Feedback on Student Programming Assignments: Teaching Assistants vs Automated Assessment Tool
- Nynne Grauslund Kristiansen,
- ,
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOpen access
Publication Information
Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOriginal language
EnglishArticle number
2Pages from-to (Number of pages)
Pages 2:1-2:10 (10 pages)Publication milestones
- Published - 2023
Publication status
Published - 2023
Place of publication
New York, NY, USAPublisher
Association for Computing Machinery, United StatesISBN (Electronic)
9798400716539Publication IDs
- Scopus: 85185534916
Host publication title
Proceedings of the 23rd Koli Calling International Conference on Computing Education Research, Koli Calling 2023, Koli, Finland, November 13-18, 2023Host publication editors
- Andreas Mühling
- Ilkka Jormanainen
Abstract
Existing research does not quantify and compare the differences between automated and manual assessment in the context of feedback on programming assignments. This makes it hard to reason about the effects of adopting automated assessment at the expense of manual assessment. Based on a controlled experiment involving N=117 undergraduate first-semester CS1 students, we compare the effects of having access to feedback from: i) only automated assessment, ii) only manual assessment (in the form of teaching assistants), and iii) both automated as well as manual assessment. The three conditions are compared in terms of (objective) task effectiveness and from a (subjective) student perspective.
The experiment demonstrates that having access to both forms of assessment (automated and manual) is superior both from a task effectiveness as well as a student perspective. We also find that the two forms of assessment are complementary: automated assessment appears to be better in terms of task effectiveness; whereas manual assessment appears to be better from a student perspective. Further, we found that automated assessment appears to be working better for men than women, who are significantly more inclined towards manual assessment. We then perform a cost/benefit analysis which leads to the identification of four equilibria that appropriately balance costs and benefits. Finally, this gives rise to four recommendations of when to use which kind or combination of feedback (manual and/or automated), depending on the number of students and the amount of per-student resources available. These observations provide educators with evidence-based justification for budget requests and considerations on when to (not) use automated assessment.
The experiment demonstrates that having access to both forms of assessment (automated and manual) is superior both from a task effectiveness as well as a student perspective. We also find that the two forms of assessment are complementary: automated assessment appears to be better in terms of task effectiveness; whereas manual assessment appears to be better from a student perspective. Further, we found that automated assessment appears to be working better for men than women, who are significantly more inclined towards manual assessment. We then perform a cost/benefit analysis which leads to the identification of four equilibria that appropriately balance costs and benefits. Finally, this gives rise to four recommendations of when to use which kind or combination of feedback (manual and/or automated), depending on the number of students and the amount of per-student resources available. These observations provide educators with evidence-based justification for budget requests and considerations on when to (not) use automated assessment.
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Related Event
Title
Koli Calling International Conference on Computing Education Research
Event type
ConferenceDegree of recognition
International eventDate
13/11/2023 - 18/11/2023Location
KoliFinland
