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

IF 10.5 1区 教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Nuodi Zhang , Fengfeng ke , Chih-Pu Dai , Alex Barrett , Saptarshi Bhowmik , Sherry A. Southerland , Luke A. West , Xin Yuan
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引用次数: 0

摘要

响应式教学是一种以学生思想为基础的教学方法,它要求教师关注学生资源并以学生资源为基础。然而,教师对学生资源的解读,特别是在现场教学中,仍未得到充分研究。在本研究中,我们考察了即时口译、教师对学生认知资源和情感资源的实时意义构建和反思,并探讨了教师的即时口译如何支持其响应式教学话语动作和知识。采用融合混合方法研究设计,我们设计并实现了一个生成式人工智能(AI)支持的虚拟仿真作为教学沙盒,供40名职前教师(pst)与虚拟学生一起实践教学,解释学生资源,并实时根据这些解释采取行动。线性回归分析发现,教师的即时口译是其响应性教学言语动作和知识的显著预测因子。定性专题分析确定了证实和扩展了定量组成部分的调查结果的主题。讨论了对教师教育和仿真设计的启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
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来源期刊
Computers & Education
Computers & Education 工程技术-计算机:跨学科应用
CiteScore
27.10
自引率
5.80%
发文量
204
审稿时长
42 days
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.
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