Challenges and Strategies in Personalised Planning Support for University Students with Autism

Publication date

2024-06-28

Authors

Cromjongh, RobinORCID 0009-0006-2245-7003ISNI 0000000518036594
Młocka, Maria
Akdağ Salah, A. A.ORCID 0000-0002-7204-5633ISNI 0000000050543653
Masthoff, J.F.M.ISNI 000000012419854X
Hauptmann, HannaORCID 0000-0002-6840-5341ISNI 0000000507309761

Editors

Advisors

Supervisors

Document Type

Part of book
Open Access logo

License

taverne

Abstract

Students in higher education with Autism Spectrum Disorder (ASD) face many challenges that might differ from their neurotypical peers. One area where students with autism face deficits is planning. This paper looks into the challenges faced and the strategies applied for planning by students with autism compared to neurotypical students. We aim to identify where personalisation and adaptivity may help them become independent and effective in their planning behaviour. This research indicates which personalisation needs designers of assistive technologies should consider for planning and task management. We present an online survey with 30 neurotypical students (NTS) and 34 students with (self-)diagnosed autism (ASDS) and interviews with six students with autism for more in-depth insights. Results indicate that ASDS experience problems with gaining a clear overview of what they need to do, knowing when they might do it, and following that plan to execution. In contrast to NTS, they also struggle with fitting routine household and self-care tasks into their schedule. We identified time-independent planning, identifying external pressure and defining sub-tasks as promising planning strategies for students with autism when combined with adaptation to their personal needs.

Keywords

adaptive systems, assistive technology, autism spectrum disorder (ASD), planning, task management, Taverne, Software

Citation

Cromjongh, R, Młocka, M, Akdağ Salah, A A, Masthoff, J & Hauptmann, H 2024, Challenges and Strategies in Personalised Planning Support for University Students with Autism. in UMAP 2024 - Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery, pp. 365-373. https://doi.org/10.1145/3631700.3664898