Understanding the Generative AI Divide: Faculty and Student Perspectives in Higher Education.
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| Title: | Understanding the Generative AI Divide: Faculty and Student Perspectives in Higher Education. |
|---|---|
| Authors: | DeStefano, Christine Depies1, Hackney, Joshua1, Moskal, Patsy D.1 |
| Source: | Online Learning. Jun2026, Vol. 30 Issue 2, p31-48. 18p. |
| Subject Terms: | *Generative artificial intelligence, *Training needs, *Student attitudes, *College teacher attitudes, *Education ethics, *Education policy, *Higher education, Innovation adoption |
| Geographic Terms: | United States |
| Abstract: | As generative artificial intelligence (GenAI) tools rapidly transform educational landscapes, higher education institutions face the critical challenge of developing effective policies and guidelines for their integration. However, little empirical research has examined actual GenAI usage patterns, perceptions, knowledge assessments, and training needs among faculty and students in U.S. universities. This study presents findings from a comprehensive survey of 3,164 students and 166 faculty members at a large R1 university in the southeastern United States. Results indicate that while 88% of students are familiar with GenAI concepts, only about a quarter currently use these tools for academic work, and 76% have received no formal classroom instruction on their use. Faculty demonstrate comparable familiarity (mean 4.5/5.0) but report substantial support needs, with 65% requesting assistance in creating AI-resistant assessments and 63% seeking guidance on effective GenAI integration in teaching. Before universities can implement effective GenAI guidelines and policies, they must first understand the current landscape of usage, perceptions, and training needs among their academic communities. [ABSTRACT FROM AUTHOR] |
| Copyright of Online Learning is the property of Online Learning Consortium and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 194761184 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Understanding the Generative AI Divide: Faculty and Student Perspectives in Higher Education. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22DeStefano%2C+Christine+Depies%22">DeStefano, Christine Depies</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Hackney%2C+Joshua%22">Hackney, Joshua</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Moskal%2C+Patsy+D%2E%22">Moskal, Patsy D.</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Online+Learning%22">Online Learning</searchLink>. Jun2026, Vol. 30 Issue 2, p31-48. 18p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Generative+artificial+intelligence%22">Generative artificial intelligence</searchLink><br />*<searchLink fieldCode="DE" term="%22Training+needs%22">Training needs</searchLink><br />*<searchLink fieldCode="DE" term="%22Student+attitudes%22">Student attitudes</searchLink><br />*<searchLink fieldCode="DE" term="%22College+teacher+attitudes%22">College teacher attitudes</searchLink><br />*<searchLink fieldCode="DE" term="%22Education+ethics%22">Education ethics</searchLink><br />*<searchLink fieldCode="DE" term="%22Education+policy%22">Education policy</searchLink><br />*<searchLink fieldCode="DE" term="%22Higher+education%22">Higher education</searchLink><br /><searchLink fieldCode="DE" term="%22Innovation+adoption%22">Innovation adoption</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22United+States%22">United States</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: As generative artificial intelligence (GenAI) tools rapidly transform educational landscapes, higher education institutions face the critical challenge of developing effective policies and guidelines for their integration. However, little empirical research has examined actual GenAI usage patterns, perceptions, knowledge assessments, and training needs among faculty and students in U.S. universities. This study presents findings from a comprehensive survey of 3,164 students and 166 faculty members at a large R1 university in the southeastern United States. Results indicate that while 88% of students are familiar with GenAI concepts, only about a quarter currently use these tools for academic work, and 76% have received no formal classroom instruction on their use. Faculty demonstrate comparable familiarity (mean 4.5/5.0) but report substantial support needs, with 65% requesting assistance in creating AI-resistant assessments and 63% seeking guidance on effective GenAI integration in teaching. Before universities can implement effective GenAI guidelines and policies, they must first understand the current landscape of usage, perceptions, and training needs among their academic communities. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Online Learning is the property of Online Learning Consortium and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=ehh&AN=194761184 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.24059/olj.v30i2.5911 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 18 StartPage: 31 Subjects: – SubjectFull: Generative artificial intelligence Type: general – SubjectFull: Training needs Type: general – SubjectFull: Student attitudes Type: general – SubjectFull: College teacher attitudes Type: general – SubjectFull: Education ethics Type: general – SubjectFull: Education policy Type: general – SubjectFull: Higher education Type: general – SubjectFull: Innovation adoption Type: general – SubjectFull: United States Type: general Titles: – TitleFull: Understanding the Generative AI Divide: Faculty and Student Perspectives in Higher Education. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: DeStefano, Christine Depies – PersonEntity: Name: NameFull: Hackney, Joshua – PersonEntity: Name: NameFull: Moskal, Patsy D. IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 24725749 Numbering: – Type: volume Value: 30 – Type: issue Value: 2 Titles: – TitleFull: Online Learning Type: main |
| ResultId | 1 |
