Examining Faculty and Student Perceptions of Generative AI in University Courses

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dc.contributor.authorKim, Junghwanen
dc.contributor.authorKlopfer, Michelleen
dc.contributor.authorGrohs, Jacob R.en
dc.contributor.authorEldardiry, Hodaen
dc.contributor.authorWeichert, Jamesen
dc.contributor.authorCox, Larry A., IIen
dc.contributor.authorPike, Daleen
dc.date.accessioned2025-01-24T17:38:39Zen
dc.date.available2025-01-24T17:38:39Zen
dc.date.issued2025-01-24en
dc.description.abstractAs generative artificial intelligence (GenAI) tools such as ChatGPT become more capable and accessible, their use in educational settings is likely to grow. However, the academic community lacks a comprehensive understanding of the perceptions and attitudes of students and instructors toward these new tools. In the Fall 2023 semester, we surveyed 982 students and 76 faculty at a large public university in the United States, focusing on topics such as perceived ease of use, ethical concerns, the impact of GenAI on learning, and differences in responses by role, gender, and discipline. We found that students and faculty did not differ significantly in their attitudes toward GenAI in higher education, except regarding ease of use, hedonic motivation, habit, and interest in exploring new technologies. Students and instructors also used GenAI for coursework or teaching at similar rates, although regular use of these tools was still low across both groups. Among students, we found significant differences in attitudes between males in STEM majors and females in non-STEM majors. These findings underscore the importance of considering demographic and disciplinary diversity when developing policies and practices for integrating GenAI in educational contexts, as GenAI may influence learning outcomes differently across various groups of students. This study contributes to the broader understanding of how GenAI can be leveraged in higher education while highlighting potential areas of inequality that need to be addressed as these tools become more widely used.en
dc.description.versionPublished versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1007/s10755-024-09774-wen
dc.identifier.eissn1573-1758en
dc.identifier.issn0742-5627en
dc.identifier.orcidKim, Junghwan [0000-0002-7275-769X]en
dc.identifier.orcidGrohs, Jacob [0000-0002-6060-6448]en
dc.identifier.orcidEldardiry, Hoda [0000-0002-9712-6667]en
dc.identifier.urihttps://hdl.handle.net/10919/124367en
dc.language.isoenen
dc.publisherSpringeren
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectChatGPTen
dc.subjectGenerative AIen
dc.subjectHigher Educationen
dc.subjectPerceptionen
dc.subjectTechnology Acceptanceen
dc.titleExamining Faculty and Student Perceptions of Generative AI in University Coursesen
dc.title.serialInnovative Higher Educationen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherArticleen
pubs.organisational-groupVirginia Techen
pubs.organisational-groupVirginia Tech/Natural Resources & Environmenten
pubs.organisational-groupVirginia Tech/Natural Resources & Environment/Geographyen
pubs.organisational-groupVirginia Tech/Engineeringen
pubs.organisational-groupVirginia Tech/Engineering/Computer Scienceen
pubs.organisational-groupVirginia Tech/Engineering/Engineering Educationen
pubs.organisational-groupVirginia Tech/Natural Resources & Environment/Geography/Geography T&R facultyen
pubs.organisational-groupVirginia Tech/All T&R Facultyen
pubs.organisational-groupVirginia Tech/Engineering/COE T&R Facultyen
pubs.organisational-groupVirginia Tech/Natural Resources & Environment/CNRE T&R Facultyen

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