Minh Tran
ABSTRACT
The power of large language models has opened up opportunities for educational use. In computing education, recent studies have demonstrated the potential of these models to improve learning and teaching experiences in university-level programming courses. However, research into leveraging them to aid computer science instructors in curriculum development and course material design is relatively sparse, especially at the K-12 level. This work aims to fill this gap by exploring the capability of large language models in ideating and designing culturally responsive projects for elementary and middle school programming classes. Our ultimate goal is to support K-8 teachers in effectively extracting suggestions from large language models by only using natural language modifications. Furthermore, we aim to develop a comprehensive assessment framework for culturally responsive AI-generated project ideas. We also hope to provide valuable insight into teachers’ perspectives on large language models and their integration into teaching practices.
Supplemental Material
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Index Terms
- Prompt Engineering for Large Language Models to Support K-8 Computer Science Teachers in Creating Culturally Responsive Projects
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