Supporting Teachers’ Professional Development With Generative AI: The Effects on Higher Order Thinking and Self-Efficacy

IF 2.9 3区教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

IEEE Transactions on Learning Technologies Pub Date : 2024-02-26 DOI:10.1109/TLT.2024.3369690

Jijian Lu;Ruxin Zheng;Zikun Gong;Huifen Xu

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Abstract

Generative artificial intelligence (AI) has emerged as a noteworthy milestone and a consequential advancement in the annals of major disciplines within the domains of human science and technology. This study aims to explore the effects of generative AI-assisted preservice teaching skills training on preservice teachers’ self-efficacy and higher order thinking. The participants of this study were 215 preservice mathematics, science, and computer teachers from a university in China. First, a pretest–post-test quasi-experimental design was implemented for an experimental group (teaching skills training by generative AI) and a control group (teaching skills training by traditional methods) by investigating the teacher self-efficacy and higher order thinking of the two groups before and after the experiment. Finally, a semistructured interview comprising open-ended questions was administered to 25 preservice teachers within the experimental group to present their views on generative AI-assisted teaching. The results showed that the scores of preservice teachers in the experimental group, who used generative AI for teachers’ professional development, were considerably higher than those of the control group, both in teacher self-efficacy ( F = 8.589, p = 0.0084 < 0.05) and higher order thinking ( F = 7.217, p = 0.008 < 0.05). It revealed that generative AI can be effective in supporting teachers’ professional development. This study produced a practical teachers’ professional development method for preservice teachers with generative AI.

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用生成式人工智能支持教师专业发展：对高阶思维和自我效能的影响

生成式人工智能（AI）已成为人类科学技术领域主要学科发展史上值得关注的里程碑和重大进步。本研究旨在探讨生成式人工智能辅助职前教学技能培训对职前教师自我效能感和高阶思维的影响。本研究的参与者是来自中国某大学的 215 名职前数学、科学和计算机教师。首先，对实验组（采用生成式人工智能进行教学技能培训）和对照组（采用传统方法进行教学技能培训）进行了前测-后测的准实验设计，调查了实验前后两组教师的自我效能感和高阶思维。最后，对实验组的 25 名职前教师进行了由开放式问题组成的半结构化访谈，以了解他们对生成式人工智能辅助教学的看法。结果显示，实验组的职前教师在教师自我效能感（F = 8.589，p = 0.0084 < 0.05）和高阶思维（F = 7.217，p = 0.008 < 0.05）方面的得分都大大高于对照组，这说明生成式人工智能可以帮助教师提高专业发展。研究表明，生成式人工智能可以有效地支持教师的专业发展。本研究利用生成式人工智能为职前教师提供了一种实用的教师专业发展方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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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.