Personalized Worked Example Generation from Student Code Submissions Using Pattern-based Knowledge Components
Adaptive programming practice often relies on fixed libraries of worked examples and practice problems, which require substantial authoring effort and may not correspond well to the logical errors and partial solutions students produce while writing code. As a result, students may receive learning content that does not directly address the concepts they are working to understand, while instructors must either invest additional effort in expanding content libraries or accept a coarse level of personalization. We present an approach for knowledge-component (KC) guided educational content generation using pattern-based KCs extracted from student code. Given a problem statement and student su...
| Authors | Griffin Pitts, Muntasir Hoq, Peter Brusilovsky et al. |
|---|---|
| Primary category | cs.HC |
| Published | 27 April 2026 |
| Last updated at source | 5 May 2026 |
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