Empowering student query debugging : feedback for aggregate queries via provenance summarization
department or school: Science, Faculty of
department or school: Computer Science, Department of
data provider: DSpace
degree campus: UBCV
creator: Huang, Jingxuan
issued: 2024-06-24T17:02:55Z
issued: 2024
related degree: Master of Science - MSc
degree grantor: University of British Columbia
description: Data provenance contains valuable information about the data involved in a query and the process it underwent to produce the output. Despite extensive research on different data provenance models and their characteristics, its potential in query debugging has not been fully exploited. Observing students’ struggle in writing aggregate queries, we adapted a provenance summarization technique for pedagogical purposes and introduced a novel feedback approach to assist students in query debugging. Our user study confirmed the effectiveness and helpfulness of this technique.
aggregated CHO: https://circle.library.ubc.ca/rest/handle/2429/88504
note: Empowering Student QueryDebugging: Feedback for AggregateQueries via ProvenanceSummarizationbyJingxuan HuangB.Sc., Nanjing University, 2022A THESIS SUBMITTED IN PARTIAL FULFILLMENT OFTHE REQUIREMENTS FOR THE DEGREE OFMASTER OF SCIENCEinThe Faculty of Graduate and Postdoctoral Studies(Computer Science)THE UNIVERSITY OF BRITISH COLUMBIA(Vancouver)June 2024© Jingxuan Huang 2024The following individuals certify that they have read, and recommend tothe Faculty of Graduate and Postdoctoral Studies for acceptance, the thesisentitled:Empowering Student Query Debugging: Feedback for Aggregate Queriesvia Provenance Summarizationsubmitted by Jingxuan Huang in partial fulfillment of the requirements forthe degree of Master of Sciencein Computer ScienceExamining Committee:Rachel Pottinger, Professor, Computer Science, UBCSupervisorEd Knorr, Associate Professor Emeritus of Teaching, Computer Science, UBCSupervisory Committee MemberiiAbstractData provenance contains valuable information about the data involved ina query and the process it underwent to produce the output. Despite exten-sive research on different data provenance models and their characteristics,its potential in query debugging has not been fully exploited. Observingstudents’ struggle in writing aggregate queries, we adapted a provenancesummarization technique for pedagogical purposes and introduced a novelfeedback approach to assist students in query debugging. Our user studyconfirmed the effectiveness and helpfulness of this technique.iiiLay SummaryAs data volumes grow, the ability to query relational databases becomes es-sential for students regardless of their discipline or chosen profession. How-ever, it can be challenging to master query writing skills, and students oftenstruggle to identify errors in their queries and make necessary revisions.To address this issue, we propose a novel feedback mechanism designedto help students debug their queries. This feedback leverages data prove-nance, which refers to the i…
has type: Thesis/Dissertation
date issued: 2024-11
is shown at: 10.14288/1.0444013
language: eng
degree discipline: Computer Science
provider: Vancouver : University of British Columbia Library
publisher: University of British Columbia
rights: Attribution-NonCommercial-NoDerivatives 4.0 International
rights URI: http://creativecommons.org/licenses/by-nc-nd/4.0/
scholar level: Graduate
contributor: Pottinger, Rachel
type: Text
identifier URI: http://hdl.handle.net/2429/88504