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2 resources

  • Yiqiu Zhou, Maciej Pankiewicz, Luc Paque...
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    journalArticle
    Yiqiu Zhou, Maciej Pankiewicz, Luc Paque...

    This study examines how Large Language Model (LLM) feedback generated for compiler errors impacts learners’ persistence in programming tasks within a system for automated assessment of programming assignments. Persistence, the ability to maintain effort in the face of challenges, is crucial for academic success but can sometimes lead to unproductive "wheel spinning" when students struggle without progress. We investigated how additional LLM feedback based on the GPT-4 model, provided for...

  • Xiner Liu, Andrés Zambrano, Ryan Baker
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    Mar 5th, 2025
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    journalArticle
    Xiner Liu, Andrés Zambrano, Ryan Baker
    Mar 5th, 2025

    This study explores the potential of the large language model GPT-4 as an automated tool for qualitative data analysis by educational researchers, exploring which techniques are most successful for different types of constructs. Specifically, we assess three different prompt engineering strategies-Zero-shot, Few-shot, and Few-shot with contextual information-as well as the use of embeddings. We do so in the context of qualitatively coding three distinct educational datasets: Algebra I...

Last update from database: 27/10/2025, 18:15 (UTC)
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