Using AI to Support SoTL

• AI Can Support the Entire SoTL Process: Generative AI has the potential to contribute across every stage of a SoTL project—from refining research questions and identifying conceptual frameworks to synthesizing literature, organizing ideas, improving scholarly writing, and supporting dissemination. Rather than viewing AI as an automated researcher, SoTL scholars are encouraged to engage with it as a collaborative partner while maintaining ownership of methodological decisions and scholarly judgment. 

• • Miller-Young, J., Hays, L., and McCollum, B. (2026). Exploring GenAI’s Potential Contributions as a Partner in SoTL Research: The PRACTICE Model. Teaching & Learning Inquiry, Vol.14:1-19. https://doi.org/10.20343/teachlearninqu.14.7  

• AI Presents New Opportunities for Educational Scholarship: Generative AI is influencing not only how educational research is conducted, but also the kinds of questions SoTL scholars investigate. Understanding AI’s opportunities and limitations enables educators to explore emerging areas of scholarship while critically examining how AI is reshaping teaching, learning, assessment, and faculty practice. 

• • Wymer, K. C. (2025). Generative AI and the Future of the Scholarship of Teaching and Learning: What Do We Stand to Gain or Lose? International Journal for the Scholarship of Teaching & Learning: Vol. 19: No. 2, Article 2. https://doi.org/10.20429/ijsotl.2025.190202  

• AI Can Strengthen Health Professions Education Scholarship: For educators in the health sciences, AI can support scholarly productivity by assisting with educational research, academic writing, and dissemination while maintaining the principles of evidence-based practice, transparency, ethical decision making, and researcher oversight. Used responsibly, AI has the potential to enhance both the efficiency and quality of educational scholarship. 

• • Patino, G.A., Amiel, J.M., Brown, M., Lypson, M.L., and Chan T.M. (2024). The Promise and Perils of Artificial Intelligence in Health Professions Education Practice and Scholarship, Academic Medicine, Volume 99, Issue 5, 477-481. 
    https://doi.org/10.1097/ACM.0000000000005636 

1. Begin with Your Educational Question: Start with a meaningful question about teaching or learning before engaging AI. Use AI to refine research questions, explore theoretical perspectives, generate alternative approaches, or identify gaps in the literature. Your educational expertise—not the AI—should drive the direction of the project. 
2. Ground AI in Trusted Sources: AI-generated responses should always be grounded in credible evidence. Use peer-reviewed literature, educational frameworks, systematic reviews, and trusted databases to verify information before incorporating it into your scholarship. Consider AI tools that allow you to work directly with selected documents or curated literature rather than relying solely on a model’s general knowledge. 
3. Use AI Throughout the Research Process while Staying In-The-Loop :AI can support many aspects of SoTL, including: brainstorming research questions, developing conceptual frameworks, designing surveys or interview guides, summarizing and comparing literature, organizing qualitative or quantitative findings, improving clarity and organization of manuscripts, drafting conference proposals and presentation materials. In all these instances, treat AI as a scholarly collaborator rather than an autonomous researcher. Human expertise is essential for selecting research methods, interpreting results, evaluating evidence, drawing conclusions, and making decisions about educational practice. 
4. Evaluate AI Outputs Critically: AI systems may generate inaccurate information, fabricate references, oversimplify findings, or introduce bias into analyses. Review every AI-generated output carefully and verify citations before incorporating them into your work. 
5. Understand Journal and Publication Policies: Many scholarly journals now provide guidance regarding the acceptable use of generative AI in manuscript preparation, authorship, peer review, and disclosure. Before submitting scholarly work, review the policies of your target research journal and relevant professional organizations. 
6. Protect Confidential Information: Do not upload identifiable student work, assessment data, patient information, or sensitive institutional materials into public AI systems unless institutional policies explicitly permit their use. When appropriate, use institutionally approved AI platforms and de-identify research data before using AI tools. 

• Mills, J. et al. Re-thinking SoTL for the Age of GenAI: Diffracted, Entangled, and Human. Teaching & Learning Inquiry 13: 1–19.  

• Using AI For SoTL: Emerging Opportunities, Responsible Use and Evolving Guidelines. Webinar. Devin Scott, PhD and Federico Gomez-Uroz Horst. Teaching and Learning Center, UTHSC. 

• AI in 30: Copilot for Quantitative Analysis (Tom Laughner, PhD) and AI for Qualitative Research (Devin Scott, PhD). Teaching and Learning Center, UTHSC. 

• Responsible AI in Academic Research: A Competency Framework for Research Training. Zyphur, M. J. (2026). Instats Policy Series. 

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Check other TLC Artificial Intelligence Resources.