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Feedback on Student Programming Assignments: Teaching Assistants vs Automated Assessment Tool

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Original language

English

Article number

2

Pages 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, USA

Publisher

Association for Computing Machinery, United States

ISBN (Electronic)

9798400716539

Publication 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, 2023

Host 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.

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Captures
22
Citations
7

Related Event

Title

Koli Calling International Conference on Computing Education Research

Event type

Conference

Degree of recognition

International event

Date

13/11/2023 - 18/11/2023

Location

KoliFinland