Automated Questionnaires About Students’ JavaScript Programs: Towards Gauging Novice Programming Processes

By Teemu Lehtinen, Lassi Haaranen, Juho Leinonen. 2023

24 citations recorded by the source corpus.

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.

Subfields: Computer Science Applications, Developmental and Educational Psychology, Software, Program Analysis & Verification, Human-Computer Interaction

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Citations in the corpus

Comparing Code Explanations Created by Students and Large Language Models (2023, background): “However, students struggle to explain their own code and the ability to explain code is a difficult skill to develop [20, 38].”