Tang, Kaiyuan;
Chen, Kerui;
Jiang, Zhou;
Quinlan, Mark;
Cho, Youngjun;
(2025)
Exploring LLM Agents as Interactive Mind Map Creators Tailored for Students with ADHD.
In: Bianchi, Andrea and Glassman, Elena and Mackay, Wendy E and Zhao, Shengdong and Kim, Jeeeun and Oakley, Ian, (eds.)
UIST Adjunct '25: Adjunct Proceedings of the 38th Annual ACM Symposium on User Interface Software and Technology.
(pp. pp. 1-6).
ACM (Association for Computing Machinery): New York, NY, USA.
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Abstract
Students with Attention Deficit Hyperactivity Disorder (ADHD) often struggle with traditional text-based learning materials due to executive function deficits that affect their ability to process, organise, and retain information. While the rapid development of Large Language Models (LLMs) has sparked innovation in generative user interfaces, existing products fail to address the specific learning challenges faced by students with ADHD. We introduce a novel approach that leverages LLM agents as interactive mind-map creators specifically designed to support ADHD learners. Our solution automatically transforms dense text-based documents into interactive, ADHD-friendly interactive mind maps. These dynamic visual representations allow students to engage with learning tasks, explore content node by node, asking questions, and monitoring their learning progress. initial evaluation indicates improvements in four key areas: increased motivation to engage with learning materials, enhanced concentration during study sessions, better task planning and organisation skills, and improved ability to extract and understand main ideas from complex texts. By specifically addressing the needs of neurodivergent learners, this research contributes to the emerging field of LLM-powered generative user interfaces by demonstrating their potential as inclusive learning tools, opening up new avenues for exploration.
| Type: | Proceedings paper |
|---|---|
| Title: | Exploring LLM Agents as Interactive Mind Map Creators Tailored for Students with ADHD |
| Event: | UIST '25: The 38th Annual ACM Symposium on User Interface Software and Technology |
| ISBN-13: | 9798400720369 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3746058.3759012 |
| Publisher version: | https://doi.org/10.1145/3746058.3759012 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | ADHD Learning Support, Generative User Interface, Large Language Models, Generative AI, Inclusive Technologies |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10215002 |
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