Research Article
Adoption of Generative AI and Learning Analytics for Personalized Learning in Nigerian Higher Education: Effects on Student Engagement, Learning Outcomes, and Academic Integrity
Ayonote Williams Elenode*
Issue:
Volume 11, Issue 1, February 2026
Pages:
1-5
Received:
28 October 2025
Accepted:
20 December 2025
Published:
16 January 2026
DOI:
10.11648/j.eas.20261101.11
Downloads:
Views:
Abstract: This study examines the integration of generative artificial intelligence (GenAI) and learning analytics (LA) in fostering personalized learning within Nigerian higher education institutions. Specifically, it explores how these emerging technologies influence student engagement, academic performance, and perceptions of academic integrity in digitally mediated learning environments. A mixed-method research design was adopted, involving 420 undergraduate students and 60 academic staff drawn from three Nigerian universities. Quantitative data were collected through structured questionnaires assessing GenAI usage patterns, learning analytics engagement, levels of digital literacy, and integrity perceptions, while qualitative insights were obtained from semi-structured interviews with academic staff and information and communication technology (ICT) administrators. The findings reveal that 64% of respondents actively use GenAI tools such as ChatGPT and Gemini to support learning activities, while 58% regularly access learning analytics dashboards for performance monitoring and feedback. Regression analysis indicates that GenAI-assisted learning and engagement with learning analytics jointly predict improved academic performance (β = 0.36, p < 0.01) and higher levels of student engagement (β = 0.42, p < 0.001). However, the study also finds that unregulated use of GenAI tools is positively associated with increased concerns about plagiarism and academic misconduct (r = 0.31, p < 0.05). The study concludes that the pedagogically guided integration of GenAI and learning analytics can significantly enhance personalized learning experiences in Nigerian higher education. Nevertheless, this potential can only be realized through the development of robust governance frameworks that emphasize ethical use, digital literacy, academic integrity, and data privacy. The study therefore recommends targeted capacity-building for educators, the establishment of transparent institutional AI policies, and continuous evaluation of the pedagogical impact of GenAI technologies.
Abstract: This study examines the integration of generative artificial intelligence (GenAI) and learning analytics (LA) in fostering personalized learning within Nigerian higher education institutions. Specifically, it explores how these emerging technologies influence student engagement, academic performance, and perceptions of academic integrity in digital...
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