Addressing educational overload with generative AI through dual coding and cognitive load theories
To ensure success, institutions must provide faculty and learners training, with consistent access, and evaluate outcomes. Pilot programs with iterative feedback can guide thoughtful implementation. By aligning educational strategies with cognitive science principles, generative AI can play a transformative role in addressing educational overload and creating more effective, engaging learning environments.
Authors
- Neil Mehta (ORCID: https://orcid.org/0000-0001-8342-4252)
- Anoop Agrawal (ORCID: https://orcid.org/0000-0003-1359-0209)
- Sofia Valanci (ORCID: https://orcid.org/0000-0002-0593-5353)
- Heather MacNeill (ORCID: https://orcid.org/0000-0001-9842-3578)
- Jennifer Benjamin (ORCID: https://orcid.org/0000-0001-6085-5973)
- Ken Masters (ORCID: https://orcid.org/0000-0003-3425-5020)
Institutions
- Baylor College of Medicine (US)
- University of Toronto (CA)
- Cleveland Clinic Lerner College of Medicine (US)
- Sultan Qaboos University (OM)
- Toronto Metropolitan University (CA)
- Royal College of Physicians and Surgeons of Canada (CA)
Publication Details
- Journal
- Medical Teacher
- Published
- 2025-08-08
- DOI
- https://doi.org/10.1080/0142159x.2025.2543548
- Citations
- 7
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 4.58