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논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2025.2
- 수록면
- 326 - 331 (6page)
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Enhancing argumentation skills is vital for developing critical thinking, communication, and problem- solving skills. While chatbots show promise in supporting these skills, passive learning with chatbots can limit their educational effectiveness. Facilitating active learning with chatbots that promote deep cognitive engagement is essential but remains underexplored. In this study, we developed ArguePro, a Large Language Model (LLM)-based chatbot designed to foster active learning by progressively deepening students’ cognitive engagement using the ICAP framework. To assess the impact of different engagement levels (active vs. passive) with chatbots on argumentation skills, we conducted a pretest-posttest quasi-experimental study with 20 undergraduate engineering students assigned to either active or passive learning groups. Results showed that active learning with the chatbot significantly improved argumentation skills by enhancing critical thinking and perspective-taking compared to passive learning. These findings offer insights into optimizing chatbot use to maximize learning outcomes.
목차
Abstract
1. Introduction
2. Background and related work
3. Methods
4. Results
5. Discussion
6. Conclusion
Reference
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