Title Pending 7361

This is an accepted article with a DOI pre-assigned that is not yet published.Emerging literature on faculty and student uses of generative AI (GenAI) tools shows that institutional factors like levels of adoption, demographics of students and faculty, institutional type, and institutional culture around GenAI can significantly impact perceptions and behaviors. This article argues that educational developers should collect local data to enhance their understanding of institutional behaviors and perceptions of GenAI in addition to reading national research. Aside from sharing data from a survey distributed to students (n=504) and faculty (n=281) across three campuses (two residential and one online) of a STEM-focused private university, this article explains how data informed CTL and professional training related to GenAI. Overall, this article models a replicable, locally tailored, and data-driven approach to GenAI professional development and adds to existing knowledge of student and faculty perceptions and use of GenAI tools.

Publication Details

Journal
To improve the academy
Published
2025-10-13
DOI
https://doi.org/10.3998/tia.7361
Primary Topic
Intellectual Property Law
Type
article
Field-Weighted Citation Impact
0.00
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Title Pending 7361

To improve the academy
Intellectual Property Law
article

Title Pending 7361

article en

Abstract

This is an accepted article with a DOI pre-assigned that is not yet published.Emerging literature on faculty and student uses of generative AI (GenAI) tools shows that institutional factors like levels of adoption, demographics of students and faculty, institutional type, and institutional culture around GenAI can significantly impact perceptions and behaviors. This article argues that educational developers should collect local data to enhance their understanding of institutional behaviors and perceptions of GenAI in addition to reading national research. Aside from sharing data from a survey distributed to students (n=504) and faculty (n=281) across three campuses (two residential and one online) of a STEM-focused private university, this article explains how data informed CTL and professional training related to GenAI. Overall, this article models a replicable, locally tailored, and data-driven approach to GenAI professional development and adds to existing knowledge of student and faculty perceptions and use of GenAI tools.

To improve the academy
Openalex Percentile: Top 56%
Intellectual Property Law
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