Early artificial intelligence education: Effects of cooperative play and direct instruction on kindergarteners' computational thinking, sequencing, self‐regulation and theory of mind skills

IF 5.1 2区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Journal of Computer Assisted Learning Pub Date : 2024-07-25 DOI:10.1111/jcal.13040

Jiahong Su, Weipeng Yang, Iris Heung Yue Yim, Hui Li, Xiao Hu

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Abstract

BackgroundWhile the integration of robot‐based learning in early childhood education has gained increasing attention in recent years, there is still a lack of evidence regarding the impact of AI robots on young children's learning.ObjectivesThe study explored the effectiveness of two AI education approaches in advancing kindergarteners' computational thinking, sequencing, self‐regulation and theory of mind skills.MethodsAn experiment was conducted with 90 kindergarteners (ages 5–6) randomly assigned to either a direct instruction (DI), cooperative play (CP) or control group.ResultsResults show that (1) children in all three groups had significant improvements on computational thinking, sequencing and self‐regulation; (2) both early AI education approaches (CP and DI) significantly enhance young children's computational thinking, sequencing, self‐regulation and theory of mind skills; (3) the DI group had significant higher improvement than the CP group on computational thinking; (4) the CP group exhibited greater enhancements in theory of mind skills than the DI group.ConclusionThese findings jointly demonstrate that each AI educational approach has unique strengths, underscoring the significance of designing new pedagogies to expand children's skills.

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早期人工智能教育：合作游戏和直接教学对幼儿园儿童计算思维、排序、自我调节和思维理论能力的影响

背景近年来，将基于机器人的学习融入幼儿教育的做法越来越受到关注，但关于人工智能机器人对幼儿学习的影响，目前仍缺乏证据。结果结果表明：(1) 三组儿童在计算思维、排序和自我调节方面都有显著提高；(2) 两种早期人工智能教育方法（CP 和 DI）都能显著提高幼儿的计算思维、排序、自我调节和心智理论技能；(3) DI 组在计算思维方面的提高显著高于 CP 组；(4) CP 组在心智理论技能方面的提高高于 DI 组。结论这些研究结果共同表明，每种人工智能教育方法都有其独特的优势，强调了设计新教学法以拓展儿童技能的重要性。

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

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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