Robots in Inclusive Education of Students With Autism Spectrum Disorder

IF 7.4 3区 教育学 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
IEEE Transactions on Learning Technologies Pub Date : 2026-01-01 Epub Date: 2026-03-22 DOI:10.1109/TLT.2026.3696075
Kaloyan Damyanov
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引用次数: 0

Abstract

This study examines how humanoid and social robots affect social and communication skills in inclusive education for children with autism spectrum disorder (ASD). A mixed-methods approach is used to collect and analyze data using quantitative and qualitative methods. The study includes 30 children with ASD who use NAO, Pepper, and KASPAR robots for 12 weeks. The main task is to diagnose children’s social sensitivity and communication skills before and after using robots in education to evaluate this approach. Children’s social adaptation and robot-mediated interaction are associated with significant improvements, particularly in nonverbal communication and social interaction. Robots can make learning more inclusive and supportive, according to the study. The study examines robotic therapy development theory, including its pros and cons. The analysis focuses on successful ASD teaching methods in Norway, Japan, Bulgaria, and the USA, where inclusive education and advanced technologies are used to support students with special needs. Based on the data, practical recommendations are developed for teachers on how to integrate robots into teaching, for policymakers on equal access to technology, and for developers of robotic systems that focus on the needs of children with ASD.
自闭症谱系障碍学生全纳教育中的机器人
本研究探讨了类人机器人和社交机器人如何影响自闭症谱系障碍(ASD)儿童全纳教育中的社交和沟通技能。混合方法的方法是使用定量和定性的方法来收集和分析数据。这项研究包括30名自闭症儿童,他们使用NAO、Pepper和KASPAR机器人12周。主要任务是诊断儿童在使用机器人教育前后的社会敏感性和沟通技巧,以评估这种方法。儿童的社会适应和机器人介导的互动与显著改善有关,特别是在非语言沟通和社会互动方面。根据这项研究,机器人可以使学习更具包容性和支持性。该研究考察了机器人治疗发展理论,包括其优点和缺点。分析重点是挪威、日本、保加利亚和美国成功的ASD教学方法,在这些国家,全纳教育和先进技术被用于支持有特殊需求的学生。根据这些数据,为教师提供了如何将机器人融入教学的实用建议,为政策制定者提供了平等获取技术的机会,为专注于自闭症儿童需求的机器人系统开发者提供了实用建议。
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
IEEE Transactions on Learning Technologies
IEEE Transactions on Learning Technologies COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
7.50
自引率
5.40%
发文量
82
审稿时长
>12 weeks
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.
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