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Project Information

Name: Real-time visual feedback: a study in coding analytics
Abstract     Higher dropout and failure rates among computer science students in introductory programming courses tend to be a norm for many institutions. Years of evidence indicate that dropouts and failures persist in spite of advancements in pedagogy, technology, and teacher training. Most advancements have relied on summative assessments and of late formative assessments. This research explores assessments computed from real-time measures, based on observational data collected during student engagement with study and remedial activities. An experiment was conducted to measure the impact of real-time code assessment and dashboard-based feedback in the domain of Programming. Results indicate better course grades for a small percentage of students, and the need for task-level and meta-level interactions to guarantee significant and persistent academic performance and programming mastery.
Start Date 2017-07-03
End Date 2017-07-07
Research Areas
Artificial Intelligencecausal modellingknowledge tracing
Learning Analytics
Funding Source Name Amount
Athabasca University1,400
Collaboration Type Collaborator
AcademicAthabasca University, Canada
Faculty Researcher(s) Role
Vivek KumarPrincipal investigator

Updated March 16 2017 by FST Technical Staff

AU, CANADA'S OPEN UNIVERSITY, is an internationally recognized leader in online and distance learning.