Exploring GenAI’s Potential Contributions as a Partner in SoTL Research: The Practice Model

The rapid advancement of generative artificial intelligence (GenAI) presents both opportunities and challenges for the Scholarship of Teaching and Learning (SoTL). This paper focuses on how SoTL scholars can thoughtfully integrate GenAI into their research processes while maintaining ethical integrity and preserving the essential human elements of scholarly inquiry. We critically examine GenAI’s capabilities, such as its potential to assist in brainstorming, to structure research ideas and protocols, and to expand methodological toolkits. However, we also emphasize its limitations, particularly regarding data reliability, inherent biases, and ethical concerns, such as transparency and student privacy. Through reflexive engagement with AI tools, we demonstrate how scholars can use GenAI as an intellectual partner rather than a substitute for critical thinking. We summarize our PRACTICE recommendations for use of GenAI in SoTL: Promote reflexivity; Read the literature; Act transparently; Conduct ethical research; Think critically; Invest in continuous learning; Check and validate outputs; Experiment and share. Ultimately, we argue that SoTL scholars must develop new competencies in order to navigate AI-enhanced research. While GenAI holds promise for advancing scholarly inquiry, its ethical use requires careful consideration and ongoing dialogue. By maintaining a balance between leveraging AI’s capabilities and upholding scholarly integrity, researchers can uphold SoTL practices that serve the field’s fundamental purposes: understanding, informing, and evolving teaching and learning for the benefit of students.

Authors

Institutions

Publication Details

Journal
Teaching & Learning Inquiry The ISSOTL Journal
Published
2026-02-25
DOI
https://doi.org/10.20343/teachlearninqu.14.7
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring GenAI’s Potential Contributions as a Partner in SoTL Research: The Practice Model

Lauren Hays, Brett M. McCollum, Janice Miller-Young
Teaching & Learning Inquiry The ISSOTL Journal
Artificial Intelligence in Healthcare and Education
article

Exploring GenAI’s Potential Contributions as a Partner in SoTL Research: The Practice Model

Lauren Hays, Brett M. McCollum, Janice Miller-Young
article en

Abstract

The rapid advancement of generative artificial intelligence (GenAI) presents both opportunities and challenges for the Scholarship of Teaching and Learning (SoTL). This paper focuses on how SoTL scholars can thoughtfully integrate GenAI into their research processes while maintaining ethical integrity and preserving the essential human elements of scholarly inquiry. We critically examine GenAI’s capabilities, such as its potential to assist in brainstorming, to structure research ideas and protocols, and to expand methodological toolkits. However, we also emphasize its limitations, particularly regarding data reliability, inherent biases, and ethical concerns, such as transparency and student privacy. Through reflexive engagement with AI tools, we demonstrate how scholars can use GenAI as an intellectual partner rather than a substitute for critical thinking. We summarize our PRACTICE recommendations for use of GenAI in SoTL: Promote reflexivity; Read the literature; Act transparently; Conduct ethical research; Think critically; Invest in continuous learning; Check and validate outputs; Experiment and share. Ultimately, we argue that SoTL scholars must develop new competencies in order to navigate AI-enhanced research. While GenAI holds promise for advancing scholarly inquiry, its ethical use requires careful consideration and ongoing dialogue. By maintaining a balance between leveraging AI’s capabilities and upholding scholarly integrity, researchers can uphold SoTL practices that serve the field’s fundamental purposes: understanding, informing, and evolving teaching and learning for the benefit of students.

Teaching & Learning Inquiry The ISSOTL JournalVol. 14
University of Central Florida (US), University of Central Missouri (US), Mount Royal University (CA)
Quality Education
Openalex Percentile: Top 45%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.