Developing Clear Guidance for Student Use of Generative AI in Academic Programs

Authors

• Steve Baule, Winona State UniversityFollow

Abstract

As generative artificial intelligence becomes increasingly embedded in academic life, institutions need clear, consistent guidance for students and faculty. This paper describes how Winona State University’s College of Education developed complementary AI guidance documents through a collaborative, community-informed process. Following a college-wide symposium and student requests for clearer expectations, faculty leaders drafted documents and gathered feedback from faculty, current students, recent graduates, library faculty, and university committees. The resulting guidance emphasizes transparency, disclosure, privacy, verification of learning, and the distinction between AI as a tool and AI as a source requiring citation. Public dissemination of the documents helped promote consistency, shared responsibility, and stronger alignment between pedagogy and academic integrity. By outlining both the development process and the content priorities of these working guidance documents, this paper offers a practical model for other academic programs seeking to respond thoughtfully and ethically to generative AI in higher education.

Recommended Citation

Baule, Steve (2026) "Developing Clear Guidance for Student Use of Generative AI in Academic Programs," Essays in Education: Vol. 32: Iss. 1, Article 15.
Available at: https://openriver.winona.edu/eie/vol32/iss1/15

Primary Author Bio Sketch

Steve Baule is an associate professor of leadership education at Winona State University. He served as a PK-12 educator and administrator prior to moving into higher education. Baule focuses on the use of educational technology for both instruction and the administration of schools. He holds a PhD from Loyola University Chicago in educational leadership and supervision and an EdD from Northern Illinois University in instructional technology.