Personalized Worked Example Generation from Student Code Submissions using Pattern-based Knowledge Components

ArXi:2604.24758v1 Announce Type: cross 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.