Alternative Title

Early Days of Normalizing Artificial Intelligence (AI) Use in a Doctoral Program

Contributor

University of Central Florida. Faculty Center for Teaching and Learning; University of Central Florida. Division of Digital Learning; Teaching and Learning with AI Conference (2025 : Orlando, Fla.)

Location

Sun & Surf I/II

Start Date

29-5-2025 10:45 AM

End Date

29-5-2025 11:10 AM

Publisher

University of Central Florida Libraries

Keywords:

AI integration; Doctoral education; Qualitative analysis; Transparency in AI; Higher education practices

Subjects

Artificial intelligence--Study and teaching (Higher); Artificial intelligence--Educational applications; Doctoral students; Graduate students--Research; Artificial intelligence--Social aspects

Description

In this presentation, we share the AI use journey of four Ph.D. students in a Hospitality Management doctoral program. While the course syllabus included an AI use statement requesting transparency and reporting of prompt engineering and percentage use of the generative AI, students' actual use was initially cautious. Qualitative data analysis of students' AI transparency statements and postcourse reflections will be shared to inform best practices for programs with emergent use of AI in higher education. Given the unique roles of doctoral students in academia - combining researcher, future mentor, and future teacher- we posit that AI should not serve a transactional purpose, but instead play a transformative role in knowledge creation.

Language

eng

Type

Presentation

Format

application/pdf

Rights Statement

All Rights Reserved

Audience

Faculty; Students

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May 29th, 10:45 AM May 29th, 11:10 AM

Early Days of Normalizing AI Use in a Doctoral Program

Sun & Surf I/II

In this presentation, we share the AI use journey of four Ph.D. students in a Hospitality Management doctoral program. While the course syllabus included an AI use statement requesting transparency and reporting of prompt engineering and percentage use of the generative AI, students' actual use was initially cautious. Qualitative data analysis of students' AI transparency statements and postcourse reflections will be shared to inform best practices for programs with emergent use of AI in higher education. Given the unique roles of doctoral students in academia - combining researcher, future mentor, and future teacher- we posit that AI should not serve a transactional purpose, but instead play a transformative role in knowledge creation.