Education

Investigating students’ programming behaviors, interaction qualities and perceptions through prompt-based learning in ChatGPT

D. Sun, A. Boudouaia, et al.

This study, conducted by Dan Sun, Azzeddine Boudouaia, Junfeng Yang, and Jie Xu, reveals how specifically designed prompts can significantly enhance programming learning outcomes using ChatGPT. Through mixed-methods analysis, it was found that students engaged more effectively in coding and debugging and received precise feedback, leading to improved perceptions of ChatGPT's usability and learning efficiency.

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Abstract

This study investigated the impact of specifically designed prompts on programming learning outcomes using ChatGPT. A quasi-experimental framework compared prompt-based learning (PbL) and unprompted learning (UL) conditions on 30 college students. Mixed-methods analysis revealed that PbL students engaged more in coding and debugging, formulated more complex queries, and received more precise feedback. PbL participants showed improved perceptions of ChatGPT's usefulness, ease of use, and intention to use, particularly regarding attitude. Structured prompts enhanced problem-solving understanding and learning efficiency.

Publisher

HUMANITIES AND SOCIAL SCIENCES COMMUNICATIONS

Published On

Oct 31, 2024

Authors

Dan Sun, Azzeddine Boudouaia, Junfeng Yang, Jie Xu

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