Nuodi Zhang , Fengfeng ke , Chih-Pu Dai , Alex Barrett , Saptarshi Bhowmik , Sherry A. Southerland , Luke A. West , Xin Yuan
{"title":"通过对学生资源的即时解读来增强响应式教学:人工智能支持的虚拟仿真研究","authors":"Nuodi Zhang , Fengfeng ke , Chih-Pu Dai , Alex Barrett , Saptarshi Bhowmik , Sherry A. Southerland , Luke A. West , Xin Yuan","doi":"10.1016/j.compedu.2025.105449","DOIUrl":null,"url":null,"abstract":"<div><div>Responsive teaching, a pedagogical approach that foregrounds and builds instruction on student ideas, requires teachers to attend to and build on student resources. However, teachers' interpretations of student resources, especially during live teaching, remain understudied. In this study, we examined <em>in-the-moment interpretations</em>, teachers' real-time sense-making of and reflection on students' epistemic and emotional resources, and explored how teachers' in-the-moment interpretations can support their responsive teaching talk moves and knowledge. Employing a convergent mixed-methods research design, we designed and implemented a generative artificial intelligence (AI)-supported virtual simulation as a pedagogical sandbox for 40 preservice teachers (PSTs) to practice teaching with virtual students, interpret student resources, and act on these interpretations in real time. Linear regression analysis was conducted and found that PSTs’ in-the-moment interpretations are significant predictors of their responsive teaching talk moves and knowledge. Qualitative thematic analysis identified themes that corroborated and extended the findings of the quantitative component. Implications for teacher education and simulation design are discussed.</div></div>","PeriodicalId":10568,"journal":{"name":"Computers & Education","volume":"239 ","pages":"Article 105449"},"PeriodicalIF":10.5000,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhancing responsive teaching through in-the-moment interpretations of student resources: A study in AI-supported virtual simulation\",\"authors\":\"Nuodi Zhang , Fengfeng ke , Chih-Pu Dai , Alex Barrett , Saptarshi Bhowmik , Sherry A. Southerland , Luke A. West , Xin Yuan\",\"doi\":\"10.1016/j.compedu.2025.105449\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Responsive teaching, a pedagogical approach that foregrounds and builds instruction on student ideas, requires teachers to attend to and build on student resources. However, teachers' interpretations of student resources, especially during live teaching, remain understudied. In this study, we examined <em>in-the-moment interpretations</em>, teachers' real-time sense-making of and reflection on students' epistemic and emotional resources, and explored how teachers' in-the-moment interpretations can support their responsive teaching talk moves and knowledge. Employing a convergent mixed-methods research design, we designed and implemented a generative artificial intelligence (AI)-supported virtual simulation as a pedagogical sandbox for 40 preservice teachers (PSTs) to practice teaching with virtual students, interpret student resources, and act on these interpretations in real time. Linear regression analysis was conducted and found that PSTs’ in-the-moment interpretations are significant predictors of their responsive teaching talk moves and knowledge. Qualitative thematic analysis identified themes that corroborated and extended the findings of the quantitative component. Implications for teacher education and simulation design are discussed.</div></div>\",\"PeriodicalId\":10568,\"journal\":{\"name\":\"Computers & Education\",\"volume\":\"239 \",\"pages\":\"Article 105449\"},\"PeriodicalIF\":10.5000,\"publicationDate\":\"2025-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & Education\",\"FirstCategoryId\":\"95\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0360131525002179\",\"RegionNum\":1,\"RegionCategory\":\"教育学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Education","FirstCategoryId":"95","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0360131525002179","RegionNum":1,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Enhancing responsive teaching through in-the-moment interpretations of student resources: A study in AI-supported virtual simulation
Responsive teaching, a pedagogical approach that foregrounds and builds instruction on student ideas, requires teachers to attend to and build on student resources. However, teachers' interpretations of student resources, especially during live teaching, remain understudied. In this study, we examined in-the-moment interpretations, teachers' real-time sense-making of and reflection on students' epistemic and emotional resources, and explored how teachers' in-the-moment interpretations can support their responsive teaching talk moves and knowledge. Employing a convergent mixed-methods research design, we designed and implemented a generative artificial intelligence (AI)-supported virtual simulation as a pedagogical sandbox for 40 preservice teachers (PSTs) to practice teaching with virtual students, interpret student resources, and act on these interpretations in real time. Linear regression analysis was conducted and found that PSTs’ in-the-moment interpretations are significant predictors of their responsive teaching talk moves and knowledge. Qualitative thematic analysis identified themes that corroborated and extended the findings of the quantitative component. Implications for teacher education and simulation design are discussed.
期刊介绍:
Computers & Education seeks to advance understanding of how digital technology can improve education by publishing high-quality research that expands both theory and practice. The journal welcomes research papers exploring the pedagogical applications of digital technology, with a focus broad enough to appeal to the wider education community.