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Empowering student query debugging : feedback for aggregate queries via provenance summarization Huang, Jingxuan
Abstract
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.
Item Metadata
Title |
Empowering student query debugging : feedback for aggregate queries via provenance summarization
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Creator | |
Supervisor | |
Publisher |
University of British Columbia
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Date Issued |
2024
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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.
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Genre | |
Type | |
Language |
eng
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Date Available |
2024-06-24
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
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DOI |
10.14288/1.0444013
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2024-11
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Rights
Attribution-NonCommercial-NoDerivatives 4.0 International