University Teachers’ Views on the Adoption and Integration of Generative AI Tools for Student Assessment in Higher Education
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This study examines the factors that may impact the adoption of generative artificial intelligence (Gen AI) tools for students’ assessment in tertiary education from the perspective of early-adopter instructors in the Middle East. It utilized a self-administered online survey and the Unified Theory of Acceptance and Use of Technology (UTAUT) model to collect data from 358 faculty members from different countries in the Middle East. The Smart PLS software 4 was used to analyze the data. The findings of this study revealed that educators developed new strategies to integrate Gen AI into assessment and used a systematic approach to develop assignments. Moreover, the study demonstrated the importance of developing institutional policies for the integration of Gen AI in education, as a driver factor influencing the use of Gen AI in assessments. Additionally, the research identified significant factors, namely performance expectancy, effort expectancy, social influences, and hedonic motivation, shaping educators’ behavioral intentions and actual use of Gen AI tools to assess students’ performance. The findings reveal both the potential advantages of Gen AI, namely enhanced student engagement and reduced instructor workloads, and challenges, including concerns over academic integrity and the possible negative impact on students’ writing and thinking skills. This study emphasizes the significance of targeted professional development and ethical criteria for the proper integration of…
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Irresponsible use of AI tools in assessment undermines academic integrity and threatens the reputation of educational institutions.
“Irresponsible use of AI tools in assessment undermines academic integrity and threatens the reputation of educa -tional institutions [ 58 ].”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [58]
Promoting critical engagement with AI-generated content fosters an educational environment where AI functions as a learning partner rather than a replacement for human cognition.
“This approach fosters an educational environment where AI functions as a learning partner rather than a replacement for human cognition [ 58, 100 ].”
From Redefining student assessment in AI-infused learning environments: a systematic review of challenges and strategies for academic integrity (2026) · cites this paper as [58]
Teachers' interpretations position them as active agents in digital transformation rather than passive technology users.
“These interpretations position teachers as active agents in digital transformation rather than passive technology users, offering an important contribution to a literature largely focused on higher education (Ayyoub et al., 2025;Khlaif et al., 2024).”
From Teachers' Experiences with AI in K–12 Education: Opportunities and Challenges (2026) · cites this paper as Khlaif et al., 2024
This study offers an important contribution to a literature largely focused on higher education.
“These interpretations position teachers as active agents in digital transformation rather than passive technology users, offering an important contribution to a literature largely focused on higher education (Ayyoub et al., 2025;Khlaif et al., 2024).”
From Teachers' Experiences with AI in K–12 Education: Opportunities and Challenges (2026) · cites this paper as Khlaif et al., 2024
Teachers' perceived shift in professional identity is consistent with international literature framing AI as a catalyst for rethinking teacher agency and professional roles.
“This interpretation is consistent with international literature that frames AI as a catalyst for rethinking teacher agency and professional roles (Khlaif et al., 2024).”
From Teachers' Experiences with AI in K–12 Education: Opportunities and Challenges (2026) · cites this paper as Khlaif et al., 2024
By focusing on K-12 teachers in Türkiye, this study addresses a notable gap in the literature, which has largely prioritized higher education contexts and technology-centered analyses.
“By focusing on K-12 teachers in Türkiye, this study addresses a notable gap in the literature, which has largely prioritized higher education contexts and technologycentered analyses (Hamamra, Khlaif & Mayaleh, 2025;Khlaif et al., 2024).”
From Teachers' Experiences with AI in K–12 Education: Opportunities and Challenges (2026) · cites this paper as Khlaif et al., 2024
Performance expectations and effort expectations significantly influence students' willingness to integrate ChatGPT into their learning practices.
“performance expectations and effort expectations significantly influence students’ willingness to integrate ChatGPT into their learning practices (Khlaif et al., 2024).”
From Exploring the factors influencing college students’ learning satisfaction in generative AI-supported MOOCs learning environment: a learning experience framework perspective (2025) · cites this paper as Khlaif et al., 2024
Both positive and negative emotions significantly impact learning satisfaction.
“Both types of emotions significantly impact learning satisfaction (Jin et al., 2025; Khlaif et al., 2024; Kim, 2023).”
From Exploring the factors influencing college students’ learning satisfaction in generative AI-supported MOOCs learning environment: a learning experience framework perspective (2025) · cites this paper as Khlaif et al., 2024
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References 65 · Cited by 177
- Authors
- Khlaif, Z. N., Ayyoub, A., Hamamra, B., Bensalem, E., Mitwally, M. A. A., Ayyoub, A., Hattab, M. K., & Shadid, F.
- Affiliations
- An-Najah National University (PS)
- Faculty of Humanities and Educational Sciences, Psychology and Counseling Department, An Najah National University, Nablus P.O. Box 7, Palestine
- Northern Border University (SA)
- University of South Africa (ZA)
- Bethlehem University (PS)
- Corresponding author
- Khlaif, Zuheir N.
- ORCID
- Venue
- Education Sciences
- Publisher
- MDPI AG
- Published
- 2024-10-06
- Volume
- 14
- Issue
- 10
- Pages
- 1090
- ISSN
- 2227-7102 (ISSN-L)
- OpenAlex
- W4403192861
- Cited by
- 177
- References
- 65
- Citations by year
- 2026: 96 · 2025: 79 · 2024: 2
- FWCI
- 66.55
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Education Sciences (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- generative AI, student assessment, teacher perceptions, technology adoption, UTAUT, institutional policy, academic integrity, instructor workload, student engagement, professional development, ethical use of AI, higher education in the Middle East
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