aceUnderstanding the Generative AI Divide: Faculty and Student Perspectives in Higher Education
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…
Students and faculty lack formal instruction and support for using generative AI in academic work, with most students receiving no classroom training.
Evidence
- Peer-reviewedEducation Sciences2025-05-16
- Peer-reviewedOnline Learning2026-06-01
- Peer-reviewedInternational Journal of Educational Technology in Higher Education2023-11-09
- Peer-reviewedComputers and Education: Artificial Intelligence2023-12-23
- Peer-reviewedBehavioral Sciences2025-05-20
How should this claim be treated?
Truvace Impact Record TRV-2026-0158, v5: “Understanding the Generative AI Divide: Faculty and Student Perspectives in Higher Education.” Truvace, 2026-09-26. /record/TRV-2026-0158 (accessed at citation time). sha256 030c80d679530d4f…
Calibration history
Every change to this record since certification, in the open.
Source set updated
Source set updated
Source set updated
Source set updated
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-0158 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.