Empowering Preservice Teachers Through Textbook Design Activities With GAI-Based Chatbot

IF 4.9 3区教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

IEEE Transactions on Learning Technologies Pub Date : 2025-09-05 DOI:10.1109/TLT.2025.3606757

Jiutong Luo;Chunying Zhu;Lixin Hu;Meng Sun

引用次数: 0

Abstract

Generative artificial intelligence (GAI) has become an epoch-making technology in the educational context. With a quasi-experimental repeated measure design and mixed-method data collection, this study examined the effects of the GAI-based chatbot in assisting preservice teachers in implementing the new national curriculum standards in Mainland China and their perceptions accordingly. A sample of 26 preservice teachers (divided into 13 teams) was included in this two-phrase study. Results showed that textbook design activities with the chatbot effectively promoted participants’ acquisition of content knowledge and improved self-efficacy, although it did not reduce teaching anxiety. Evidence was also extracted from participants’ open-ended responses with an extended COSTEM (i.e., content, others, self, tasks, ethics, and model) framework. Meanwhile, preservice teachers perceived both advantages and disadvantages regarding the utility of the GAI-based chatbot in learning. Implications of this study were also discussed.

查看原文本刊更多论文

基于ai的聊天机器人通过教科书设计活动赋予职前教师权力

在教育领域，生成式人工智能（GAI）已经成为一项划时代的技术。通过准实验重复测量设计和混合方法数据收集，本研究考察了基于ai的聊天机器人在协助中国大陆职前教师实施新国家课程标准方面的效果以及他们对新课程标准的看法。本研究以26名职前教师为样本，分为13个小组。结果表明，使用聊天机器人进行教材设计活动，有效促进了参与者对内容知识的获取，提高了自我效能感，但并没有减少教学焦虑。通过扩展COSTEM（即内容、他人、自我、任务、伦理和模型）框架，从参与者的开放式回答中提取证据。与此同时，职前教师认为基于ai的聊天机器人在学习中的应用既有优点也有缺点。本文还讨论了本研究的意义。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Transactions on Learning Technologies COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-

CiteScore

7.50

自引率

5.40%

发文量

审稿时长

>12 weeks

期刊介绍： The IEEE Transactions on Learning Technologies covers all advances in learning technologies and their applications, including but not limited to the following topics: innovative online learning systems; intelligent tutors; educational games; simulation systems for education and training; collaborative learning tools; learning with mobile devices; wearable devices and interfaces for learning; personalized and adaptive learning systems; tools for formative and summative assessment; tools for learning analytics and educational data mining; ontologies for learning systems; standards and web services that support learning; authoring tools for learning materials; computer support for peer tutoring; learning via computer-mediated inquiry, field, and lab work; social learning techniques; social networks and infrastructures for learning and knowledge sharing; and creation and management of learning objects.