教师教育中的人工智能:开启教学支持、全纳学习和数字素养的新维度

IF 5.1 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Journal of Computer Assisted Learning Pub Date : 2024-04-25 DOI:10.1111/jcal.12988
Jia Zhang, Zhuo Zhang
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引用次数: 0

摘要

本定量研究调查了将人工智能纳入师范教育的机遇、困难和后果。研究通过结构化问卷收集了 202 名大学生和 68 名教职员工的数据,并使用 SPSS 软件进行了分析。本研究通过深入调查人工智能对师范教育的各种影响,做出了新颖的贡献。它从有益的角度探讨了可能带来的益处和挑战,揭示了人工智能在未来可能给学习和教学领域以及教学方法带来的深远变化。研究试图从五个主要方面评估采用人工智能对师范教育的影响:(i) 人工智能对教学支持和课堂管理的影响,(ii) 人工智能在创建包容性和无障碍学习环境方面的作用,(iii) 人工智能对提高教师数字素养和计算机技能的贡献,以及增强数字教学资源的获取,(iv) 人工智能对识别学生学习风格和促进采用多样化教学方法的积极影响,以及(v) 人工智能在通过改善互动加强师生关系方面的作用。研究结果阐明了人工智能在教师教育领域带来的大好机会,以及在有效融合人工智能教育环境方面需要解决的障碍。
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AI in teacher education: Unlocking new dimensions in teaching support, inclusive learning, and digital literacy

Background

AI can positively influence teaching by offering support for classroom management, creating inclusive learning environments, enhancing digital skills, personalizing teaching methods, and strengthening teacher-student relationships.

Objectives

This quantitative research study investigates the opportunities, difficulties, and consequences of incorporating AI into teacher education.

Methods

Data were collected through structured questionnaires from 202 college students and 68 staff members. The analysis was conducted using SPSS software.

Results

The study provides a novel contribution by its thorough investigation of the diverse effects of AI on teacher education. It offers beneficial perspectives on the possible benefits and challenges, illuminating the far-reaching changes that AI could bring to the terrain of learning and instruction and teaching methods in the time yet to come. The research sought to assess the effect of AI adoption in teacher education across five main dimensions: (i) its influence on teaching support and classroom management, (ii) its role in creating inclusive and accessible learning environments, (iii) its contribution to improving teachers' digital literacy and computer skills, and enhancing access to digital teaching resources, (iv) its positive influence on identifying students' learning styles and facilitating the adoption of diverse teaching methods, and (v) its role in strengthening teacher-student relationships through improved interactions.

Conclusion

The findings elucidate the promising opportunities that AI presents in the field of teacher education, along with the obstacles that require resolution for the effective fusion of AI educational settings.

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来源期刊
Journal of Computer Assisted Learning
Journal of Computer Assisted Learning EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
9.70
自引率
6.00%
发文量
116
期刊介绍: The Journal of Computer Assisted Learning is an international peer-reviewed journal which covers the whole range of uses of information and communication technology to support learning and knowledge exchange. It aims to provide a medium for communication among researchers as well as a channel linking researchers, practitioners, and policy makers. JCAL is also a rich source of material for master and PhD students in areas such as educational psychology, the learning sciences, instructional technology, instructional design, collaborative learning, intelligent learning systems, learning analytics, open, distance and networked learning, and educational evaluation and assessment. This is the case for formal (e.g., schools), non-formal (e.g., workplace learning) and informal learning (e.g., museums and libraries) situations and environments. Volumes often include one Special Issue which these provides readers with a broad and in-depth perspective on a specific topic. First published in 1985, JCAL continues to have the aim of making the outcomes of contemporary research and experience accessible. During this period there have been major technological advances offering new opportunities and approaches in the use of a wide range of technologies to support learning and knowledge transfer more generally. There is currently much emphasis on the use of network functionality and the challenges its appropriate uses pose to teachers/tutors working with students locally and at a distance. JCAL welcomes: -Empirical reports, single studies or programmatic series of studies on the use of computers and information technologies in learning and assessment -Critical and original meta-reviews of literature on the use of computers for learning -Empirical studies on the design and development of innovative technology-based systems for learning -Conceptual articles on issues relating to the Aims and Scope
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