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

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Summary

Current adaptive programming practice relies on fixed example libraries that often don't align with students' specific coding errors, leading to less effective learning and high authoring effort. This paper proposes a novel method to automatically generate personalized worked examples directly from student code submissions. By utilizing pattern-based knowledge components, it aims to provide highly relevant learning content, thereby improving student understanding and significantly reducing the need for extensive manual content creation.

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