The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Generative Artificial Intelligence in Higher Education: A Mixed-Methods Study on Faculty Usage and Perceived Impacts
Abstract
This study investigates the diverse practices and impacts of generative artificial intelligence (AI) in higher education, focusing on faculty usage of AI tools. Employing a rigorous mixed-methods approach, the research combines a structured quantitative questionnaire exploring multiple dimensions of AI integration including pedagogical, scientific, institutional, and ethical uses with a qualitative experimental phase where faculty engage with standardized AI prompts to generate and analyze AI-produced content. The study aims to map declared usage patterns, evaluate perceived effects on teaching effectiveness and workload, and analyze disciplinary and seniority-based variations in adoption. Results reveal higher engagement and satisfaction among early-career faculty and those in engineering disciplines, alongside stronger ethical awareness, while more experienced faculty and those in literature fields report lower adoption. Quantitative analyses include descriptive statistics, ANOVA, factor analysis, and regression modeling, while qualitative data undergo thematic coding and natural language processing to identify recurrent usage themes and assess response quality. This research contributes to an interdisciplinary framework combining educational sciences, technological and pedagogical analysis, offering actionable insights for policy development and responsible, equitable AI integration in academia.
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Citations
Cites
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
User Acceptance of Information Technology: Toward A Unified View1
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003) · MIS Quarterly · doi:10.2307/30036540 · Cited by 45,035
Examining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence
Cooper, G. (2023) · Journal of Science Education and Technology · doi:10.1007/s10956-023-10039-y · Cited by 1,263 · cited 2×
“Similar to studies by [ 8 ] ; [ 9 ] and [1 0 ], our results show that university faculty particularly those in technical disciplines leverage AI to enhance course preparation, reduce time-consuming tasks, and improve research productivity.”
Generative AI and the Automating of Academia
Watermeyer, R., Phipps, L., Lanclos, D., & Knight, C. (2023) · Postdigital Science and Education · doi:10.1007/s42438-023-00440-6 · Cited by 200
ChatGPT—A Challenging Tool for the University Professors in Their Teaching Practice
Kiryakova, G., & Angelova, N. (2023) · Education Sciences · doi:10.3390/educsci13101056 · Cited by 171
Research works printed but not linked: 5
- Caballero-Morales, 2024, Generative and quantitative processions, general, and future directions through the systematic literature review, Educ. Sci., 14, 11
- Chiu, 2024, Scoping review of generative AI in higher education: Applications and challenges, Educ. Sci.
- Chan, 2024, Student perceptions of generative AI in Hong Kong: A survey study, J. Educ. Technol.
- Tlili, 2023, Global perspectives on generative AI in education: A survey of 1217 stakeholders, Int. J. Educ. Technol. High. Educ.
- Maslej, 2025, The AI Index 2025 annual report, 2025
Cited by
Sorted by citations
Ncube, P. D. N., Dzvapatsva, G. P., Matobobo, C., & Ranga, M. M. (2026) · AI and Ethics · doi:10.1007/s43681-025-00871-w · Cited by 31
“Furthermore, some scholars have called for the expansion of AI literacy training as a means of addressing the challenges posed by inappropriate or uninformed AI use [ 73, 75, 86, 95, 101].”
Metadata
- Authors
- El Hassouni, M., Fouad, F., & El Bassim, H.
- Affiliations
- SUPMTI,MFMDI Laboratory,Rabat,Morocco
- Venue
- 2025 International Conference on Smart Learning Courses (SCME)
- Publisher
- IEEE
- Published
- 2025-07-09
- Pages
- 215-222
- OpenAlex
- W7084142841
- Cited by
- 1
- References
- 5
- Citations by year
- 2025: 1
- FWCI
- 1.20
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Smart Learning Courses (SCME) (publishedVersion)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- generative AI, higher education, AI in teaching, teaching effectiveness, faculty workload, AI ethics awareness, new faculty, disciplinary differences, artificial intelligence adoption, responsible AI adoption
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