Automated Questionnaires About Students’ JavaScript Programs: Towards Gauging Novice Programming Processes
Open accessAbstract
Students sometimes manage to produce functionally correct program code while having a fragile understanding of the related learning goals. Such unproductive success could be intercepted by an educator who asks questions that target the structure and evaluation of the student’s program using the constructs and identifiers in the code. We provide a tool that automatically generates multiple-choice questions of seven different types for this purpose. We integrated these questions into a web-based program writing exercises, which we also publish as a part of this work, and successfully used them on an introductory programming course. In our pilot evaluation of the tool, we found that the students who answer these questions repeatedly incorrectly are likely to drop out, have more challenges while writing a program, and resort to tinkering behavior.
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AI-generated code examples and explanations could be used as ready-made materials for code review sessions and could inspire new types of assignments that are automatically generated and possibly automatically assessed using techniques like 'questions about learner's code'.
“These could be used as ready-made materials for code review sessions for students, but could also inspire new types of assignment that are automatically generated and possibly automatically assessed using, for example, the 'questions about learner's code' technique [20].”
From Instructor Perceptions of AI Code Generation Tools - A Multi-Institutional Interview Study (2024) · cites this paper as [20]
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References 35 · Cited by 17
Research works printed but not linked: 4
- Ibrahim Albluwi. 2019. Plagiarism in programming assessments: a systematic review. ACM Transactions on Computing Education (TOCE) 20, 1 (2019), 1-28.
- Roya Hosseini, Arto Vihavainen, and Peter Brusilovsky. 2014. Exploring Problem Solving Paths in a Java Programming Course. In Psychology of Programming Interest Group Conference, PPIG 2014. 65 -76. http://d-scholarship.pitt.edu/21832/
- Amruth N Kumar. 2018. Epplets: a tool for solving parsons puzzles. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education. 527-532.
- Dale Parsons and Patricia Haden. 2006. Parson's programming puzzles: a fun and effective learning tool for first programming courses. In Proceedings of the 8th Australasian Conference on Computing Education-Volume 52. 157-163.
- Authors
- Lehtinen, T., Haaranen, L., & Leinonen, J.
- Affiliations
- Aalto University (FI)
- Venue
- Proceedings of the 25th Australasian Computing Education Conference
- Publisher
- ACM
- Published
- 2023-01-30
- Pages
- 49-58
- OpenAlex
- W4317502083
- Cited by
- 17
- References
- 35
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 7 · 2023: 3
- FWCI
- 5.14
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Australasian Computing Education Conference (publishedVersion, cc-by)
- Aaltodoc (Aalto University) (submittedVersion, cc-by)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- automatic question generation, multiple-choice questions, JavaScript, novice programmers, introductory programming, program comprehension, program evaluation, school dropout, programming education
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