Exploring Potential Application Areas of Artificial Intelligence-Infused System for Engagement Recognition: Insights from Special Education Experts
Name
3675094.3678376.pdf
Size
1.71 MB
Format
Adobe PDF
Checksum (MD5)
3caca5bf4de7ce21c33679089e24aa28
Author(s)
Kim, Won
Seong, Minwoo
DelPreto, Joseph
Matusik, Wojciech
Rus, Daniela
Kim, SeungJun
Date Issued
October 5, 2024
Publisher
ACM|Companion of the 2024 ACM International Joint Conference on Pervasive and Ubiquitous Computing
Citation
Kim, Won, Seong, Minwoo, DelPreto, Joseph, Matusik, Wojciech, Rus, Daniela et al. 2024. "Exploring Potential Application Areas of Artificial Intelligence-Infused System for Engagement Recognition: Insights from Special Education Experts."
Version
Final published version
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.
Description
UbiComp Companion ’24, October 5–9, 2024, Melbourne, VIC, Australia
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1145/3675094.3678376
