have done [part of] my PhD in an interdisciplinary environment interacting with peers from different backgrounds and I have found it productive. 20/31 Most of my learning takes place in the labs, which are typically assigned to a specific department or program. 17/30 Being a member of a wider scientific community on campus has helped me dealing with isolation in my PhD 17/30 Campus library is a motivating learning space. 17/31 I have found the Graduate Collegium a productive learning space. 14/30 Classrooms have been the most important learning spaces during my studies. 14/31 I prefer doing my studies off campus in informal spaces such as coffee shops. 14/31 Available physical spaces on campus have been sufficient and helpful to conduct my PhD 11/31 Bookable Student Study Spaces on campus (for example in EME building) have been useful as individualized spaces for writing and reflection. 11/29 In an open-ended question included in this section, I asked participants to add any comments or ideas that they had on their learning spaces on campus. Responses to this question were used as a starting step to analyze the qualitative data regarding how doctoral students use and interact the university’s provided spaces; participants’ photographs along with the interviews in the next phase, Photovoice, added more detailed explanations to these comments and assisted answering the second research questions, the relationship between the university’s provided spaces and students’ identified learning spaces. 120 Table 4.7 organizes the codes emerged from the comments along with the themes that clustered the codes together. Table 4.7 Comments on UBC Okanagan’s learning spaces, participants’ experiences (questionnaire) Codes Themes More consideration of isolation in PhD students, P7; Working mostly from home, which is isolating, P18. Isolating work from home Inconsistent Wi-Fi connection, P3; Desks are not assigned, P9; Different stages of research require different spaces of learning, P19; It is important to have a range of spaces, P20; A physical space to map out ideas on a wall, P8; work with two monitors…can’t move all this stuff to EME bookable rooms, P5 Space affordances Graduate Collegium is lovely but loud for work, P7; Graduate Collegium and Platypus are my “go to” spaces, P4; ‘social’ space provided is far and isolated from active engagement with peers, P16; Social spaces are inadequate/ they are spread out across campus/ aren't very conducive to building community, P3; Social spaces have not been a part of my UBCO experience, P2 Not conducive to build communities Spread out/ far from department Isolated Loud for work Not provided Privileged to have a shared office, P6; Access to many spaces depending on the season, P8; Terrible shared office, P1; Not enough ventilation in grad office, P1; Overcrowded shared office, P5; A lot of distractions in office, P9; The graduate office as an important space in my PhD, P10; A big hurdle in my creativity as it is overcrowded and noisy, P13; Working from home is not workable because of simultaneous lab work, P18; Working from home because of inadequate graduate office, P20 Graduate office problems Noise, ventilation, distracting, overcrowded, not provided by department/supervisor Improving library for graduate students, P12; Library: busy, noisy to be productive, P19; Inconsistent Wi-Fi connection in library, P18 Library space for graduate students Figure 4.15 shows doctoral students’ use of space distribution at UBC Okanagan’s campus. The green dots reflect the areas that participants used the most. Among thirty-eight participants in this phase, ten participants came from Engineering and six students were from 121 the OSE. It made sense that EME building (graduate offices of Engineering and Education) obtained the most frequent use of space based on what participants commented on Question 34, prioritizing the spaces that they have most used during their PhD. Students who came from the FCCS and IKBSAS, and were provided with graduate offices, also mentioned their offices as the spaces that they most used during their doctoral studies. Library and the Graduate Collegium obtained the next level. Participants mentioned that they use library for research and occasional study when it is not too busy otherwise, they work from home. Participants’ comments also revealed that they tended to use the Graduate Collegium mostly to get together, eat, take naps, and rest (P3, P4, P7, P16). There were only two participants that used the space for reading and writing (P1, P4). At the time that I was collecting data the Commons building was launched, and participants of this study might not have been aware of the space that specifically provided to graduate students; only one participant mentioned that she used this space for reading Figure 4.15 Campus Map in Question 34 to prioritize the usage of the spaces by participants 122 4.2.9 Comments on doctoral students’ experiences of learning spaces 4.2.9.1 Social space. Social spaces that foster conversations with scholarly communities have been rated as the most important component of a learning space by doctoral student participants while they complained engaging in such spaces has not been necessarily part of their PhD experience. The problems they mentioned included: spaces are not conducive to build communities (P5); social spaces are spread out/far from department (P3) and they are loud for work (P7); and the problem of being isolated from active engagement with peers (P16). 4.2.9.2 Individual space. Individual spaces and students’ homes were the next most frequent spaces by students. Likewise, it did not mean that all the participants were provided with individual workspaces; there were problems regarding individual offices/spaces that will be more discussed in the in-depth interviews. There were also participants who felt privileged and appreciated the provided shared offices by their supervisors/departments. They said they felt isolated mostly when they had to work from home. 4.2.9.3 Library. There were also issues related to the library, which has been used as a learning space. Participants who used the campus library requested to improve the library to better meet the needs of graduate students; they found it busy and noisy to be productive with inconsistent Wi-Fi connection. 4.2.9.4 Affordances. Similar to the previous section, affordances were mentioned as important components of a learning space based on students’ experiences. Participants believed that different stages of doctoral study require different spaces for learning and as a result, it is important to have access to a range of spaces on campus. The need for individual assigned desks and walls/surfaces to map out ideas were mentioned. In the Photovoice, the emerged elements from this phase were discussed with participants, which will be reported following the questionnaire analysis in this chapter. 4.2.10 Data from fourth section of questionnaire The fourth section included two open-ended questions concerning participants’ ideals and imaginations on the future learning spaces. Responses to these questions were used as a beginning step to explore how doctoral students envision learning spaces appropriate to meet 123 their needs. Data from this section of the questionnaire provided an incipient identification of the areas that explored in participatory prototyping, third phase of the study. To analyze these open-ended questions, I drew on inductive Thematic Analysis, where coding and theme development are directed by the content of the data (Braun & Clarke, 2006; Boyatzis, 1998). It took the study into unforeseen areas and identified some areas of exploration for participatory prototyping in the third phase, where participants were invited to imagine the learning spaces for doctoral education. During iterative reading and coding of data, I remained open to all possible directions emerged from the data. Table 4.8 categorizes the emerged codes from this section of the questionnaire, which were clustered into themes. Table 4.8 Codes and themes from section four of questionnaire, participants’ ideals and imaginations Codes Themes Less isolated, P13; Less exclusive collegium, P5; Fluidity of dialogue, conversation, and research trajectories over a long period of time, P3; Spaces for dialogue and working together P1; Isolation and lack of interaction with peers, P5; Communal space in ARTS; Creating social spaces that students across the campus can communicate, P22; A faculty-specific common space dedicated to less formal work or relaxation, P15; A faculty-specific area, P7; One can speak, debate, without disturbing people trying to work, P2; A common area for socialization, P20; `Collaboration for creativity, P4; Inviting, centralized spaces to prevent the idea of working in silos, P3; Casual and relaxing spaces to share our ideas, P18; Conducive to building community, P9 Faculty-specific social spaces Open for discussion with other PhD students, P4; Spaces for interdisciplinary and collaborative work, P7; Multi-disciplinary space, P11; Communal, transdisciplinary, P22; Places for interdisciplinary dialogue, P2 Interdisciplinary space on campus Silent spaces/ quiet offices/ personal offices P14; Isolation for focus/ own space, P3; Individual, private/more private office, P1; small office with one or two students not with 20 students, P5; Less disturbance and distraction, P8; Private/no disturbance, P19; Fewer student crammed into tiny offices, P11; Less populated and quiet offices, P12 Private and quiet spaces 124 Table 4.8 (Cont.) Codes and themes from section four of questionnaire, participants’ ideals and imaginations Codes Themes A humble building near nature, P3; Windows onto the mountains and trees, P2; View of trees, windows, P19; Nice view, P8 Interaction with natural environment Ventilation and A.C. in office, P32; Nice lighting, P3; Better phone reception, P24; Fully supported with all IT facilities, P28; Good quality internet, P2; Room to store/prepare food, P29; A kettle and even a coffee machine, P30; Access to fresh water, P3; Comfortable to work in for long periods of time, P16; Well equipped (desk, computer, comfortable chair), P4; Own desk in a common faculty-specific workspace, P25; Well-designed working furniture, P1 Affordances More availability of learning spaces, P23; More availability of learning spaces for graduate students in the FCCS, P4; Accessible; Grad student space in the library, P32 Availability/Accessibility More open and configurable interiors, P4; Customizable, P20; Flexible, P33; Open concept office space, P18; Physically connected to the activities of the discipline (ie: Visual Arts), P7; Flexible working spaces, P16; A continual and easily transitional environment between modes of engagement, P19; Like having a house inside a building, P5; Continuity of space, P18; I could write and leave my research materials in place, P9 Configurable/Customizable interiors 4.2.11 Comments on doctoral students’ ideals and imaginations of learning spaces Doctoral student participants aimed to have more available learning spaces on campus for graduate students; these spaces included private and quite spaces, a specific space for graduate students in the library, a specific social space within each faculty/department, and interdisciplinary spaces on campus to promote conversation among doctoral students across the campus. Participants imagined configurable and flexible interiors where they can change them and make spaces that better meet their needs. Participants agreed that they can make some changes to their learning spaces to better meet their needs; Participant 5 believed “since needs and experiences of people are different, their approach to use the spaces is different too”. However, they pointed out the restrictions of making changes within the spaces; they explained that “individual adaptability should be without impeding on other people’s spaces” (P3) since they believed spaces “are available to 125 the collective rather than individual” (P9). People have different sensitivities to environmental circumstance; as a result, agreement to change requires collective consent. Two respondents raised another restriction in relation to “students’ rights” (P7) and “power inequality” (p22) to make any fundamental changes in their learning spaces. 4.2.12 Reviewing/Refining the themes on doctoral students’ perceptions Through reviewing the themes (Braun & Clarke, 2006) in a recursive approach, I checked the candidate themes against the dataset in order to gain as much insight as possible and determine that the themes tell a story of the data, that ultimately answer the research question. In this step, themes were refined, split, combined, or discarded. As Braun and Clarke’s (2006) remind, themes should be defined as pattern of shared meaning underpinned by a central concept or idea. Themes from Tables 4.5 (perceptions), 4.7 (experiences), and 4.8 (ideals) were reviewed, refined, and combined into areas for discussion and exploration. Table 4.9 categorizes the themes arose from the data set in the first phase and the preliminary areas related to experiences and ideals of students, which guided the study to proceed to the next phases, Photovoice and participatory prototyping. The main areas related to doctoral students’ perceptions of learning spaces emerged from clustering the themes included: perceiving space beyond its physicality, being able to turn a space into a place, the importance of configurability of space, the need for interconnected scholarly communities, having access to spaces that foster well-being, and the importance of being provided with a personal space on campus. These areas will be discussed in the next chapter. In addition, students’ explicit knowledge (what they said about their learning spaces) revealed some indications of the multi-layered definition of learning space in doctoral education and guided the study toward the next phases, where I explored students’ experiences of the identified spaces and their imaginations of the ideal spaces. Photovoice reflected the objective aspect of learning spaces and data form this provided answers to the second research question, which explored the relationship between university’s spaces and the students’ identified spaces. As a complementary set of data to the questionnaire, it also provided an in-depth understanding of how doctoral students perceive, understand, and acknowledge learning spaces as they relate to their studies. Table 4.9 shows the refined 126 themes which provide areas for discussion and responses to the research questions based on data from questionnaire. Table 4.9 Refined themes and areas for discussion and exploration (data from questionnaire) Research Question Themes Areas for discussion/exploration First research question Perceptions Beyond formal physical settings; A conceptual space unique to each person; Access to literature/ publications; New environments to get new perspectives/challenge assumptions; Meeting with supervisor Beyond physicality of space Making space everywhere; Turning a space into a place; Potential for choice; Turning a space into a place From space to place Configurable/customizable; Physically flexible Affordances; Home-like Configurability Graduate/academic communities; Interdisciplinary space on campus; Faculty-specific social spaces; Peer communication A nested community of practice Solitude and reflection; Emotional needs; Nature; Less isolated; No cell phone reception; Foster “mood; A place to "plant" one’s self; Indigenous ceremonial learning Well-being Solitude and reflection; Private and quiet spaces; Offices for graduate students Personal spaces 127 Table 4.9 (Cont.) Refined themes and areas for discussion and exploration (data from questionnaire) Research Question Themes Areas for discussion/exploration Second research question experiences Isolating work from home; Isolated Dealing with Isolation Not provided offices; Distracting; Overcrowded Need for personalized Spaces Space affordances; Ventilation, Furniture/comfortable chairs; Loud for work Need for Affordances Not conducive to build communities; Spread out/ far from department Need for Community Third research question Ideals Students’ Right to change spaces Students’ Right to change Faculty-specific social spaces; Interdisciplinary space on campus Communities of practice Private and quiet spaces Personal spaces Configurable/Customizable interiors Configurability of space Interaction with natural environment Space to promote well-being 4.3 Data from Photovoice Data from Photovoice supported answering the second research question, the relationship between the university’s provided spaces and students’ identified learning spaces. This phase aimed at reaching the areas connected to students’ tacit knowledge on learning spaces and how they use the existing provided spaces in everyday basis. It also corresponds to conceived space (Lefebvre, 1991), the conceptualized space by planners 128 which attempt to describe patterning of the social in space. Lefebvre (1991) argues that inhabitants make spaces by living in them explaining [t]he user’s space is lived – not represented (or conceived). When compared with the abstract space of the experts (architects, urbanists, planners), the space of the everyday activities of users is a concrete one, which is to say, subjective….[it is] a space of ‘subjects’ rather than of calculations (p. 362). Photovoice aimed at capturing students’ experiences within or beyond university’s provided spaces. Through Photovoice, in the second phase of this study, students constructed what mattered to them through taking photos and reflecting on them. Wang (1999) states that Photovoice enables people to define issues for themselves and others; what is worth remembering and what needs to be changed. As a knowledge creation process, participants were placed in a position to engage in critical reflection and determine their own definitions of learning spaces, which arose from their photos and the subsequent interviews. Photovoice is used to empower participants for social change (Wang & Burris, 1997; Wang, 1999; Wang, Yuan, & Feng, 1996). The intent of this project was not to create change immediately; it created an avenue for change through providing an opportunity for students to address the problems and formulate new visions for the future in a participatory manner, which can lead to more understanding and ultimately to change at UBC Okanagan’s future strategies. The Photovoice process seemed to promote awareness in relation to their learning spaces among participants. One participant (P5) commented on how the process made them aware of learning space, noting, “…talking about it has definitely caused me to think about it more and choose my spots more mindfully and more appropriate to what I want to do.” Participants had different ideas about experiencing the Photovoice process. One of them (P7) described that she was not sure about how she wanted to show his learning spaces. She explained “at the beginning of this project, it was very slow for me. I kept asking myself what my learning space is and how can I show it.” Learning space is a concept that can be hard to define for doctoral students. Participants needed to have a safe place to think about this concept and reflect on their own experiences within learning spaces. One of the participants (P9) said that she enjoyed this research because she could express her ideas 129 about the issues that doctoral students had with learning spaces. She stated “I felt that we were in control of what we wanted to say and what we wanted to achieve…. when we enact our agency, learning is more engaging.” Investigating students’ explicit and tacit knowledge (what they said and what they did in the questionnaires and Photovoice) revealed some indications of the multi-layered definition of learning space, captured students’ experiences in relation to their learning spaces in doctoral studies, and guided the study toward the next phase, where I explored students’ imaginations and ideals for the future of their learning spaces. 4.3.1 An eclectic approach to analyze the data from Photovoice Brunsden and Goatcher (2007) note that “[o]ne issue that arises with previous studies utilizing the Photovoice technique is a lack of clarity regarding the analytic process used on the data” (p. 47). Agreeing with this argument, Hergenrather et al. (2009) explain that word data generated through Photovoice projects are “analyzed like other qualitative data, through codifying data, and exploring, formulating, and interpreting themes” (p. 688). The lack of analytical specificity offered within most extant Photovoice literature leads researchers to look outside the methodology when deciding to analyze data (Latz, 2017). Given that this phase explored experiences of doctoral students expressed through their photographs and explained in the interviews, a combination of multiple techniques was applied in analyzing the data: reflexive Thematic Analysis (Braun & Clarke, 2006) as a general strategy as well as reflexive iteration (Srivastava & Hopwood, 2009) as a complimentary applied strategy to analyze the transcript data from the individual dialogue sessions. From an art-informed approach (Capous-Desyllas & Bromfield, 2018), the process also included the creation of collages/infographics as a technique to “conceptualize a phenomenon by fleshing out different facets in order to get a nuanced understanding of it” (Butler-Kisber & Poldma, 2010, p. 4). Borrowing Capous-Desyllas and Bromfield’s (2018) major levels of analysis, data from this phase was analyzed through three levels: 1) an analysis of each participant’s transcript, 2) a cross-case analysis comparing all transcripts together, and 3) creating visual art to gain a deeper understanding of the transcript data and corresponding photographs. As a 130 guideline, Tinkler’s (2013) proposed steps in analyzing the photo-elicitation interview have been considered, which include: Look (What do participants see?); Contextualize (How to the photos fit into the participants’ lives?); Listen (What is said? What is not said?); Juxtapose (How does the talk compare to the visual?); Watch (How to the participants interact with the photographs?); and Trace (In what ways is the total narrative irreducible to the discrete narratives based on individual photos?). Tinkler’s (2013) suggestions imply a non-participatory approach to analysis which aligned with the circumstances of the study since the participants were not all interested to be involved in the analysis process. Sutton-Brown (2014) clarify participants in Photovoice should be actively involved in the research process as feasible depending on what the circumstances allow. As said, the method of analysis chosen for this phase was a hybrid approach of qualitative methods (Fereday & Muir-Cochrane, 2008) in Thematic Analysis; it incorporated the data-driven inductive approach, the deductive —a priori template of codes approach—, along with latent approach in Thematic Analysis. This approach complemented the second phase by allowing the tenets of existing ideas from the previous phase and the literature to be integral to the process of deductive Thematic Analysis. It also allowed the themes to emerge directly from the data using inductive approach and the underpinning assumptions to come out through latent approach. 4.3.1.1 Coding the data. As the first step of coding, I looked for the fit of my conceptual framework with the interviews to determine if these would be useful and informative data to gain understandings about my second research question, the relationship between the university’s provided learning spaces and students’ identified learning spaces. I began with deductive analysis as I coded the interviews using the main categories from the previous phase: individual, social, and digital spaces. Through deductive approach in Thematic Analysis (Braun & Clarke, 2006; Nowell et al., 2017), I used the existing 131 concepts to guide development of new codes and themes, while I kept coding open-ended to explore the emerging codes from the data. Table 4.10 illustrates the deductive analysis of the transcripts. Through the reading and coding of the data, I began to see a strong fit for these codes in this initial data and determined that this data set would be useful for providing insights about students’ experiences within the provided learning space. The deductive analysis process allowed me to return to questionnaire’s findings and the literature and to engage in theorizing and sense-making in order to further understand what I was learning from the data. The aim of using iterative rounds of analysis was to develop deep and rich insights and understandings of participants’ experiences to guide new theorizing about phenomenon being studied (Charmaz, 2006; Saldana, 2013). Table 4.10 Codes and themes from the deductive analysis of the interview transcripts Individual Space Social Space Digital Space Not having a private space, P1, P2, P7, P8 Creating community with small group of people, P1 Creating casual social spaces on WhatsApp, P1 Working at home after 5pm, P4 No funding, only by students’ contributions Sharing/enjoying, P2 Hard to engage in discussions, P3 Locked door/ No distraction, P6 Sunshine café as get-together space for lunch, P8 Online writing club, P8 A space to concentrate & reflect, P3, P4, P6, P7 Collegium is not convenient for conversations, P2 Rarely deep discussions in course blogs, P8, P3 Not having an opportunity to personalize the space and feel belonged, P1, P6, P4 Potential for small conversation, P7, P6, P11 UBC online library, P1, P5, P11, P10 Intimate private space, P3, P11 Potential for random informal yet productive conversation with people from the department, P7, P11 Opportunity for multi-tasking, P2 132 Table 4.10 (Cont.) Codes and themes from the deductive analysis of the interview transcripts Individual Space Social Space Digital Space Lack of office space, P8, P1, P8, P6, P9, P10 Accommodate different people, P1, P4, P9 Limited use of online space for collaboration, P4 Not having access to bookable, P10, P1, P8 Spaces not accessible, P6 Supervisor’s front porch, P3 Comfortable adjustable furniture, P11, P3, P11, P6, P10, P9 Challenging research site, P3 Having OWN space, P8, P1, P3, P2, P7, P11 Not being seen, P7 Sketch noting/hearing impairment, P3 Use of marginal, in-between spaces, P7, P2 Cozy home-like space equipped with appliances, P11, P7 Portable standing desk, P3, P8 Having blankets, food and tea available in that office, P4 Moving around campus to find space, P1 Going to Starbucks/ people sitting nearby motivate me to study for longer period, P10, P1, P5 Home-office space, P11, P2, P8 Feeling belong/ Reminders of who you are/ desks show our personalities, P1, P4 plants that need sunlight to thrive, P4 Considering the potentials for well-being spiritual fulfilment Blanket by indigenous Peoples, P4 Visual/ aesthetics stimulators Basic small space at home (international students), P1, P2. P4, P5, P8, P9 Learning walks, P11 Staying late on campus for deadlines (international student), P1 Not having a supportive community/ Loneliness, P1, P9 133 Table 4.10 (Cont.) Codes and themes from the deductive analysis of the interview transcripts Individual Space Social Space Digital Space Long hours at home makes me down/ keep at-home work to a minimum, P8 I need people around me when I am working, P9 Nervous/Discouraging when feel I don’t have a space on campus, P1 Grad students are last priority in spaces, P9 Having a space to claim, P2 Equipping the marginal, in-between spaces, P7 Displacing students, P1 Safe space for discussion/ Space for trial and error, P3 Focus on functional more than socializing, P7 A hub with facilities, p4 Reconfigurable, P2, P4, P7, P9, P11 Potential for choice, P7 Need for social spaces within the department, P2, P8 Social negotiation to make a space, P11 Feeling of support and mutual understanding, P11 4.3.2 An analysis of each participant’s transcript Focusing on one participant at a time, I read each transcript with attention to the related photo(s) to generate codes and themes. Borrowing from Thematic Analysis, I used inductive and latent analysis approaches identifying patterns in the data by iterative cycles of coding. Latent approach helped me identify the underlying assumptions and conceptualizations that shaped the surface data. It guided the interpretation reflecting the concepts and assumptions that underpin the data. Braun and Clarke (2006) clarify “for latent Thematic Analysis, the development of the themes themselves involves interpretative work, and the analysis that is produced is not just description but is already theorized” (p. 84). To organize the individual transcripts into a set of data that I could analyse, I began the inductive analysis process through iterative rounds of descriptive coding, which summarizes in a word or a short phrase (Miles et al., 1994; Saldana, 2013). The initial codes in Table 4.11 demonstrate the emerged codes from iterative reading of each transcript. Given 134 the interpretive and reflective nature of analysis, I constantly reflected on what I was reading in the transcripts throughout the descriptive coding process to focus my attention on understanding the meaning of the participants’ stories, not just focusing on the words they used (Saldana, 2013). Through the interpretative understanding and sense making of what participants were sharing with me, I also tried to reflect on my interpretations that were likely being guided by the emerging aspects that I was bringing to the process (Charmaz, 2006); my perceptions and experiences of learning spaces as a doctoral student, my previous beliefs about participants’ perspectives, and my own understandings and beliefs about learning spaces all contributed to my interpretations. 4.3.3 A cross-case analysis comparing all transcripts Cross-case analysis of all transcripts allowed me to examine, pinpoint, and record similarities within the data set in order to organize them into themes (Braun & Clarke, 2006). Themes, which were patterns that found across the data set, were directly associated with the research questions, and became categories for analysis (Fereday & Muir-Cochrane, 2008). After conducting initial coding, axial coding as a second cycle method was employed to find bigger-picture ideas through concepts that link across the data set (Strauss, 1987; Strauss & Corbin, 1998). Saldana (2013) clarifies axial coding “describes a category’s properties and dimensions and explores how the categories and subcategories relate to each other”. Through axial coding (Table 4.11), I explored how the initial and emerging codes relate to each other within the data set in order to build a thick summary of the data (Saldana, 2013). 4.3.3.1 Thematizing. DeSantis and Ugarriza (2000) suggest that the term theme is often used interchangeably with such words as category, domain, phrase, unit of analysis, and others. Ultimately, they propose a more stable definition based on their content analysis: “A theme is an abstract entity that brings meaning and identity to a recurrent [patterned] experience” (p. 362)”. Auerbach and Silverstein (2003) confirm this definition declaring a theme categorizes a set of data into “an implicit topic that organizes a group of repeating ideas” (p.38), which leads to the development of higher-level theoretical constructs when similar themes are clustered together. Figure 4.16 shows how inductive, deductive, and latent 135 Thematic Analysis informed individual transcripts and axial coding linked the codes across the data set in order to develop themes. Transitioning beyond initial coding to categorization across the data (Saldana, 2013), the data analysis moved from real to abstract and the analysis evolved from codes to themes. The transition occurred through the labelling of codes, the development of categories from multiple codes as they are compared to each other. Through the initial descriptive coding process, the data was grouped into different codes. Reading through the coded data, I noticed patterns beginning to emerge as I organized and re-organized the data. The categories I created from the codes describe the data collected, but also convey my interpretations of the data. For instance, I clustered data together coded as “creating a community with five fellow students in the lab”, “shared office with fellow graduate students”, “feeling support and mutual understanding”, “losing motivation working from home”; I interpreted it as doctoral studies as a journey together. According to Saldana (2013), there is not assumption with qualitative data analysis that the researcher will “get coding right”, and so it is necessary to approach categorization with a flexible mindset and leave space for new connections and “families” to be formed (p. 10). Figure 4.16 Coding strategies in Photovoice analysis drawing on Thematic Analysis Table 4.11 represents initial codes emerged from iterative reading of each participant’s transcript along with the axial codes linking the codes across the data set, which are categorized into themes. 136 Table 4.11 Themes developed from codes: individual transcripts and cross-case coding/thematizing (interviews) Initial Codes Axial Codes Themes Too many students in an office, P9 Displacing students, P1 Prioritizing students, P9 Squeezing students, P5 Distracting office space, P1 Go from building to building, P9 Lack of office spaces Lack of office spaces Not having the “own” space, P7, P8, P1 Locked door no distraction, P6 You are not in anybody’s space, P7 The majority of everything that the university can offer, P11 No longer concentrate when s.b else at home, P8 Lock my phone in a cupboard, P11 No distraction Having own space Opportunity to multi-tasking, P2 Cooking while working, P4 Kitchen table with nice natural view, P11 Access to online resources, P1 Work from home Access to virtual spaces from home No personalized space to feel belonged, P1 Looking for a space, P2 Stuff that aren’t mine, P2 A poem on the wall, P1 Favorite candies on desk, P5 Making “my” space, P7 Personalized space Sense of belonging having own space Natural light/window, P5 Walking pedagogy, P11 Lying down on lawn when read something, P8 Close to nature Promote well-being 137 Table 4.11 (Cont.) Themes developed from codes: individual transcripts and cross-case coding/thematizing (interviews) Initial Codes Axial Codes Themes Making a space under the stairs, P7 Nobody sees you, P9; Nobody is behind you, P2 Quick informal conversation on coach, P7 Limited and relaxed enough, P1 Feels homy, P11 Comfortable, quiet convenient home office, P8 Cozy space Home-like Intimate spaces Creating a community with 5 fellow students in the lab, P1; Shared office with fellow graduate students, P11 Feeling of support and mutual understanding, P11 Losing motivation while working from home, P8 Sense of community A journey together Small conversations, P11 Bringing appliances from home, P9 No funding to buy microwave/kettle for lab, P1 Bringing tea/coffee for research group, P1 Indigenous thinking: things are shared in a circle, P7 Sharing/making space Sense of community Working from home when no need to come to campus, P10 Working from home to reduce long commutes, P1 Working from home/bus schedule limits, P2 Working from home is not convenient, P8 Prefer campus over home Campus preference Nice comfi chairs, P7 Adjust the chair till I get it right, P10 I really need a comfortable couch, P8 Comfortable/ adjustable furniture Adjustability Discouraging space issues, P1 Space as indicator of support from program, P9 Feeling ignored/not having a space on campus, P1 Feeling ignored Space as indicator of support I can do different tasks/I don’t need to go anywhere, P7 Alter the space to your needs, p4 Furniture not conducive to moving around, P7 Let me pick and choose, P7 Ability to re-arrange my space, P3 Good pedagogical spaces give people options, P11 Potential for choice Reconfigurability 138 4.3.3.2 UBC Okanagan’s spaces. Doctoral student participants also shared their experiences and insights regarding the existing spaces on UBC Okanagan’s campus including the campus library, bookable spaces, graduate offices, Commons (new building on campus with spaces provided to graduate students), and graduate Collegium as well as off-campus spaces and students’ homes. I summarized their ideas in Table 4.12 and discuss the findings in the next chapter. Table 4.12 Doctoral students’ experiences in existing spaces, data from interviews Graduate offices Squeezing too many students in an office, P5; Displacing students several times, P1; Lack of space, P1, P2, P7, P8, P9; Not having private and/or personalized space, P8, P9; No windows/natural light, P5, P9; Not having access to microwave/kitchen, P2; Distracting/overcrowded, P1; Not having a space/desk to claim, P2; Discouraging when not having a space, P1 Campus library Not suitable for long time, P6; Overrun with undergrads, P7; Graduate Collegium Far away, P1; Noisy, P11; Not conducive to learning, P2; Needs constant clean up, P10 Bookable spaces Not available/accessible in fall-winter time, P1, P2, P11, P8, P9; Almost booked by undergraduate students, P2, P7 Commons Not being used, P2; Facing mountains in Commons is productive, P2; They promised a grad student space and it ended up with a tiny space, P7; Conference rooms are functional and spacious, P3 Home Prefer to come to campus/need to be surrounded by fellow students, P9; Writing at home because it is quiet, P10, Not having a proper home office, P1, P2, P4, P5, P8, P9, P10; Basic home space, P2 Off-campus Work in cafes if they have no other choices, P9, P5; Outdoor public spaces for reading, P8; Supervisor’s front porch, P3; Overseas research site, P3 4.3.3.3 If you can change one thing. Data from interviews also included students’ rough ideas on how the ideal doctoral learning spaces might look like. In the last question of the interviews, I asked participants if they can change one thing in their learning spaces, what would it be? Responses to this question guided the study to the next phase identifying the main areas of exploration in participatory prototyping, where I explored students’ 139 imaginations and ideals. Students ideals and their envisioned changes within learning spaces emerged from this phase included: - Creating private and quiet spaces; - Creating configurable spaces to meet several needs; - Creating inviting centralized spaces - Providing affordances to accommodate different people; - Creating a safe space for discussion and trial and error; - The capacity to have a standing desk or to convert to a standing desk; and - Rethinking policies and changing mindset of the programs in order to not over admit doctoral students. 4.3.4 Incorporating arts-informed approach to gain a deeper understanding of the transcript data Using arts-informed approach can contribute to analyze the multimodal data from Photovoice. Capous-Desyllas and Bromfield (2018) support the use of art in data analysis within social science research to deepen meaning, expand awareness, and enlarge understanding. Gerstenblatt (2013) similarly believes creating visual art in this context generates themes of the research in a pronounced way, through “adding another layer of vision” to convey participants’ stories (p. 12) that is memorable. Incorporating arts-informed approach in analyzing and representing Photovoice data also contributes to interdisciplinary approaches to research (Capous-Desyllas & Bromfield, 2018), which is the nature of this research. It also increases the possibility for examining the data in multilayered ways. Creative forms of data representation could be more memorable to people and, as Capous-Desyllas and Bromfield (2018) claim, have the potential to inspire, evoke deep emotion, and push the boundaries of teaching and learning. Building on the work of Gerstenblatt (2013) and Capous-Desyllas and Bromfield (2018), using creative forms of data representation offered an opportunity to use visual elements to represent the emerged themes from Photovoice. I created infographics (a combination of words, photos, and icons) as a means for formulating students’ insights and articulating the relationships between photos and the emerged codes to help better understand their experiences. Neilsen (2002) suggests visualization of data is a useful way for “listening visually” and getting into “liminal spaces” where “knowledge . . . never arrives . . . it is always on the brink” (p. 208). Infographics at this stage allowed me to make sense and keep 140 track of data interpretations; it was also useful for documenting the relational aspects of Photovoice data. Since collage and infographic cannot be used as an independent form of analyses, I used it alongside the textual analysis as a juxtaposition of the verbal and the visual together (Butler-Kisber & Poldma, 2010), and as a means of reconstructing ideas in a relational manner (Poldma, 2006). In figures 4.17 to 4.19, I placed participants’ photos and emerged codes and themes side by side to visualize the whole data from Photovoice. Figure 4.17 shows how deductive approach and the themes from questionnaire guided the coding process while Figure 4.18 illustrates the emerged codes from each participant transcript (inductive coding) and the axial codes clustering them into categories. Figure 4.19 presents the underpinning assumptions (latent coding) that shaped the data along with some related photos from research participants. 141 Figure 4.17 Photovoice analysis collage, deductive approach in Thematic Analysis 142 Figure 4.18 Photovoice analysis collage, inductive approach in Thematic Analysis 143 Figure 4.19 Photovoice analysis collage, latent approach in Thematic Analysis 144 4.3.5 General comments on doctoral students’ experiences of learning spaces Photovoice data, as a ring in the chain of data sets across the study, sought to explore PhD students’ experiences in their learning spaces and contextualize the analysis through visual representations of how the findings built upon itself to illustrate the experiences and challenges of the participants in relation to their learning spaces. Rather than seeing doctoral students’ specific space such as a classroom, work office, or a lab as a singular person’s situation or place or targeting doctoral students’ learning spaces within a specific discipline, Photovoice proposed seeing doctoral students’ learning spaces across UBC Okanagan’s campus through multiplicities of the daily experiences of students. Participants’ experiences expressed the idea that there were diverse forms of spaces within the life world of doctoral students: a student laying in the grass or on a bench, different types of home-offices, laboratories, graduate offices on campus, coffeeshops, marginal spaces on campus, and natural environments. These learning scenarios may occur whether we have already arranged the spaces or not. In his theory of space, Lefebvre (1991) declares that space “is lived directly before it is conceptualized” (p. 34). What we can do, as Chism (2006) notes, is to “facilitate deeper and richer learning when we design spaces with learning in mind” (p.17). 4.3.6 Specific comments on doctoral students’ experiences of learning spaces Students’ experiences characteristically represented as two-dimensional individual-virtual constructs that provided learning experiences transcending some of the limitations of time and space. 4.3.6.1 The need to have one’s own space: an intimate space to feel belonged. The need to have “own space” on campus was addressed frequently by research participants in the interviews and reflected in their photos (P8, P1, P3, P2, P7 & P11). There were students who felt privileged to have an individual space on campus (P3, P6 & P11), while others complained that they were not supported by their department or their supervisors to have a space to claim (P1, P2, P7 & P8). Students, who had individual spaces, tried to make that space their “own space” by personalizing the space with plants, or adding anything that was meaningful for them (P4, P6, P10). One of the participants (P4) shared a photo of her 145 personalized desk and explained “it makes the space more intimate and makes me feel belong to the space” (Figure 4.20). Figure 4.20 Doctoral student’s individual space in a shared office 4.3.6.2 Lack of office spaces. Students, who did not have a space on campus, were constantly grappling with situations such as displacing and prioritizing people, for example, post-docs over PhD students or PhD students over master’s students. A second year PhD student in Engineering (P1) revealed, I see many students don’t have office spaces, even the postdocs. They should find a spot every day; the department takes a master’s student’s office…it was the case for me….my desk was given to a postdoc. We need more spaces in engineering. This issue seemed to be more acute for students who mostly did not have a proper workspace at home. Figure 4.21 illustrates a corner of an international student’s (P2) room in a basement. Sاe tried to make the space as comfortable and functional as possible to meet her needs. S explained: “[i]t is quite small, but it is just the space that I have, and it became the space that I need”. 146 Figure 4.21 International doctoral student’s work space at home 4.3.6.3 A journey together or “squeezing” together? Students, who had an individual space in a shared office with fellow graduate students, thought that sharing space with others has given them a feeling of “support and mutual understanding”. One of them from School of Education (P11) mentioned that, It does give a sense of community when you run into your colleagues there, your cohort. now we are three and we stay connected as much as we can…. I hate to be the only one without those two there…. they make the experience more pleasant and it is a journey together. This was the case only for students with a shared space with three or four people (P3, P4 &P11). On the other hand, students, who had an overcrowded space, were not satisfied with the experience of shared space. An Engineering alumnus (P9) said, “[i]f the program is designed for 10 students, we cannot admit more students. We cannot add more students to the existing spaces and expect get quality work”. After being graduated from UBC Okanagan, he experienced several campuses as a postdoc, and he thought that those experiences were different in terms of providing quality space to Engineering graduate and post-graduate fellows. He believed “[b]ringing more students within a space without caring 147 about the problems that we had with the spaces was the biggest problem”. Another PhD student (P1) added, UBC Okanagan is a campus of UBC known as a top tier research university; most students chose to come here to get quality education and conduct high quality research. If there is not enough support, we cannot get the quality that we expect. Meetings with supervisor and having the opportunity to discuss ideas with peers in the same program were considered as social aspect of learning space; doctoral students found them “helpful in stimulating productivity” (P4) and “challenging perceptions and biases” (P11) that they may not recognize. There was a photo among participants’ photos of their learning spaces showing an intimate porch with two chairs (Figure 4.22). The participant (P3), who had taken the photo, explained in the interview that this space was her supervisor’s front porch, where some of the research meeting took place. She clarified, I have also unlocked a lot of writer’s block moments here on [this] front deck…. I recently learned to record these moments on tape because with my supervisor, there are so many of these insights you cannot hope to remember them all. A lot of learning happening in this space as we unpack the results of my research. There’s been a lot of work and stressful situation specially as I finish. This was a wonderful inviting spot for us to sit. She brings strawberries and fresh bread and things like that. It generated good conversations. She added that her lack of hearing has often complicated their meetings. To ensure she is able to get the gist of their discussions, her supervisor tended to make sketches which she took away. She said, “as you can see by the pile, we have had a lot of meetings! It’s the process…. it’s really helpful.” (Figure 4.23) 148 Figure 4.22 Supervisor’s front porch space used for research meetings Figure 4.23 Supervisor’s sketches used in meetings 4.3.6.4 Need for community. Despite the strong desire for social aspect of learning spaces expressed by doctoral students, they felt that supports from university have been inadequate. Findings from questionnaire data along with the interviews revealed that students in doctoral education context of UBC Okanagan identified social learning spaces as an important layer of the space; what they thought they needed most in their PhD journey was being provided with potential spaces that can connect them together and that are conducive to 149 social learning. Feeling isolated and not being part of communities was an issue, which was addressed by research participants frequently (P1, P2, P3, P4, P5, P8, P9, P10). An interviewee (P1) said that in the research laboratory that he was doing experiments, his research group brought whatever they needed from home or bought second-hand appliances to make a convenient space in a safe corner of the laboratory for their lunch time and research conversations within the group. They did not receive funding from the university, but through social negotiation, they contributed to create a shared space within an existing space that met their need. He told the story of the space that they created together: In the lab there are only my research group, that we know each other well. We made good friendship. We put money and bought a small secondhand fridge, a microwave, a toaster, and a kettle. Each student shares coffee and tea, …. I think it goes back to people and how they approach and arrange it. We’ve created a shared space and we are enjoying it. No other labs have such a space. Graduate Collegium has been equipped and designated to graduate students as a space to call home away from home at UBC to socialize, have rest, study, or use the appliances when needed, but research participants found it noisy (P2), crowded (P11), mostly dirty (P4), far away (P1) from their buildings and not conducive to learning (P5). They thought every department or building needs such a space to use and take care of it (P1, P7). They thought these kinds of spaces embrace opportunities for “anytime learning” and convey the message that the campus environment is designed to invite students to the spaces that meet their learning needs (P4, P11, P9). 4.3.6.5 Need to access to virtual spaces everywhere. Virtual spaces were another layer of learning space that doctoral students used. By virtual spaces they meant access to “UBC library’s online resources” (P1) and “scientific publications” (P4, P7 & P9). One participant explained “when you are in the writing process or you need to read something, wherever, you have access to internet, you can make it as my learning space” (P10). Figure 4.24 shows a participant’s (P5) photo taken in a café, where she used to write her 150 dissertation. Also, Figure 4.25 illustrates a participant (P8) who needed to meet a deadline while she wanted to be around her family in a weekend. It is worth mentioning that working from home or other off-campus spaces were not as “comfortable”, “easy”, and “efficient” as they might look. Although participants had access to online resources that they needed and they were not required to be physically on the campus, they still preferred to come to campus since they feel they are a part of a community. One of the doctoral students (P9) mentioned: “When I stay at home for a couple of days, I start to feel down”. Another participant (P8) agreed and added: “long hours of working at home could really make you down and depressed”. Virtual spaces were not used as a space for discussion, collaboration, and making communities in research participants’ experiences. They mentioned that they use Skype for meeting with their supervisors whenever one of them is not available on campus (P6). There were students who said that they created WhatsApp groups for casual conversations within their research groups (P1). “Online Writing Clubs” and course blogs did not work properly for a participant (P8) because it was hard for them to get engaged. One of the interviewees (P3) explained this problem, saying, “it didn’t really work for me; sometimes, you had to just go there and put something to fulfil the requirement or to get rid of a task. Rarely, you get in interesting deep discussions.” Figure 4.24 Doctoral student working in a café Figure 4.25 Doctoral student working from home in a weekend In addition, having access to Wi-Fi and phone reception was not always considered as an advantage by research participants. When they need to reflect, write, or concentrate on 151 conceptualizing their thoughts, they preferred to choose the spaces where there were no internet and phone receptions (P3, P7 & P11). According to Participant 7, “[e]very little buzz makes you look at your phone. We are so attached to these devices.” Another participant (P11), who believed that his phone is his “worst enemy” said he tried to discipline himself to stay off the other sites while writing or conceptualizing ideas on his laptop. Photovoice data was collected and analyzed before COVID-19 pandemic, when virtual spaces were not used as much as the COVID time. The rise of COVID -19 has forced educational institutions to replace virtual platforms for teaching, learning, and collaborating. If the Photovoice was conducted during the pandemic, participants would have expressed different experiences and brought totally different ideas. Further exploration on learning spaces during and after COVID-19 pandemic is beyond the scope of this study, while it will certainly inform my future work. 4.3.6.6 Tuning marginal spaces to spaces for learning. Various situations and sites both inside and outside the campus revealed areas that are not necessarily designated for particular individual or social purposes; however, they were used as spaces for special needs; a spare corner of a laboratory and turning it into a space for collaborative activities through social negotiation of the space users is an example, which was previously explained. Research participants expressed that any space could turn into a learning space (P2, P4, P6, P8 &P9). Participant 5 said, “as an international graduate student, I find that any space has become a learning space when necessary, airports, corridors, buses, gyms, etc.” Doctoral students emphasized that it is important that all spaces can link up as reconfigurable learning spaces meaning that spaces should contain the potential and possibility of becoming into a different space or even their opposites (P2, P4, P7, P9 &P11); so that public spaces can be reconfigured to become private and active spaces can become passive and quiet. This is how they have already been dealing with the existing spaces and turn them to the spaces of their needs. 152 Figure 4.26 shows a doctoral student’s kitchen table that was used as a workspace/reading and writing space (P11). Talking about this photo, this participant explained: Obviously, I am adapting my kitchen to make it become a doctoral student workspace; I am kind of transposing an eating area into my miniature office for the morning and it becomes sort of a portable thing like it becomes my office. Figure 4.26 Doctoral student’s workspace in the kitchen Another doctoral student participant (P7) explained about his favorite space that it seemed to be an unused and a “dead space” and he happened to find it randomly. It was an under-stair area in the CCS building, which was not a crowded building on campus, and a couch, which was just randomly put there. This space became his individual space while has the potential for random informal yet productive conversation with people from the department passing by. He shared two photos (Figures 4.27) and clarified that the coach was not under the stairs at the time that he had taken the photos. He shared the experience: 153 It is locked on two sides. Nobody is behind you. The stairs give a convenient ceiling that is not a room. The esthetics of the space has a more non-academic feel because you get weird angles. It is the foyer, so people walk into that space all the time, but you feel free to talk. People don’t use this building as a shortcut; there is no exit. I can see people from my department that I may have questions for them. I see them walking by. I can sit on that coach and have a quick informal conversation with somebody who is passing by. You are not in anybody’s space. I have my own privacy and at the same time, I can connect to the people. You can sit there for hours; no one can see you. It is my favorite space. It has the majority of everything that the university can offer. It is suitable to start conversations… limited and relaxed enough. Figure 4.27 An under-stair area and a random couch turning into a learning space 4.3.6.7 Need for reconfigurable spaces. Research participants believed spaces need to be more flexible and have the potential to be re-configurated by students (P2, P4, P7, P9 & P11). Participant 2 clarified, “our spaces are set up more functional than anything; they have to hit those kinds of metrics. Things can be altered and manipulated by people using them. You give them the tools they make it their own space”. Reflecting on his PhD journey, Participant 9 thought adjustability is a missing characteristic of the spaces that he 154 experienced during his doctoral studies, which is a long journey and requires different spaces at different stages of the work. He described, Master’s is short, two years, but PhD is four years (at least). Having access to a space that I can adjust my needs as I need them. Let me pick and choose what I need. Sometimes, I need to focus, and I need a hard, rigid chair; I have to sit down and do my work in a corner. Sometimes, I am energetic, and a bean bag chair is perfect. You can’t manipulate the space to do that; you have to find the space. So, you constantly go from building to building to find those spaces. Reflecting on a photo in the interview, Participant 7 explained that he felt privileged that he had access to the MacLab on campus as he found the space “flexible” (Figure 4.28). He added, “people can sit around the table…you can spread the stuff out having room on either side. I can do different tasks and I don’t need to go anywhere.” Figure 4.28 MacLab as a flexible space on campus Figure 4.29 Portable cardboard standing desk One of the research participants (P3) even went further and made her adjustable and portable stand-up desk (Figure 4.29). She explained about the photo saying, “this is a cardboard stand up desk that I can take wherever I go … so great because I do find standing rather than sitting to be beneficial”. 4.4 From Space to Place: Comparing the Questionnaire and Photovoice Data The emerged themes from this phase were compared to the data from previous phase, which is represented in Figure 4.30. The comparison helped answering the second research question, the relationship between students perceived and lived spaces. It also guided the 155 study to the next phase, participatory prototyping, through identifying the areas for discussion and exploration with participants. It is important to clarify the complex relationship between space and place in this study, which can be seen in Figure 4.30 to compare participants’ perceptions and experiences of learning spaces. The terms space and place have been interpreted and permutated across interdisciplinary literature (Bhabha, 2012; Massey, 2005; Soja, 1989). Swist and Kuswara (2016) clarify they have been intermingled and interchangeably uses as terms. The premise of space and place used in this study is in accordance with Tuan (1977) where the meaning of place is situated and emerges from the distribution of space. As Tuan (1977) notes, ‘[w]hat begins as undifferentiated space becomes place as we get to know it better and endow it with value’ (p. 6). Drawing on this interpretation, Swist and Kuswara (2016) suggest space is, therefore, a nominal, descriptive layer (such as associating an urban space or learning space with its multilayered properties, while place is an interpretive and affective layer, “imbuing a sense of locality, in essence, the habitat where we live, dwell and that is familiar to us” (p.103). Considering this assumption, what participants perceived as a learning space in the questionnaires is addressed as space and how they engaged with provided spaces in multifarious ways (experiences from Photovoice) is identified as place. In Figure 4.30, I visualize what perceived as space and what experienced as place based on data from questionnaires and Photovoice. Then, in the following sections, I compare space and place and provide discussion. 156 Figure 4.30 Comparing students’ identified learning spaces and students’ experineces 157 4.4.1 Space: What doctoral students perceived as their learning spaces 4.4.1.1 Beyond physicality, social spaces. Data from questionnaire indicated that doctoral student participants perceived learning spaces beyond their physicality. To them, learning space is “a conceptual space unique to each person that meets psychological and emotional needs” (P4), “access to literature/publications” (P4, P7& P9), “new environments to get new perspectives and challenge assumptions” (P2), “a place to ‘plant’ one’s self” (P11), and “meeting with supervisor” (P3). What perceived most as a learning space was social aspect of space where conversation with peers and creating communities is possible. 4.4.1.2 Individual spaces. Next layer of space, which considered as a learning space to doctoral students was “quiet” (P8, P10, P12 & P14) and “private” spaces (P1, P2, P3, P4, P7, P8, P9, P11), which can be used for writing, solitude, and reflection. Participants thought this layer of space helped them concentrate on what they needed to do without being distracted (P7, P8, P9). It also made them feel more belong (P1, P4) if they were provided the opportunity to claim a space and made it their own space. 4.4.1.3 Virtual spaces. Virtual spaces perceived mostly as access to free Wi-Fi everywhere (P1, P3, P4, P5, P8, P9 & P10), access to scientific publications and online library (P4, P7 & P9). Participants believed they could turn any space into a learning space if they were provided with quality internet connection. 4.4.2 Place: How doctoral students interacted with their learning spaces 4.4.2.1 Need for individual spaces. What reported frequently in the interviews and reflected from students’ photos was the need for individual spaces (P1, P2, P3, P4, P5, P7, P8, P9(. Doctoral students spent most of their times in individual spaces in shared offices on campus or in their home offices. Some offices were reported as “overcrowded”, “noisy”, “distracting” with no windows to get sunlight and fresh air. Students who have not been provided with an individual space (or even a desk), were struggling with looking for a spot to do their work every day all over the campus. They also felt “ignored” and not supported by their programs or supervisors (P1, P9). International students, who were not privileged to have a proper space at home, felt the need to have a space on campus more than local students, who had established homes with a corner or a room to work/study. 4.4.2.2 Experiencing isolation. Feeling isolated was reported frequently by doctoral students in the interviews (P1, P2, P3, P5 & P7). They felt a crucial need to form and engage 158 in communities and peer communications in order to stay motivated, get inspired, and tackle isolation during doctoral studies. Although they can work from home in certain times of their doctoral studies, they thought working from home could make them unmotivated. A combination of spaces to meet different needs and spaces for interdisciplinary and collaborative work were students’ suggestions to create communities and overcome loneliness during their doctoral studies. What they needed was a nested community of practice within and beyond departments in order to connect to the peers across the campus. Figure 4.31 outlines students’ experiences in individual and social level captured from the interviews and photos taken by participants. Figure 4.31 Students’ experiences in individual and social level 4.4.3. Imaginations In the questionnaires (Table 4.8) as well as interviews (If you can change one thing), participants implied their imaginations of their ideal learning spaces. Participants’ ideas were coded and turned into themes, which guided the study to the next phase, participatory prototyping. The themes include inviting centralized spaces for discussion and trial and error, 159 students’ rights to change, space to promote well-being, configurability of space to accommodate different people (see Figure 4.30). In the next phase, I explored students’ imaginations and ideas on the future of learning spaces and how they wanted them to be through making prototypes. Dell'Era and Landoni (2014) claim this approach stimulates the researcher to investigate the remote past (memory) and the most distant future (dreams), which is known as latent knowledge of the participants. 4.5 Data from Participatory Prototyping Data from participatory prototyping supported answering the third research question, how might doctoral students envision the future of their learning spaces? This phase aimed at reaching the areas connected to students’ latent knowledge on learning spaces and how they imagine the future spaces based on their ideals though what they make (Sawhney, Prandelli & Verona, 2003). It also corresponds to representational space or lived space (Lefebvre, 1991). This component of space, according to Lefebvre, is a complex ideational space; space of the inhabitants and users that can be altered and transformed by them through their imaginations. Investigating students’ explicit and tacit knowledge revealed some indications about the multi-layered learning spaces through what participants said in the questionnaires and how they interacted with their learning spaces in Photovoice. This phase aimed exploring students’ imaginations and ideals for the future of their learning spaces. As mentioned before, the prototyping phase took place in a virtual asynchronous form where participants contributed to a shared digital space through making two- and/or three-dimension models using the generative tools that I provided them. The aim of the process was to encourage research participants to imagine and express their own ideas about how they want their learning spaces to be in the future 4.5.1 Analyzing the prototypes Qualitative data was gathered from virtual prototyping in both a written format and a visual format. The written format included participants’ notes and descriptions of their made prototypes along with the comments they made when I asked them questions about their 160 artefacts. Visual format consisted of the photos of participants’ prototypes, two- or/and three-dimensional models. The content of the postings on the Padlet platform was analyzed using thematic coding, similar to what I have explained in Photovoice and questionnaire analysis (sub-sections 4.2.2 & 4.3.1). Drawing on a reflexive Thematic Analysis, I used inductive and latent approach in this phase to find underlying patterns in the prototypes. Using inductive and latent Thematic Analysis, coding and theme development were directed by the content of the data and the underlying assumptions of what participants expressed. In coding, I considered both common codes, and outlier or uncommon codes; due to the creative and imaginative nature of the exploratory process, the outlying responses contained original or unique ideas. Figure 4.32 shows the content of the Padlet including participants’ photos of their prototypes along with their notes and sketches. Figure 4.32 Padlet contents Borrowing Capous-Desyllas and Bromfield’s (2018) major levels of analysis, data from this phase was analyzed through three levels: 1) an analysis of each participant’s transcript, 2) a cross-case analysis comparing all transcripts together, and 3) creating visual art/infographic to gain a deeper understanding of the transcript data and corresponding prototypes. I also used reflexive iteration (Srivastava & Hopwood, 2009) as an applied strategy through visiting and re-visiting the data; it helped me connect the data with the insights and refine the codes/themes and develop meaning. Figure 4.33 shows the process of coding and theme development through iterative inductive and latent Thematic Analysis; the process 161 started from coding in each participant’s work and then, linking the codes across the data set in order to develop themes. Figure 4.33 Coding and theme development strategies in prototype analysis Given that in this phase I explored imaginations of doctoral students expressed through integration of visual (tow- and three-dimensional prototypes) and textual elements, I applied a combination of multiple techniques in analyzing the data: inductive and latent approach in Thematic Analysis (Braun & Clarke, 2006) as well as reflexive iteration (Srivastava & Hopwood, 2009) as a complimentary applied strategy in coding and thematizing the data. From an art-informed approach (Capous-Desyllas & Bromfield, 2018), the process also included the creation of collages/infographics, which I explained in detail in the Section 4.3.4. Based on this iterative and organic process of coding, I categorized the emerged initial codes from individual data and group them into themes across the data set (Table 4.13). Also, similar to the Photovoice analysis, I used infographics alongside the textual coding as a juxtaposition of the verbal and the visual together. Figure 4.34 shows the emerged codes from participants’ prototypes and their textual explanations (inductive coding) and the axial codes, which help me cluster the codes into categories. 162 Table 4.13 Themes developed from codes: individual and cross-case coding/thematizing, data from participatory prototyping Initial Codes Themes Private spaces to concentrate P2, P5, P8, P9, P10 First inside (peace of mind), then outside (workplace), P5 Quietness, P4 Privacy Shared spaces for discussion; Invigorating interdisciplinary research, P3, P4, P6, P8, P11, P12 Foster conversation Having option, P4, P7, P11 Flexible spaces, P7, P8 Folding or sliding walls/screens/doors, P6 Movable furniture on wheels, P4 Foldable tables, P3 Reconfigurability to address physical distancing, P11 Flexibility/re-configurability Turning unused corners/in between spaces into individual spaces, P5 Liminal spaces Ability to change/switch positions, P7 Sofa to lie down, P8 Ergonomically suitable chair and desk, P5 Comfort Lockers; Storage for books and arts supplies, P8 Safety Access to food and coffee, P2, P5, P11; Mobile coffee and snack carts, P2 Microwave, P1, P3, P11 Freshwater fountains, P11 Home-like spaces Indoor green spaces, P5 Natural light, P2 Humble shelters, P11 Temporary outdoor structures; Yurt-like structure, P12 Lots of plants, P3 Closeness to the land (an Indigenous principle), P7 Mindfulness/yoga corners, P10 Connect to nature (indoor and outdoor) Specific space for graduate students, P9 Allocated graduate space Writing surfaces on walls, desks; Ergonomic chairs, P4 Power on walls and in floors; Noise-cancelling headphones, P1 Access to Wi-Fi, P1, P4 Affordances 163 Figure 4.34 Participatory prototyping analysis collage, inductive approach in Thematic Analysis 164 4.5.2 General comments on doctoral students’ imaginations of learning spaces The prototypes and notes from the virtual gallery on Padlet platform were the last ring in the chain of data sets within this multi-phased study; they followed the questionnaires and Photovoice data and reflected PhD students’ imaginations of their ideal learning spaces. Prototyping added another layer of participants’ knowledge about learning spaces through externalizing unrefined concepts in material ways and identify key aspects of their ideas and imaginations, as Jewitt et al. (2019) confirm. 4.5.3 Specific comments on doctoral students’ imaginations of learning spaces Doctoral student participants, who participated in this study, came from different departments across the campus. However, what they envisioned as the future learning spaces and their priorities were not significantly different and discipline-dependent as their perceptions and experiences were. Through Thematic Analysis, I developed analytical themes, which I elaborate in the next section. 4.5.3.1 A balance between individual and shared spaces. Regarding the physicality of learning spaces, participants advocated flexible spaces that balance solitude and shared spaces. Participants noted qualities such as comfort, quietness, privacy, living-learning spaces (integrating living, learning and leisure), technology support as well as spaces that foster conversation, which blur the boundaries between individual and shared spaces and learning and living spaces (Figures 4.35 & 4.36). Explaining his prototype (Figure 4.35), Participant 8 said, “[in this setting, you have both private space when you need to concentrate and also a shared space when you want to discuss or hang out with your peers!”. Participant 12 added, “when I think about learning space, three things come to my mind at the first place (QCB): Quietness, Comfort, Brightness”. Emphasizing the home-like spaces, Participant 10 noted, “I prefer to switch my study positions from time to time. For example, after sitting behind the desk for a while, I mostly prefer to lie down on the sofa”. Digital prototypes and post-it notes reflected participants’ interest in easy access to coffee, fresh water, and microwaves (Figures 4.37 & 4.38). 165 Figure 4.35 Arrangement of private and collective spaces Figure 4.36 Arrangement of private and collective spaces Figure 4.37 Participant’s digital post-it note, bottom right note Figure 4.38 Movable coffee cart 4.5.3.2 In-between and on-margin of the existing defined spaces. Doctoral students expressed understanding of the limited physical spaces provided to graduate students by university officials due to the complicated decision makings and university’s priorities. They suggested using the “waste” spaces and turning them into learning spaces. One of the prototypes (Figure 4.39) illustrates an unused corner, which has been re-purposed as a reading/writing space with an access to power, Wi-Fi, noise-cancelling headphones, and some writable surfaces as well as coffee and food/snack. Participant 10 explained: I understand that the amount of space is limited to assign individualized spaces to all doctoral students; so, I thought we can turn any waste space on campus into a workstation. For example, under the stairs or corners of any building or window 166 spaces. I would define spatial privacy and make a cozy/comfortable space, something like the one in the picture. Figure 4.39 Turning an unused space on campus into a workspace Creating space within the unused spaces on campus has been also mentioned in students’ experiences in Photovoice (Figure 4.27). A “dead space”, as Participant 7 called it, became a favorite private space for learning. He happened to find an under-stair on campus randomly and turned it to an individual temporary space. 4.5.3.3 A balance between fixed and customizable. (re)-configurability was another theme that emerged from participants’ imaginations of future learning spaces. Participants expressed their interest in having option between private and shared spaces based on their needs (Figures 35, 36, & 37) as well as flexible and reconfigurable spaces in different layers of space including the arrangement of private and collective spaces (Figures 37, 38, 40 & 41), layout of the space (Figure 4.36), movable and folding walls and furniture (Figures 4.39- 4.41), and the flexibility of the affordances (Figure 4.38). 167 Figure 4.40 Folding doors Figure 4.41 Movabe and writable walls 5.4.3.4 Connecting to the nature, indoor and outdoor: a balance between built and natural environment. Participants’ sketches and written descriptions revealed another layer of their ideal learning spaces. Closeness to the nature was a repeated theme across the data set emphasizing the unique landscape of UBC Okanagan and the potential to be more connected to the nature outside of the buildings or/and bring the nature into the indoor spaces (Figures 4.42 & 4.43). Participant 1 noted, “our campus is located in a beautiful natural landscape and we are note using the outdoor spaces as much as we should. In spring and summer when we are still on campus, sitting outside cheers us up.” Participant 3 added, “[t]he stone-circle at EME is an example of a gathering space for learning. Of course, protection from the elements and a power source are important. I think about adapting a yurt-like structure to create something for graduate students to study in”. Creating humble shelters to protect them from sun or possible rain and wind along with power, Wi-Fi, comfortable benches, and writing surfaces were mentioned as ideal outdoor learning space components. Participant 11 thought “the shelters could be folded and stored for the next year in fall”. Acknowledging the land on which we gather at UBC Okanagan, Participant 11 built upon other ideas and emphasized the importance of Indigenous design principles through consultation and 168 collaboration with the Syilx Okanagan peoples. “[C]loseness to the land, in respectful, collaborative and inspirational spaces need to be considered”, she said. Ideas on bringing natural spaces into the buildings included natural light (P2) and “plant/flower boxes and partitions” (P5) (Figure 4. 43). Explaining his digital sketch, Participant 5 said, “the desks are around four sides of the green space and room walls, but I don't have time to show all four sides”. Figure 4.42 Temporary outdoor shelters Figure 4.43 Indoor green office space 4.5.3.5 Comfort: home-like spaces. Some doctoral student participants referred to the campus as their “second home” (P9) since they spend most of their times on campus. Comfortable furniture (P1 & P5) and having access to coffee/tea (P3, P8 & P11), fresh water (P11) were repeated codes across the data set reflected in participants’ sketches and written descriptions (Figures 4.37, 4.38 & 4.39). 4.6 Summary of Chapter 4 In Chapter 4, I presented data from the sequential research phases and the findings obtained from each phase as well as the analysis and reflection process, which inform responses to the research questions in the following chapter. In Chapter 5, I explain how the presented findings provided some answers to each research question. Space as perceived, space as conceived, and space as lived which respectively address subjective, objective, and co-constructed aspects of learning spaces, provide responses to the three research questions. The theoretical framework of the study, Lefebver’s (1991) production of space along with 169 Lave and Wenger’s (1991) notion of community of practice hold the meaning and guide the interpretation of the findings in Chapter 5. 170 Chapter 5: Discussion of Findings 5.1 Overview of the Study The increasing shift to the knowledge-based society in the time of globalization reinforces the importance of doctoral programs more than ever, while it has necessitated the programs to re-frame doctoral education through incorporating responsive approaches, skills, and environments to support students’ learning and prepare them for the potential diverse futures within and/or beyond the academia, where they can address the complex problems of the new age (Flores & Nerad, 2012; Nerad, 2012; Walker et al., 2009). Learning space is an important factor, among many, in the complex relationship that enables learning and is an integral part of teaching, learning, and research activities. Learning spaces have been investigated within a range of disciplinary perspectives including architecture and design (Long & Ehrmann, 2005; Savin-Baden, 2007), environmental behaviorism (Scott-Webber, 2004), and library sciences (Beatty, 2016; Elmborg, 2011). Often, learning space in the higher education setting has been considered in the context of space planning, or in the context of campus master-planning and architecture which aim at providing appropriate amounts of space for the defined uses and to maximize their uses (Temple, 2007). There is limited literature with a focus on the space issues in relation with teaching and learning, or research-related practices (Temple, 2008). Furthermore, despite an increasing interest in learning spaces investigation, the key basic concepts in relation to learning and space remain uninvestigated (Boys, 2011). In this study, I developed an integrated conceptual framework and a process for data gathering and knowledge creation which allowed me to explore learning space design for doctoral education. The procedure developed in this study addressed subjective, objective, and co-constructed aspects of space in doctoral education context. The purpose was to reach areas connected to understandings, experiences, and imaginations of doctoral students about learning spaces. Intersection of Lefebvre’s (1991) Production of Space along with Situated Learning theory (Lave & Wenger, 1991) enabled me to build an integrated conceptual framework to explore spaces for learning in doctoral education context. The framework is not merely about developing a design guideline or offering any design solutions; it is more about questions to ask within the complex relationship between space and the act of learning, which can support and inform design of learning spaces in the future. 171 To explore learning spaces from a Lefebvrian perspective, it was necessary to explore the production of such spaces considering the complexities of social reality and avoiding binary thinking about learning spaces (for example formal vs informal spaces). Careful attention to the perceived, conceived, and lived spaces, respectively related to students’ perceptions, experiences, and imaginations of doctoral students, explored in questionnaires, Photovoice, and prototyping, can illuminate how learning space for doctoral education is produced. Investigating students’ explicit and tacit knowledge revealed some indications about the multi-layered learning spaces through what participants said in the questionnaires and how they interacted with their learning spaces in Photovoice. In prototyping, I explored students’ imaginations and ideals for the future of their learning spaces. Accordingly, I conducted data analysis strategies for this research based upon the research questions and the theoretical framework of the study. A combination of interconnected strategies for analyzing the data was applied in this study. While Thematic Analysis (TA) (Braun & Clarke, 2006; Boyatzis, 1998; Roulston, 2001), as the general method, informed the data analysis process at all stages, complimentary strategies were integrated to each phase when needed. The benefits of using such an eclectic approach included cross-disciplinary non-linear investigation, creating a complete picture of participants’ knowledge obtained in different levels, enhancement of trustworthiness and rigor, and building a creative medium to interpret the data. Findings from the three phases generated some responses to the research questions, but also highlighted some theoretical and methodological issues. In this chapter, I discuss and reflect on the main themes that emerged from the findings addressing the following overarching questions as well as the involving theoretical and methodological concerns. 172 1. How do doctoral students perceive a “learning space” and its intended use(s)? 2. What is the relationship, if any, between the university provided learning spaces and students’ identified spaces? 3. How might doctoral students envision the future of their learning spaces? In the following sections, I explain how findings from sequential phases of the study generated responses to the research questions. 5.2 Space as Perceived: Subjective Aspect of Learning Spaces (First Question) Boddington and Boys (2011) remind us that learning space is a combination of institutional ideas, the socio-spatial practices occurring in them alongside the individual perceptions and practices within the spaces. The perception of learning space, that the first phase of this exploration was embedded in, represents the accumulation of multiple person-space-learning relationships that are mediated by culture and identity of different departments and individual ways of learning. Despite the different perceptions, the consensus among doctoral student participants from different disciplines was that “learning happens everywhere.” Doctoral students’ perceptions in my study further confirm Lefebvre’s (1991) perceived space in which space is subjected to the social practice, experiences and interpretations of the people who use the space. The diverse practices happen within the spaces are under constant changes and the usages are subjected to the experiences and interpretations of the users. Participants of this research perceived learning spaces beyond their physicality; a learning space to participants was understood both as a physical and a conceptual entity. Also, considering the complex interplay between individual, environment, and community (Swist, & Kuswara, 2016), the relationship between the personal, social and material space tended to be a dynamic and unfolding interrelationship. The concept of perceived space (Lefebvre, 1991) is under constant changes based on experiences and social practices of the space inhabitants. Participants completed the questionnaire before the COVID-19 outbreak, while I collected data for the last phase of this study at the beginning of COVID-19 outbreak in a virtual environment. Since then, virtual spaces started to grow at an unprecedented rate and became inevitably vital spaces for the current (or maybe future) time(s), albeit at the first and second phases of the study, participants did not give the same value as the physical spaces and their potential to create 173 communities. In addition, to prevent disease transmission, physical spaces have been the subject of radical changes allowing physical distancing. Further exploration is required to investigate how COVID-19 circumstances have impacted students’ perceptions about their learning spaces, which is beyond the scope of this study. 5.2.1 Beyond physicality: multiplicity of spaces for multiple identities Any space can become meaningful to people; Keppell, Souter, and Riddle (2011) provide examples such as “erecting shrines at the sites of fatal car crashes or making pilgrimages to farmlands which were once battlegrounds” (p.24). Learning spaces take on some of the emotional aspects of the potential space. Data from questionnaire indicated that doctoral student participants perceived learning spaces beyond their physicality. To them, learning space is “a conceptual space unique to each person that meets psychological and emotional needs”. For students “access to literature/publications”, “new environments to get new perspectives”, “a place to ‘plant’ one’s self”, “meeting with supervisor”, or “computer screens” can all provide potential spaces for learning. A major issue in thinking about learning spaces is to maximize the ease with which spaces that can become psychologically available for large numbers of students; this is what Keppell, Souter, and Riddle (2011) call spatial-dimensional multiplicities for identities. 5.2.2 Social space, community as a missing vital layer of space Research participants repeatedly mentioned the importance of being part of scholarly communities during a doctoral journey. What perceived most was social aspect of space where conversation with peers and creating communities is possible. Participants felt that, however, they did not have enough opportunities to get involved in those communities as much as they should. One participant (P3), who was about to graduate, complained, [f]or the most part, peer engagement is crucial, and often missing in grad studies. I do not think we have enough real dialogue space for students to gather and share. It is the nature of grad studies, but it is hard to get those connections. Based on previous studies within doctoral education, McAlpine and Norton (2006) state, “emphasizing the social and complex nature of learning acknowledges that the thinking and learning of professors and students is situated within distinct academic tribes or communities of practice”. Doctoral learning in this context aligns with cognitive 174 apprenticeship (Austin, 2009) through “participation in a community of scholars and by experiencing Situated Learning” (p. 179). This study also drew upon Situated Learning theory (Lave & Wenger, 1991), which views learning in doctoral education situated and embodied in communities of practice. Research participants confirmed the need to gain sense of belonging, stay motivated and inspired, be challenged, and tackle the PhD lonely time through engaging in academic communities. 5.2.3 Individual space, a necessity in any PhD journey Doctoral students from different disciplines expressed a high level of need for individual spaces to support their long writing and reflection hours. As they get closer to the end of the doctoral program, the intensity of their writing hours increases, so too does their need for individual space. Despite the importance of such spaces in doctoral students’ lives, participants expressed their dissatisfaction about not being provided a (quality) space. One of the participants (P6) said: “I don't believe that this was provided to me as a grad student at UBCO”. Participants from School of Engineering all complained that the department provided shared offices where too many people squeezing into a tiny space, which is likely to increase levels of disruption and frustration. 5.2.4 Virtual space, still an ill-defined space In the changing context of doctoral education, many course- or research-related practices no longer require the institutional physical places due to the increasingly widespread use of digital, virtual, and smart learning environments (Hwang, 2014). Kuntz (2012) reports faculty members similarly indicate that they have been able to extend their offices on campus to virtual and home-work places since the technologies have made it possible to have a virtual set of space and resources including access to extended academic relationships. Nevertheless, McAlpine and Mitra (2015) note that people in academia still need the institutional workplaces because: a) some practices required special tools that are only available in the institution, e.g., lab equipment, super-computers; and b) face-to-face access to some institutional affordances, e.g., supervisor, research team, invited institutional work. Participants of this study also mentioned that they often chose campus physical spaces to use the social resources to their research-related tasks; one of them said that he felt more 175 supported when he works on campus. Participant 9 explained his experience and the need for physical spaces to interact with peers: In doctoral process, you work for a couple of years and the outcome starts coming out and you see it in the last part of the process. It is not a short-time rewarding work. When you work from home and you are not surrounded by your community, simply you can lose motivation and the meaning of the work that you are doing. It is not always easy to work from home; that’s why I believe we need spaces on campus to work, have discussions, and motivate each other directly or indirectly. Other participants, who choose to work at home, often seek solitude to accomplish a task since they did not have a space on campus, or the shared offices were overcrowded and noisy. In addition, International students, who were not privileged to have a proper space at home, felt the need to have a space on campus more than local students, who had established homes with a corner or a room to work/study. An alumnus from FCCS (P8) elucidated, International students deal with many issues. They pay more tuitions and the hours that they are allowed to work are limited. Money is a big issue. They mainly rent smaller places or share rooms. So, they don’t have a comfortable proper space at home to work. They need offices on campus. 5.3 Space as Conceived: Objective Aspect of Learning Spaces (Second Question) Lefebvre (1991) refers to conceived space as the dominant “representations of space” that produce society’s spaces. He identifies conceived space as “the space of scientists, planners, urbanists, technocratic subdividers and social engineers” (p.38). We can gain insight into the conceived spaces for learning in any context by investigating how learners experience such spaces and interact with them. The use of photographs to picture and document personal experiences of learning spaces and the subsequent process of sharing and discussing the photographs allowed the group of doctoral students, and me as the facilitator of the process, to explore the multiple meanings and facets of learning spaces, a seemingly obvious concept. Through the process of 176 sharing and discussing their photographs, I identified commonalities and developed a complex conceptualization of learning space. To some viewers, at first glance, the images might not appear to portray a learning space. For example, a photograph of a random coach under the stairs in CCS main floor may not trigger thoughts of learning space without the story behind it, which was explained by the Participant 7. In the interview, he clarified: “I like this area when the couch is here because you get to see who is coming and going, is open to casual meetups without ever having an excessive amount of foot traffic, and it is near the gallery, and is never loud or crowded like FIPKE, ARTS, and ASC.” Participants’ descriptions of personal experiences and intention underlying each photo evoked intriguing and in-dept discussions about learning space. The conceived space, which is the mental image of the spaces tends to be expanded based on university’s negotiations with students to fulfil their needs. The new building on UBC Okanagan campus, called the Commons, for example, was launched during this study but, participants did not reflect their experiences with those spaces as they did interact with the spaces at the time of data collection. Physical spaces are under constant development and change based on university’s strategic plans. As a result, continuous and timely review of the spaces to inform the evaluation and usability assessment is required. Photovoice provided a process for students to amplify their voices to influence to shape future learning spaces at UBC Okanagan and qualitative data from this phase uncovered themes and patterns, which I explain below. 5.3.1 Lack of personalized space As explained before, doctoral students’ perceptions about learning spaces emphasized mostly social aspect of learning, while in real life experiences, they confront lack of communities as well as lack of individual spaces. Drawing from the concept of different degrees of users’ knowledge (Sawhney, Prandelli & Verona, 2003), explicit knowledge of participants about their learning spaces revealed what they thought about learning spaces in the past and the immediate future. Photovoice underlined the actual situation and how students interacted with the existing learning spaces (what people do). In the first phase of the study, where I explored participants’ perceptions on learning spaces, they indicated the complex and multilayered quality of a learning space while they found it imperative to form 177 a community within doctoral studies, especially since there is a lot of alone time in writing and/or reading. Since PhD students generally spend several hours a day working on their projects, they needed personalized spaces and elements as reminders of who they are aside from their work. One of the interviewees (P4), who came from an Indigenous background put a blanket on her chair in a shared office on campus (Figure 4.20) and said: Our desks show our personalities. The blanket is really important for me. That was one of the things that I brought with me when I first moved to Canada. It is important for me to have that here. It is important that my culture is there, and I have a reminder of where I came from with me in my office… it is motivating me for my project… kind of energizing me for what I do. It makes my desk ‘my desk’. I guess that’s important to have that space. It is very helpful. Definitely, it’s good for your health mentally. Also, to have a space to claim. Students, who did not have a space on campus, were constantly grappling with finding an individual space on campus. One of the participants (P9), believed, Space is one of the elements that can convey a message. When students do not have the space that they need and they deserve, they feel ignored. According to participants explanations, when they were admitted to a PhD program at UBC Okanagan, as a top tier university, they expected to get involved in a community of peers and be provided with (at least) “standard” space and affordances that they needed to conduct a PhD research. One of the participants (P1) expressed dissatisfaction with physical spaces: “[t]he most annoying thing is that you reach to become a PhD student at UBC, and you realize that you don’t have a space or even a desk for yourself.” Participants believed that space is an indicator of support and the way that the program is treating the grad students and research. An alumnus (P9), who experienced lack of space as well as community during his PhD, declared, “I’m not talking about just adding fancy chairs or desks; what is much 178 more important is that you get support from the community that you work in and you can support other to survive and thrive in PhD.” 5.3.2 Lack of community and connection with peers Participants of this study thought trading off ideas with their peers, who are in the same program, was essential, especially since “the collaborative atmosphere proves to be helpful in stimulating productivity” (P4). However, when I explored their experiences in the next phase, Photovoice, what they experienced was not aligned with what they expected or what they perceived as a learning space. For example, Participant 3 clarified, The one word that seems difficult to connect with is 'peers' during my doctoral journey. With interdisciplinary studies, the chances of discovering peers seems remote. What I did discover are experts in their areas of studies, research methodologies, and research methods that through dialogue and conversation, we learned together. Despite the strong desire for social aspect of learning spaces expressed by doctoral students, they felt that supports from the university have been inadequate. One of the interviewees (P11) explained this problem, It is the most isolated learning in my life. I think that’s why most people pull out. It’s become too big. The reality is there is no connection between us and other learners. I don’t think the coursework provided this opportunity. As declared by Lefebvre (1991), space and the people who inhabit the space are not separated. In the context of doctoral studies, participants of this study also emphasized the importance of interactions within the learning spaces, which give rise to the institution’s community; they implied creation of communities can turn an existing space into a place. Temple (2009) notes “[t]here is an interaction between space and the university community, during which both are changed” (Tample, 2009). On the other hand, interviewees who felt privileged to have a proper shared office confirmed that it helped them create a friendly and supportive community. They reported that gives them a sense of support and mutual understanding. One participant (P4) called her 179 shared office a “hub” where she spent at least four hours a day. She explained although there were seven people who shared the space, there was respect amongst them when they were working, and they were quite clear with the boundaries. 5.3.3 Spatial affordances An affordance is the design aspect of an object which suggests how the object should be used (Norman, 1988). It was first coined by Gibson (1979) to describe an action possibility available in the environment to an individual, independent of the individual’s ability to perceive this possibility. Doctoral students who participated in Photovoice addressed the restrictions that physical, social, and individual affordances created within the spaces. They valued comfort in learning spaces and the necessary affordances such as Wi-Fi, ease of access to furniture and above all, a friendly and reconfigurable space. Physical environment could support or restrict behaviors and actions, which has its underlying foundation based on Gibson’s (1979) concept of affordances. He suggests, “[t]he affordances of the environment are what it offers the animal, what it provides or furnishes” (p. 127). For example, a flat surface may afford some activities of standing on or walking on, while a space behind another object may afford hiding behind. Drawing of the concept of affordances, participants claim activities and affordances within the spaces can play an important role in their engagement with learning. Lack of offerings and action possibilities in the environment was reported in the interviews with doctoral students. Students believed physical space’s elements and possibilities such as access to kitchenette, private spaces, writing surfaces, natural light, standing desks, and sofas can provide them with flexibility and comfort. Heft (1988) states the primary attention of affordances concept is on what the environment could offer to individuals rather than focusing on common properties that are often used for describing the environment, such as form, color, texture, or the name of particular objects. Physical affordances extend the comprehension of a learning space beyond the common label of the space and beyond the common function or use of it; rather, they allow for various possibilities that spaces and objects could support learning and students’ comfort and engagement. Exploring space affordances and their influence on individuals’ experiences within the space, Atmodiwirjo (2014) believes, “[i]n the process of perceiving 180 objects or spaces, an individual perceives the affordances of the objects or spaces, and then they could determine what could be done with them”. 5.4 Space as Lived: Co-Constructed Aspect of Learning Spaces (Third Question) The third phase aligns with Lefebvre’s (1991) lived space or complex ideational space, which is the space of the inhabitants that can be altered through their imagination towards transformation. Lefebvre criticizes the domination of conceived space over space as lived. Lived space, as Gardiner (2002) explains, is “where essential human desires, powers and potentialities are initially formulated, developed and realized concretely” (p. 75). However, space, as Lefebvre (1991) argues, is always produced trialectically through perceived, conceived, and lived processes. Lefebvre’s lived space embodies symbolisms linking to what is hidden. Savin-baden (2007) confirms the notion of lived spaces is symbolized by activities that occur in them, while at the same time, they portray complexity and symbolism. Lived spaces might be adjusted due to circumstances. However, this understanding of representational (lived) space could be problematic when the change is not recognized by all who utilize that space. Prototyping helped participants to make their thinking visible and express their imaginations to shape future possibilities for learning spaces at UBC Okanagan. Learning spaces of doctoral students have been made up through a three-way dialectic between perceived, conceived and lived space, the senses, physical movement, and imagination. In the following sections, I explain how I interpreted the qualitative data about students’ imagination and ideals. 5.4.1 Physicality, individual and shared spaces Regarding physicality of learning spaces, participants imagined comfort, quietness, privacy, living-learning spaces (home-like comfort), technology support as well as spaces that foster conversation. They envisioned the future spaces as a balance between individual and collaborative spaces. In fact, they imagined freedom and choice based on their learning styles and their needs to accomplish different tasks. Savin-Baden (2007) confirms the blurriness quality of learning spaces and that learning spaces are places of transition; “they might be seen as liminal in nature in that they can be seen as betwixt and between states that 181 generally occur because of a particular need of an individual to gain or create a learning space” (p. 9). 5.4.2 Liminality, in-between and on the margins Turning the unused spaces into spaces for learning emerged in participants’ imaginations as they expressed their understanding about the limited physical spaces and the complicated university decision makings and priorities regarding providing (more) space to graduate students. What students suggested was to re-use or re-purpose the unused existing spaces. They believed if spaces are flexible enough, they can arrange things in their own ways pushing the boundaries. As Hunt, Huijser, and Sankey (2012) mention, this process in not always predictable and does not necessarily align with what has been designed, but “if there is sufficient flexibility, the learning space will enable innovation driven by imagination”, they said (p. 189). There are liminal, unused spaces in all buildings, whether we are aware of them or not. Corridors and stairwells, for instance, as places of chance meetings, welcome and unwanted as well as places for learning. Ruth (2017), Hurdley (2010) as well as Iedema, Long, and Carroll (2010) believe liminal spaces are often of great liveliness with more life than inside the formal settings of spaces. 5.4.3 (Re)-Configurability Participants’ imaginations and ideals emphasized the flexibility and configurability of spaces to enable self-initiative. They felt that the ability to manipulate their spaces enables them to create the required spaces based on what they need in different situations. Acknowledging that any space can provide a good fit, or a bad one to its inhabitants, Keppell, Souter, and Riddle (2011) suggest “contents can rupture the container” (p. 25) while Bion (1984) has already claimed that the dynamic interaction of container and contained enables creative mental life. This interaction involves a cross-checking process exploring whether the inhabitants feel satisfying or if the space is enabling. If not, are they able to make mutual adjustments? When reconfigurable quality of the space allows for check-adjust-fit, mental space can free up for learning. This study has been partly conducted in the time of COVID-19 pandemic and still so many uncertainties remain as educational institutions plan for the reopening of their buildings to students and educators. Rethinking learning spaces to prevent disease transmission, changes to the physical space will be necessary to allow for physical distancing. As a result, 182 learning spaces will not be the same again. Configurability will be an important quality of space more than ever. Considering the ambiguous future and the restrictions that COVID-19 have brought during the past few months, one of the participants (P11) explained, “with emphasis on reconfigurable spaces, whether indoor or outdoor, many options are achievable. And, to address physical distancing into our future, this reconfigurable principle needs to be foregrounded.” 5.5 Summary of Chapter 5 In Chapter 5, I provided some answers to the research questions. Space as perceived represented subjective aspect of learning spaces. Findings from questionnaire along with interviews corresponded to participants’ conceptualizations about learning spaces. Data from Photovoice, including photos and interviews, reflected participants’ experiences within the existing spaces, which is space as conceived. Space as lived aligns with co-constructed aspect of learning spaces. Data from prototyping reflected participants’ imaginations and their latent knowledge about learning spaces, which provided responses to the third research question. In the next chapter, I explain how this study contributed to the existing literature through developing design methodology and domain theory based on a DBR approach. At the end, I provide recommendations for future research and practice. 183 Chapter 6: Conclusion and Recommendations In this chapter, I discuss the lessons learned derived from the findings which I presented in Chapter 4 and 5 guided by DBR framework. Reflecting on the research approach, I offer recommendations for future research and practice and close the chapter with some final comments. Figure 6.1 summarizes contributions of this research to the literature, outline the lessons learned, and sums up the recommendations. In the following sections, I explain all the mentioned components. 6.1 Contribution to the Literature: Developing Design Methodology and Domain Theory Drawing on DBR In Chapter 3, I explained that Design-Based Research (DBR) provides opportunities for developing design methodology (design procedure), domain theories (design principles or simply lessons learned), and design frameworks (generalized design solutions) (Edelson, 2002). This study supports the development of domain theory and design methodology. Findings from this study do neither produce any generalized design solution, nor a complete account of learning space design. In this study, I developed and tested a new framework and methodology for data gathering and knowledge creation about learning space design for doctoral education through a participatory approach. The results represent a vision, a beginning base to take action based on students’ experiences about learning space in doctoral studies. The design methodology and domain theory developed in this study are the initial contributions to learning space research. To generalize, constant investigation and retrospective analysis should be conducted to identify appropriate generalizations. Edelson (2006) confirms, “being research-driven, maintaining systematic documentation, and conducting formative evaluation all support the process of generalization” (p. 103). It is also important to expand the information by including the perspectives of other users of the spaces (undergraduate students, professors, staff, graduate program providers, etc.) in future work. 184 Figure 6.1 Summarizing contributin of this study to the related literature 185 6.1.1 Design methodology A design methodology is a design procedure (Edelson, 2002; 2006), which provides guidelines for the process rather than any product. The procedure developed in this study included pre-design, design, and post-design stages aiming to address subjective, objective, and co-constructed aspects of learning spaces in doctoral education. The purpose was to reach areas connected to understandings, experiences, and imaginations of doctoral students about learning spaces. The design procedure drew on the concept of “different degrees of users’ knowledge” in Design Research Methods including “what people say”, “what people do”, and “what people make” (Sawhney, Prandelli & Verona, 2003), which correspond respectively to explicit, tacit (observable), and latent knowledge of the participants. In the pre-design stage, I identified the area of the problem through exploring the first and second research questions connecting them to the perceived and conceived spaces in Lefebvre’s (1991) spatial triad. The design stage included a prototyping process exploring participants’ imaginations and ideals, which addressed Lefebvre’s (1991) lived space. These stages along with documentation, reflection, and evaluation of the process (post-design) helped me understand the complexity of learning spaces and how they affect and are affected by their inhabitants through the interplay of the perceived, conceived, and lived spaces. In Chapter 3, I explained how I designed the process being informed by the research questions and theoretical framework of the study. The process created an avenue for students to address the problems and formulate new visions for the future of learning spaces in a participatory manner. 6.1.2 Domain theory Exploring learning spaces in doctoral education context through the designed process helped me analyze the area of the problem related to doctoral students’ experiences within the existing spaces; this is what is called domain theory in DRB research, a descriptive analysis of the area of the problem. Edelson (2002) confirms that a domain theory is descriptive, not prescriptive. The problem analysis informed by the findings from the first and second phase is a context theory (Edelson, 2006), a description of the needs of doctoral students in UBC Okanagan campus. The problem analysis entails developing a process that can make the design happen. Based on the findings from the first and second phases, I designed the third phase, 186 prototyping, to address the co-constructed aspect of learning spaces as the desired outcome (Edelson, 2006) of problem analysis. Developing a design process guided by the initial findings supported the development of theoretical assertions about using a participatory approach in learning space design. In the next section, I explain the theoretical output of this research project, which emerged from the findings inductively. 6.2 Design principles (Lessons Learned) DBR produces knowledge in the form of design principles. Design principle is a term that Van den Akker (1999), Reeves (2006), and Wademan (2005) use when they refer to the theoretical outputs of Design-Based Research. Other authors call it domain specific theory (Gravemeijer & Cobb, 2006), design theory (Wademan, 2005), or lessons learned (Van den Akker et al. 2006). McKenney, Nieveen, and van den Akker (2006) state: “design principles offer situated guidelines, which rely on accurate, thorough portrayal of pertinent contextual variables” (p. 77). This study took place at the UBC Okanagan campus as a “naturally occurring test bed” (p.77) to address doctoral students’ perceptions, experiences, and imaginations about learning spaces and the space issues, which intimately portray the context. Since design knowledge is contextual, social, and active, constant iterative exploration is required to refine the design process as well as the design principles. In the following sub-sections, I discuss the lessons learned derived from the findings. 6.2.1 Learning space is a layered multi-faceted phenomenon This study begins to open up the field of learning spaces in doctoral education to its complexities through integrating two views while offers a developing clarity that each focus can bring: 1) Lefebvre’s conception of space (1991) that suggests investigating the interactions between occupants and space. Based on this view, the societal production of space is a dialectical interaction between physical, mental, and social spaces. 2) Lave and Wenger’s (1991) Situated Learning and communities of practice model as well as cognitive apprenticeship approach in doctoral education (Ausin, 2009). Communities of practice model sees learning as a dynamic social process and acknowledges that students’ learning is situated within distinct and different academic communities. Since learning in doctoral education is situated and embodied in a variety of communities of practice, cognitive 187 apprenticeship approach supports students’ learning journeys within a nested community of practice. Drawing from this integrated framework, learning is always situated and embodied, not just in material space but also in individual, social and cultural contexts. Also, space can only be viewed in relation to its occupation, that is, as socio-spatial practice. Boddington and Boys (2011) explain this means that “learning spaces are not so much a matter of aesthetics or innovative design, as about the processes of learning, teaching and research and the ways in which relationships between these are categorized, organized and connected both conceptually and materially” (xii). Unpacking participants’ perceptions, experiences, and imaginations of learning spaces through the three sequential phases of this study, the emerged themes revealed multiple, layered, and dynamic components of learning spaces and the relationships through which learning and space intersect. Lefebvre (1991) argues that space does not simply exist as a given; it is always produced. The modes that he suggests helps us think through the complexity of how all spaces are produced. Lefebvre’s trialectical model clarifies “space is produced by and productive of a dynamic interplay of material, conceptual, and experiential processes” (Nunes, 2006, p.xxi). To explore learning spaces from a Lefebvrian perspective, it was necessary to explore the production of such spaces taking into account the complexities of social reality and avoiding binary thinking about learning spaces (for example formal vs informal spaces). Careful attention to the perceived, conceived, and lived spaces, respectively related to students’ perceptions (questionnaires), experiences (Photovoice), and imaginations (prototyping) of doctoral students elucidated how learning space for doctoral education is produced. In addition to the relationship of learning and space, which is complex and interactive, a particular educational institution is part of a wider, dynamic web of social, cultural, and political aspects (Gislason, 2010). The multi-faceted layered learning spaces reflected by participants allow envisioning the spaces in-between the students’ routines and socio-spatial practices and the conventional and institutional spaces. Boys (2011b) informs us of the danger of viewing the components of space as settled and explained in totality; the patterns are always situated in relationship to both particular places and people. The resulting patterns in each context is what Geertz (1973) calls a thick description; it is a rich and 188 layered account that may not result in design solutions or conclusion in short term but can illuminate our decision-making. 6.2.2 Learning space is an indicator of support Space can be seen both as a site of learning and more as a site of power. Savin-Baden (2007) argues the architecture of universities tends to represent different ideologies, for instance, the lecture theatres of tradition and knowledge or the beanbags of innovation. These decisions are made in official meetings and the control of space and the way in which it is valued and represented is achieved in organizational practices. Borrowing Lefebvre’s understanding of space, Savin-Baden (2007) claims, “[t]his very ordering belies the way that university learning spaces shape not only student learning and staff practices, but also the very nature of higher education itself” (p. 9). Lefebvre (1991) argues: “(social) space is a (social) product” (p.324) or a complex social construction based on values, and the social production of meanings which affects spatial practices and perceptions. Space thus serves as a tool of thought and of action; “in addition to being a means of production it is also a means of control, and hence domination, of power; yet that as such escapes in part from those who would make use of it” (Lefebvre, 1991, p. 26). Findings from this study describe an approach and multiple design features that enable and support learners’ autonomy. Boud (1981) suggests that autonomy enables learners find resources for learning and choose when and where to learn. Participants of the study envisioned comfortable home-like spaces with flexible spatial affordances to accommodate different people. Students who were not provided with a space to work on campus were more likely to go home, which was not an ideal place for the less privileged students. They believed that providing quality space to graduate students to make it their “own space” is an indicator of support from the graduate programs and the supervisors. This is what Temple (2009) calls message sending meaning that “campus designs give out signals about the importance of scholarship” (p. 210). Edwards (2000), who is an expert of this approach, argues that university buildings are silent teachers and that we may detect the exacting agendas of intellectual inquiry in the design of many university buildings. 6.2.3 Learning space has a potential to improve and sustain well-being Distinguishing between survival and well-being needs, Boyden (1971) explains survival needs deal with aspects of the environment that directly affect human health, such as 189 clear air and water, while well-being needs are more indirect affecting overall health through their relationship to fulfillment, quality of life, and psychological health. Among Boyden’s (1971) well-being needs are several that are directly relevant to learning spaces; they include opportunity to engage in spontaneous social encounters, freedom to move from solitary work to group interaction, opportunity to engage in a range of behaviors such as creativity, self-expression, cooperation, and exploration, opportunity for physical movement, noise levels not much above or below that in nature, and an interesting visual environment. Boys (2014), however, warns that we can get too easily seduced by stylistic feds behind many new learning space designs, without contextual research-based evidence to understand if those spaces add more value and are effective and sustainable in lived experiences of space inhabitants. Kuh et al. (2005) confirm “the physical environment communicates messages that influence students’ feelings of well-being, belonging, and identity– and so aids learning” (p.106). Participants of this study sought both physical and psychological comfort that implied their sense of well-being; they explained it has the potential to impact their productivity, creativity, and engagement. In her research, design, productivity and well-being, Heerwagen (1998) focuses on four elements that must coexist to create positive and productive places: cognitive effectiveness, social support, emotional functioning, and physical function. She claims if people do not have a sense of well-being, they become distracted. Participants’ perceptions, experiences, and imaginations about learning spaces emphasized the effective learning relates to well-being, belonging, and engagement that they felt support them in their studies. Providing them with a space to make it their “own intimate space” helped them feel more belong and reminded them of who they are; outdoor spaces, fresh air, natural light, and indoor plants can provide a space for solitude and reflection in order to “feel one-ness with nature” and "plant one’s self”, according to participants. Home-like spaces, kitchenettes and sofas suggested a domestic space with sense of rootedness and familiarity. Research participants also felt the need to gain sense of belonging, stay motivated and inspired, and tackle the PhD lonely time through engaging in academic communities. What was missing in their PhD journey was engaging in a nested community of practice (Lave & 190 Wenger 1991) within and beyond departments in order to connect to the peers across the campus that can lead to developing and sharing knowledge (Nonaka & Konno, 1998). Knowledge embedded in a shared space is tacit and can only be made explicit through sharing of feelings, thoughts, and experiences of persons in the space. Temple (2009) clarifies one way to link university’s physical form with academic effectiveness is through the contribution of space to the creation of sense of community and thus of place. 6.2.4 Learning space is a changing entity Drawing on students’ perceptions, the notion of learning space is a maze of different spaces that is continually unfolding and changing based on different situations and needs, which make them grapple to navigate and negotiate with the provided opportunities. Emphasizing the complexity of learning, in this study, participants imagined the “potential for choice” in relation to their learning spaces. They tended to see a learning space as a changing and flexible entity in order to reconfigure it themselves based on their changing needs. Lefebvre’s (1991) conceptualization of space helps to understand how a learning space affects and is affected by its inhabitants in the interplay of physical, virtual, and potential (transitional) spaces; the spatial relations that show Lefebvre’s proposal of three relations: spatial practice, representations of space, and representational spaces. Addressing the dramatically changing global educational environments and practices, Keppell, Souter, and Riddle (2011) call attention to reconfigurability as a multistable quality, which is an inhering aspect of any space. They suggest in order to create potential spaces, as many of the modalities as possible need to be brought into play. “This means that spaces must contain the potential and possibility of becoming their opposites, so that public spaces can be reconfigured to become private and active spaces can become didactic” (p. 27). Participants emphasized the provision of choice since they need multiple spaces depending on the task they do or the stage of their doctoral program. As Parisio (2013) suggests, providing the learners with choice encourage freedom, flexibility, independence, mobility, and agility, which are integral to empowering autonomous learners. Learning spaces could then be portrayed in particular ways, seen as bounded by time, place, institutional and disciplinary culture. Deleuze and Guattari’s (1988) conception of smooth and striated space could be useful in influencing our thinking about what learning 191 spaces might mean for dramatically changing global educational environments and practices. The notion of smooth space is open space, one of becoming, which is nomadic, in opposition to the striated which is space of closure, sedentary, or bordered State space. Savin-Baden (2007) incorporates the concepts of smooth and striated spaces into spatial ecology, which is a broader scope. She identifies spatial ecology as creation of balance between and across spaces in higher education, where not only knowledge, content, conceptions, and acquisition, but also values and beliefs, uncertainty and complexity are taken into account. In today’s unpredictable world with increasingly development of technology and the need for virtual spaces, which has brought “new types of visuality, literacy, pedagogy, representations of knowledge, communication and embodiment” (Savin-Baden, 2007, p. 13), the development of a sense of place and the connection of experiences through social and cultural interactions are fundamental to think about learning space as a spatial ecology. As mentioned earlier, I conducted the last part of the data collection and analysis of this study at the beginning of COVID-19 outbreak. I designed and developed a virtual studio so that research participants could express their imaginations through making prototypes and displaying them in the provided virtual space. Since then, virtual spaces started to grow at an unprecedented rate and has become inevitably vital spaces for the current times. Virtual communities are being defined using current networked technology, while communities of practice emerge within those communities. Bringing the current network technology into teaching and learning context more than ever, has both advantages and disadvantages in emergent development of communities of practice, which constantly needs cautious and close investigation. In addition, physical distancing regulation to prevent disease transmission has brought a new consideration to physical spaces. (Physical) learning spaces may not be the same again as we are witnessing radical changes in physical spaces and socio-spatial practices that occur within them. As a result, there is now a shift towards a notion of flexible spaces in homes or/and reconfigurable spaces on campuses. Savin-Baden (2007) argues the notion of representations of space, the conceptualized space by planners which attempt to describe patterning of the social in space (Lefebvre,1991), “no longer engenders an integrated idea of the use of space but, rather, is a space of change.” 192 6.3 Recommendations for Future Research In this study, I proposed an integrated framework to create a shared vocabulary about the complexities of learning space in doctoral education. My framework builds upon Lefebvre’s (1991) Production of Space and Lave and Wenger’s (1991) Situated learning and the concept of communities of practice. I also incorporated participatory design as a theory for action to bring those theories one step further into action. This blend of approaches helps to foreground the complexity of space as a socially constructed entity and how to overcome binary thinking about learning spaces in higher educational setting. Research often leads to further questions, and this study is no exception. Findings from this study identified avenues for future research, which are outlined below: Recommendation 1: Conducting longitudinal research on learning spaces through identifying the interactions between learning space and learning over a longer time frame both in undergraduate and graduate settings in order to view the campus as a whole through a spatial ecology model (Savin-Baden, 2007). Findings presented in this study focused only on the lived experiences of doctoral students of UBC Okanagan where I had to collect the data within a limited time frame designated for this study as a doctoral dissertation. The development of a sense of place and the connection of experiences through social and cultural interactions are fundamental to think about learning space as a spatial ecology. Recommendation 2: Exploring a participatory approach to design and research on learning spaces around parallel partnerships with other research-intensive universities, U15 (Group of Canadian Research Universities) and U21 (the leading global network of research universities for the 21st century) in which UBC is a member. Reich et al. (1996) confirm that considering “the cascading nature of design, participatory design cannot be a one-shot affair” (p. 170). Hence, effective participation requires continuous commitment in various contexts. It is also important to expand the information by including the perspectives of other inhabitants and users of the spaces. Recommendation 3: Exploring the future of (physical) learning spaces, which allow physical distancing and considerations that help prevent diseases or virus transmission (such 193 as COVID-19), in addition to virtual spaces as potentials to create communities when physical spaces cannot be accessed. 6.4 Contextual and Practical Recommendations In this Section, I offer practical and contextual recommendations to improve doctoral students’ learning spaces at UBC Okanagan. The “ideal” learning space according to doctoral students and alumni from UBC Okanagan should provide a range of spatial arrangements fostering self-regulated activities of the individuals or a group of students who work together. Therefore, flexible and easily adaptable spaces that a variety of activities could conceivably happen in them are suggested; open and multifaceted spaces to allow the widest range of activities possible. The following suggestions focus on several conditions that will be important for university officials to consider in order to support conditions for PhD students to experience quality spaces that meet their needs. However, drawing on Lefebvre’s (1991) conceptualization of space and considering that doctoral experience is influenced by the social practices of the scholarly communities (Lave & Wenger, 1991) upon which this study has been conducted, learning space is a socially constructed and a collective resource. As a result, I offer the following recommendations based on participants’ contributions at the time of conducting this study at UBC Okanagan campus. They are not generalized principles for other contexts until they are tested as “working hypothesis” (Cronbach, 1975, p 125) in other contexts. Most importantly, these recommendations are not offered as “how to do” guides, but as a guide to help us think deeper about what learning spaces for doctoral education at UBC Okanagan’s campus may look like. I offer these contextual recommendations, which reflect participants’ thoughts and ideas, while I remain conscious that learning is more than the space in which it occurs, and space is more than the practices it contains. As Boys (2011a) advises, “[space] is one of the means through which we attempt to articulate new social and spatial practices or to make concrete and obvious existing ones” (p.174). 1. Drawing on a social constructivist paradigm in learning and the notion that learning is embedded in communities of practice in doctoral undertaking, using the potential of digital technologies to develop virtual communities of practice is inevitably vital spaces for the current (or maybe future) time(s). Wisker, Robinson, and Shacham (2007) has already 194 claimed that conducting doctoral thesis in isolation is the dominant problem of doctoral experience and being part of communities of practice has been seen to be helpful. 2. Creating potential opportunities within the learning spaces through inviting students to take charge of the configurations of their working environment. They will be able to work wherever comfortable and technologically convenient. Uduku (2015) notes unlike previous centuries, the 21st century requires not more physical spaces but increased flexibility of available spaces making them “capable of continuously reconfiguring themselves.” (Pearlman, 2010, p. 124). 3. Using movable, folding, and writable walls that allow students to create private spaces for individual and group workspace and provide an opportunity for brainstorming and conceptualizing ideas on the walls; the potential for multiple usage of space is a key characteristic of autonomous learning, according to Boud (1981). Reconfigurable spaces also allow us rethink density in order to prioritize physical distancing. 4. Providing movable and comfortable furniture on wheels and foldable tables that provide flexibility and configurability to make comfortable spaces. Keppell, Souter, and Riddle (2011) explain comfort in space creates a physical and mental sense of ease and well-being. This feature provides a fertile ground for students to customize their environment as they self-direct their learning. 5. Creating home-like intimate spaces to switch positions from time to time through providing sofas, desks, standing desks, floor sitting cushions in addition to easy access to coffee, fresh water, microwaves, kitchenettes, and somewhere to keep belongings. Parisio (2013) reminds us that providing home-like comforts can encourage students to spend recreational time while they are doing academic tasks on campus in learning spaces. “Amenities such as kitchens, boiling water, showers, lockers, lounges, TVs, and cafés provide comfort and function to support some basic human needs” (p. 678). Maintaining cleanliness of these spaces is an important factor in providing such spaces on campus. 6. Providing power on walls and in floors, noise cancelling headphones, and quality Wi-Fi; design features that include affordances or action possibilities that the space provides the users. 7. Making quiet zones with no cell phone reception and internet where students can enjoy the quiet space for reading and writing or meditate, contemplation, or use the space to 195 do some yoga or lay down on the floor to stretch their bodies. Consideration of the needs of cultural and physical differences is addressed as equity by Keppell, Souter, and Riddle (2011). 8. Providing opportunities to connect to the natural environment (indoor and outdoor) to work, play, and rest, which aligns with Indigenous principle of closeness to the land; providing indoor green spaces and plants, humble shelters, temporary outdoor structures, and comfortable outdoor furniture with Wi-Fi access are few examples. 6.5 Looking Back on My journey/Final Comments As I come to the end of this study, I reflect on my own learning journey as a researcher. During my doctoral research, I had the opportunity to visit a few campuses in North America (University of British Columbia – both campuses, McGill, Concordia, and Stanford Universities) and in Australia (RMIT and La Trobe Universities) where I attended the related workshops and spent a lot of time reading, writing, and reflecting on my thoughts on those campuses. I also contributed to UBC Okanagan’s (my host university) courses and events as a participant or collaborated as a facilitator through virtual spaces while I was away and in the time of COVID-19 outbreak. Having had this flexibility and diversity of learning spaces, my perception of a leaning space as a conventional physical space has changed. However, being away from my own scholarly community impacted my mental well-being, sense of belonging, and my professional identity. I agree with Brooks et al. (2012) who note, stretching learning spaces beyond physicality of the spaces, is associated with the shift away from an objective understanding of space as a system of geometry towards an emphasis on how space is constructed (physically or virtually) through the social processes that give it meaning. Reflecting back on my experiences as a visiting student in other universities, I can now better comprehend Lefebvre’s notion of space as socially constructed. I did not have a meaningful engagement in constructing the spaces since I did not feel that I was a member of those communities although I was using the provided spaces as my temporary workplace. Also, confirming Situated Learning’s idea that views learning as a function of the activities, the context, and the culture in which learning is situated (Lave, 1988), I better understand that those temporary experiences were not fully embedded in the communities of practice with “history, norms, tools, and traditions of practice” (Kolb & Kolb, 2005, p. 200). As Lave 196 and Wenger (1991) note, becoming a member of a community of practice can happen through a legitimate peripheral participation (e.g., cognitive apprenticeship). Considering the radical changes that COVID-19 has brought in how we work, collaborate, study, and engage in social events, the timing is right for higher educational institutes to rethink their learning spaces for the post- COVID era in order to support students’ learning and their meaningful engagement in learning communities and learning spaces. They might start to explore the contribution of space to the creation of a sense of community and thus a place. I would adopt Evans’ et al., (2006) learning in, for, and through a workspace for a learning space through which social processes can shape learners’ perceptions and attitudes toward engagement in learning, thus influencing their personal and professional development within the learning spaces and beyond. Providing potentials for learning spaces influences the nature of scholarly communities and the culture that exist within them. I also admit Temple’s (2009) argument that through such process any space can be transformed into a place, and this is the place that impacts academic experiences and outcomes. Before any decisions on learning space (re) design, we need to explore the complex interaction between space and campus community, during which both are changing. 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Routledge. 226 Appendices Appendix A: Behavioral Research Ethics Board Certificate of Approval 227 Appendix B: Tri-Council Policy Statement (TCPS 2: CORE) Certificate 228 Appendix C: Information Sheet and Initial Consent for Using Data from the Questionnaires 229 230 Appendix D: Questionnaire 231 232 233 234 Appendix E: Information Sheet and Informed Consent for Participating in Photovoice 235 236 237 Appendix F: Photovoice Training Agenda 238 Appendix G: Instructions for Photovoice Participants 239 Appendix H: Consent to Use of Image Form 240 241 Appendix I: Photo Release Form 242 Appendix J: Semi-structured Interview Questions 243 Appendix K: Information Sheet and Informed Consent for Participating in Participatory Design 244 245
Thesis/Dissertation
eng
Interdisciplinary Studies
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Towards co-creating a sense of place : a multilayered participatory approach, exploring learning spaces for doctoral education based on design-based research
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