Test Case-Informed Knowledge Tracing for Open-ended Coding Tasks

This paper introduces TIKTOC, a knowledge tracing framework that uses test case results and LLMs to model student knowledge in computer science education by predicting both whether code passes specific test cases and generating the open-ended code students might write. The method is evaluated on the CodeWorkout dataset of university-level programming problems.

Open-ended coding tasks, which ask students to construct programs according to certain specifications, are common in computer science education. Student modeling can be challenging since their open-ended nature means that student code can be diverse. Traditional knowledge tracing (KT) models that only analyze response correctness may not fully capture nuances in student knowledge from student code. In this paper, we introduce Test case-Informed Knowledge Tracing for Open-ended Coding (TIKTOC), a

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