Impacts of interacting with an AI chatbot on preservice teachers' responsive teaching skills in math education

IF 5.1 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning Pub Date : 2024-11-08 DOI:10.1111/jcal.13091

Dabae Lee, Taekwon Son, Sheunghyun Yeo

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引用次数: 0

Abstract

Background

Artificial Intelligence (AI) technologies offer unique capabilities for preservice teachers (PSTs) to engage in authentic and real-time interactions using natural language. However, the impact of AI technology on PSTs' responsive teaching skills remains uncertain.

Objectives

The primary objective of this study is to examine whether interaction with a responsive AI-based chatbot that acts as a virtual student improves pre-service teachers' noticing abilities. The second objective is to compare how the presence or absence of chatbot responses affects changes in PSTs' questioning practices. Finally, the third objective is to investigate how the experience of interacting with the responsive virtual student affects PSTs' perceptions of the effectiveness of their questioning, their satisfaction with the interactions, and their confidence about interacting with a real student compared to the non-responsive chatbot.

Methods

A randomised controlled pre- and post-test design was used with 50 PSTs. PSTs' noticing, interaction with the chatbot, and post-survey data were collected, and a t-test was conducted to examine significant differences by group.

Results and Conclusion

In the experimental group, the virtual student responded to PSTs' questions, while in the control group, she did not. Notable differences were observed in their questioning practices.

Takeaways

Overall, AI-based chatbots hold promise for enhancing PSTs' responsive teaching skills. Future research is needed to examine the long-term impact of responsive chatbot use on PSTs' noticing skills.

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来源期刊

Journal of Computer Assisted Learning EDUCATION & EDUCATIONAL RESEARCH-

CiteScore

9.70

自引率

6.00%

发文量

116

期刊介绍： The Journal of Computer Assisted Learning is an international peer-reviewed journal which covers the whole range of uses of information and communication technology to support learning and knowledge exchange. It aims to provide a medium for communication among researchers as well as a channel linking researchers, practitioners, and policy makers. JCAL is also a rich source of material for master and PhD students in areas such as educational psychology, the learning sciences, instructional technology, instructional design, collaborative learning, intelligent learning systems, learning analytics, open, distance and networked learning, and educational evaluation and assessment. This is the case for formal (e.g., schools), non-formal (e.g., workplace learning) and informal learning (e.g., museums and libraries) situations and environments. Volumes often include one Special Issue which these provides readers with a broad and in-depth perspective on a specific topic. First published in 1985, JCAL continues to have the aim of making the outcomes of contemporary research and experience accessible. During this period there have been major technological advances offering new opportunities and approaches in the use of a wide range of technologies to support learning and knowledge transfer more generally. There is currently much emphasis on the use of network functionality and the challenges its appropriate uses pose to teachers/tutors working with students locally and at a distance. JCAL welcomes: -Empirical reports, single studies or programmatic series of studies on the use of computers and information technologies in learning and assessment -Critical and original meta-reviews of literature on the use of computers for learning -Empirical studies on the design and development of innovative technology-based systems for learning -Conceptual articles on issues relating to the Aims and Scope