ATTENPlay: A Game-Based Attention Network Test for Autistic Children

要旨

Atypical attention in Autism Spectrum Disorder (ASD) presents challenges to children's learning and daily functioning. Traditional assessments like the Attention Network Test (ANT) often fail to engage autistic children due to their abstract and repetitive nature, leading to low task completion and limited data. To address this gap, we developed ATTENPlay on a tablet, a game-based assessment from a systematic, expert-led co-design process that translates ANT tasks into a child-friendly narrative with single-tap interactions. We conducted a study with 52 children (28 autistic, 24 neurotypical) to evaluate the proposed ATTENPlay. Our findings indicate ATTENPlay significantly improves usability and user experience compared to the traditional paradigm. The assessment also captured interpretable cognitive data, revealing significant group differences in both the orienting and executive control networks. This work contributes a game-based tool that supports more accessible attention network testing for autistic children and demonstrates an inclusive design process for creating cognitive assessments.

受賞
Honorable Mention
著者
Yuying Wan
The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China
Xin Tong
The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China
Kaishun Wu
The Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: AI, Learning and Inclusion in Education

P1 - Room 114
7 件の発表
2026-04-16 20:15:00
2026-04-16 21:45:00