{"title":"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","authors":"Jijian Lu;Ruxin Zheng;Zikun Gong;Huifen Xu","doi":"10.1109/TLT.2024.3369690","DOIUrl":null,"url":null,"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 (\n<italic>F</i>\n = 8.589, \n<italic>p</i>\n = 0.0084 < 0.05) and higher order thinking (\n<italic>F</i>\n = 7.217, \n<italic>p</i>\n = 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.","PeriodicalId":49191,"journal":{"name":"IEEE Transactions on Learning Technologies","volume":"17 ","pages":"1279-1289"},"PeriodicalIF":2.9000,"publicationDate":"2024-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Supporting Teachers’ Professional Development With Generative AI: The Effects on Higher Order Thinking and Self-Efficacy\",\"authors\":\"Jijian Lu;Ruxin Zheng;Zikun Gong;Huifen Xu\",\"doi\":\"10.1109/TLT.2024.3369690\",\"DOIUrl\":null,\"url\":null,\"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 (\\n<italic>F</i>\\n = 8.589, \\n<italic>p</i>\\n = 0.0084 < 0.05) and higher order thinking (\\n<italic>F</i>\\n = 7.217, \\n<italic>p</i>\\n = 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.\",\"PeriodicalId\":49191,\"journal\":{\"name\":\"IEEE Transactions on Learning Technologies\",\"volume\":\"17 \",\"pages\":\"1279-1289\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-02-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Learning Technologies\",\"FirstCategoryId\":\"95\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10444988/\",\"RegionNum\":3,\"RegionCategory\":\"教育学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Learning Technologies","FirstCategoryId":"95","ListUrlMain":"https://ieeexplore.ieee.org/document/10444988/","RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Supporting Teachers’ Professional Development With Generative AI: The Effects on Higher Order Thinking and Self-Efficacy
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.
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.