Artificial Intelligence for Supporting College Students with Attention-Deficit/Hyperactivity Disorder: Cognitive, Emotional, and Ethical Perspectives  

Authors

DOI:

https://doi.org/10.46328/ijonses.5915

Keywords:

Artificial intelligence, Attention-Deficit/Hyperactivity Disorder (ADHD), Higher education, Cognitive assistance, Emotional regulation, AI-driven interventions, Disclosure and data privacy

Abstract

College students with Attention-Deficit/Hyperactivity Disorder (ADHD) often face academic underperformance, executive functioning challenges, and emotional regulation difficulties that hinder persistence and success in higher education. Advances in artificial intelligence (AI) offer promising opportunities to provide adaptive support through innovative tools for personalized interventions and cognitive assistance. A literature search conducted across PubMed, ERIC, SpringerLink, ScienceDirect, PsycINFO, and IEEE Xplore identified peer-reviewed studies relevant to ADHD in higher education and the application of AI-based tools. Findings indicate that AI-based systems, including explainable AI models and biometric frameworks, can enhance risk estimation and pattern recognition related to ADHD symptomatology, while also raising concerns about responsible data governance. Importantly, these tools do not perform clinical diagnoses; rather, they support licensed professionals by aggregating and organizing data that may inform clinical decision-making. Generative and assistive technologies, such as ChatGPT, socially assistive robots, and mobile applications, have been found to enhance academic writing, self-regulation, and executive functioning; however, their adoption is limited by gaps in digital literacy and inconsistent institutional support. Ethical considerations, including privacy, algorithmic fairness, trust, and students’ willingness to disclose ADHD status, critically influence acceptance and effectiveness. The review highlights the importance of inclusive design, participatory development, and AI literacy training. When ethically implemented within institutional frameworks, AI-driven interventions can complement traditional services, fostering more accessible, supportive, and responsive learning environments for neurodivergent college students.

References

Baethge, C., Goldbeck-Wood, S., & Mertens, S. (2019). SANRA—a scale for the quality assessment of narrative review articles. Research Integrity and Peer Review, 4(1). https://doi.org/10.1186/s41073-019-0064-8

Baird, J., Stevenson, J. C., & Williams, D. C. (2000). THE QUARTERLY REVIEW OF BIOLOGY THE EVOLUTION OF ADHD: A DISORDER OF COMMUNICATION? In Thte Quarterly Review of Biology (Vol. 75, Issue 1).

Black, M. H., Helander, J., Segers, J., Ingard, C., Bervoets, J., de Puget, V. G., & Bölte, S. (2024). Resilience in the face of neurodivergence: A scoping review of resilience and factors promoting positive outcomes. In Clinical Psychology Review (Vol. 113). Elsevier Inc. https://doi.org/10.1016/j.cpr.2024.102487

Cortese, S., & Coghill, D. (2018). Twenty years of research on attention-deficit/hyperactivity disorder (ADHD): Looking back, looking forward. Evidence-Based Mental Health, 21(4), 173–176. https://doi.org/10.1136/ebmental-2018-300050

Doyle, A., Healy, O., Paterson, J., Lewis, K., & Treanor, D. (2024). What does an ADHD-friendly university look like? A case study from Ireland. International Journal of Educational Research Open, 7. https://doi.org/10.1016/j.ijedro.2024.100345

DuPaul, G. J., Weyandt, L. L., O’Dell, S. M., & Varejao, M. (2009). College students with ADHD: Current status and future directions. Journal of Attention Disorders, 13(3), 234–250. https://doi.org/10.1177/1087054709340650

Fichten, C., Jorgensen, M., Havel, A., Vo, C., Libman, E., Fichten, C., Jorgensen, M., Havel, A., Vo, C., & Libman, E. (2022a). AI-Based and Mobile Apps: Eight Studies Based on Post-Secondary Students’ Experiences. In Journal on Technology and Persons with Disabilities Santiago, J (Vol. 10). https://scholarworks.csun.edu/handle/10211.3/223460

Fichten, C., Jorgensen, M., Havel, A., Vo, C., Libman, E., Fichten, C., Jorgensen, M., Havel, A., Vo, C., & Libman, E. (2022b). AI-Based and Mobile Apps: Eight Studies Based on Post-Secondary Students’ Experiences. In Journal on Technology and Persons with Disabilities Santiago, J (Vol. 10). https://scholarworks.csun.edu/handle/10211.3/223460

Green, B. N., Johnson, C. D., & Adams, A. (2006). Writing narrative literature reviews for peer-reviewed journals: secrets of the trade.

Jafarian, N. R., & Kramer, A. W. (2025). AI-assisted audio-learning improves academic achievement through motivation and reading engagement. Computers and Education: Artificial Intelligence, 8. https://doi.org/10.1016/j.caeai.2024.100357

Kim, S., Lee, H., & Lee, K. (2021). Can the mmpi predict adult adhd? An approach using machine learning methods. Diagnostics, 11(6). https://doi.org/10.3390/diagnostics11060976

Lalwani, H., Elgarf, M., & Salam, H. (2024). Productivity CoachBot: a Social Robot Coach for University Students with ADHD. In Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction (HRI ’24) (Vol. 1). https://doi.org/XXXXXXX.XXXXXXX

Lee, H. J., Belitz, C., Nasiar, N., & Bosch, N. (2025). XAI Reveals the Causes of Attention Deficit Hyperactivity Disorder (ADHD) Bias in Student Performance Prediction. 15th International Conference on Learning Analytics and Knowledge, LAK 2025, 418–428. https://doi.org/10.1145/3706468.3706521

Liu, X.-Q., Guo, Y.-X., & Xu, Y. (2023). Risk factors and digital interventions for anxiety disorders in college students: Stakeholder perspectives. World Journal of Clinical Cases, 11(7), 1442–1457. https://doi.org/10.12998/wjcc.v11.i7.1442

Mikolas, P., Vahid, A., Bernardoni, F., Süß, M., Martini, J., Beste, C., & Bluschke, A. (2022). Training a machine learning classifier to identify ADHD based on real-world clinical data from medical records. Scientific Reports, 12(1), 12934. https://doi.org/10.1038/s41598-022-17126-x

O’Connell. (2024). Design and Evaluation of a Socially Assistive Robot Schoolwork Companion for College Students with ADHD. 533–542.

Pagespetit, È., Pagerols, M., Barrés, N., Prat, R., Martínez, L., Andreu, M., Prat, G., Casas, M., & Bosch, R. (2025). ADHD and Academic Performance in College Students: A Systematic Review. Journal of Attention Disorders, 29(4), 281–297. https://doi.org/10.1177/10870547241306554

Pierrès, O., Darvishy, A., & Christen, M. (2025). Perceived Risks and Benefits of Disclosing ADHD to AI-based Educational Technologies: Semi-structured Interviews. https://doi.org/10.21203/rs.3.rs-6106311/v1

Sedgwick-Müller, J. A., Müller-Sedgwick, U., Adamou, M., Catani, M., Champ, R., Gudjónsson, G., Hank, D., Pitts, M., Young, S., & Asherson, P. (2022). University students with attention deficit hyperactivity disorder (ADHD): a consensus statement from the UK Adult ADHD Network (UKAAN). BMC Psychiatry, 22(1). https://doi.org/10.1186/s12888-022-03898-z

Staley, B. S., Robinson, L. R., Claussen, A. H., Katz, S. M., Danielson, M. L., Summers, A. D., Sherry, ;, Farr, L., Blumberg, S. J., & Tinker, S. C. (2024). Morbidity and Mortality Weekly Report Attention-Deficit/Hyperactivity Disorder Diagnosis, Treatment, and Telehealth Use in Adults-National Center for Health Statistics Rapid Surveys System, United States, October-November 2023. https://www.cdc.gov/mmwr/mmwr_continuingEducation.html

Stubbe, D. E. (2000). ATTENTION-DEFICIT I HYPERACTIVITY DISORDER OVERVIEW Historical Perspective, Current Controversies, and Future Directions (Vol. 9, Issue 3).

Sukhera, J. (2022). Narrative Reviews: Flexible, Rigorous, and Practical. Journal of Graduate Medical Education, 14(4), 414–417. https://doi.org/10.4300/JGME-D-22-00480.1

Tricco, A. C., Lillie, E., Zarin, W., O’Brien, K. K., Colquhoun, H., Levac, D., Moher, D., Peters, M. D. J., Horsley, T., Weeks, L., Hempel, S., Akl, E. A., Chang, C., McGowan, J., Stewart, L., Hartling, L., Aldcroft, A., Wilson, M. G., Garritty, C., … Straus, S. E. (2018). PRISMA extension for scoping reviews (PRISMA-ScR): Checklist and explanation. In Annals of Internal Medicine (Vol. 169, Issue 7, pp. 467–473). American College of Physicians. https://doi.org/10.7326/M18-0850

Weyandt, L. L., & DuPaul, G. (2006). ADHD in college students. In Journal of Attention Disorders (Vol. 10, Issue 1, pp. 9–19). https://doi.org/10.1177/1087054705286061

Wilder, T. L., & Stratchan, N. E. (2025). Artificial Intelligence-Enhanced Interview Success: Leveraging Eye-Tracking and Cognitive Measures to Support Self-Regulation in College Students with Attention-Deficit/Hyperactivity Disorder. Education Sciences, 15(2). https://doi.org/10.3390/educsci15020165

Wolf, L. E. (2001). College students with ADHD and other hidden disabilities: Outcomes and interventions. In Annals of the New York Academy of Sciences (Vol. 931, pp. 385–395). Blackwell Publishing Inc. https://doi.org/10.1111/j.1749-6632.2001.tb05792.x

Yu, D., & Fang, J. hui. (2024). Using artificial intelligence methods to study the effectiveness of exercise in patients with ADHD. Frontiers in Neuroscience, 18. https://doi.org/10.3389/fnins.2024.1380886

Zhao, X., Cox, A., & Chen, X. (2025). The use of generative AI by students with disabilities in higher education. Internet and Higher Education, 66. https://doi.org/10.1016/j.iheduc.2025.101014

Downloads

Published

2026-01-01

Issue

Section

Articles

How to Cite

Artificial Intelligence for Supporting College Students with Attention-Deficit/Hyperactivity Disorder: Cognitive, Emotional, and Ethical Perspectives  . (2026). International Journal on Social and Education Sciences, 8(1), 1-17. https://doi.org/10.46328/ijonses.5915