Exploring Potential Application Areas of Artificial Intelligence-Infused System for Engagement Recognition: Insights from Special Education Experts

Active engagement where children with autism spectrum disorder (ASD) are involved (e.g., educational and social activities) plays a crucial role in enhancing their cognitive, motor, and social development. This offers opportunities to enhance overall development, including learning abilities, physical coordination, and social interactions. Indirect methods, leveraging sensors and artificial intelligence (AI), have exhibited potential for enhancing engagement predictions but have been primarily focused within specific fields, resulting in a gap that leads to limited generalizability of ASD studies. This gap, due to small ASD sample sizes, presents a significant challenge as the annual ASD population increases, highlighting the need for practical and applicable research solutions, especially for general learning. In this work, we conducted expert interviews to explore the potential application areas of AI-infused systems that provide three levels of engagement status for children with ASD, ranging from "not engaged and out of control" to "highly engaged." Interviews with special educators revealed five key application areas for AI-driven engagement recognition: social skills training, stereotyped behavior modification, support for leisure activities, effective tutoring, and independent daily living skills. These findings highlight the potential of adaptive AI interventions in improving educational and daily outcomes, advocating for expanded applications for children with ASD.

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Publication Details

Published
2024-09-22
DOI
https://doi.org/10.1145/3675094.3678376
Citations
5
Primary Topic
Education and Learning Interventions
Type
article
Field-Weighted Citation Impact
3.90
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article

Exploring Potential Application Areas of Artificial Intelligence-Infused System for Engagement Recognition: Insights from Special Education Experts

Wojciech Matusik, SeungJun Kim, Joseph DelPreto, Daniela L. Rus et al.
5 citations
Education and Learning Interventions
3.90
article

Exploring Potential Application Areas of Artificial Intelligence-Infused System for Engagement Recognition: Insights from Special Education Experts

Wojciech Matusik, SeungJun Kim, Joseph DelPreto, Daniela L. Rus, Won Kim, Minwoo Seong
article en
5 citations

Abstract

Active engagement where children with autism spectrum disorder (ASD) are involved (e.g., educational and social activities) plays a crucial role in enhancing their cognitive, motor, and social development. This offers opportunities to enhance overall development, including learning abilities, physical coordination, and social interactions. Indirect methods, leveraging sensors and artificial intelligence (AI), have exhibited potential for enhancing engagement predictions but have been primarily focused within specific fields, resulting in a gap that leads to limited generalizability of ASD studies. This gap, due to small ASD sample sizes, presents a significant challenge as the annual ASD population increases, highlighting the need for practical and applicable research solutions, especially for general learning. In this work, we conducted expert interviews to explore the potential application areas of AI-infused systems that provide three levels of engagement status for children with ASD, ranging from "not engaged and out of control" to "highly engaged." Interviews with special educators revealed five key application areas for AI-driven engagement recognition: social skills training, stereotyped behavior modification, support for leisure activities, effective tutoring, and independent daily living skills. These findings highlight the potential of adaptive AI interventions in improving educational and daily outcomes, advocating for expanded applications for children with ASD.

Gwangju Institute of Science and Technology (KR), Massachusetts Institute of Technology (US)
Openalex Percentile: Top 6%
Education and Learning Interventions
3.90
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