Artificial intelligence use and its influence on academic learning behaviour among undergraduate students in Nigeria

Artificial Intelligence (AI) is evolving rapidly across all aspects of life, particularly in educational institutions, where it is observed to impact the learning behaviours of students. Despite emerging literature on AI awareness, academic applications and adoption among undergraduate students, limited qualitative evidence exists on how Nigerian undergraduates experience AI use and perceive its influence on their academic learning behaviours. This study therefore examined AI use and its influence on academic learning behaviour among undergraduate students in Nigeria. The study is anchored on the Technology Acceptance Model (TAM) and the Self-Regulated Learning (SRL) Theory, which served as the theoretical lenses in explaining students’ AI use. The TAM argues that students perceive AI tools as vital instruments in enhancing and supporting learning activities, improving access to information and simplifying intricate academic concepts. The SRL positions students as active agents who structure, control, monitor and assess their learning, implying that students can intentionally use AI to regulate their learning, clarify difficult concepts and obtain resources tailored to their specific needs. The study adopted an exploratory research design, using in-depth interviews to collect data from 12 undergraduate students across the six geopolitical zones in Nigeria. Data from the study were analysed using thematic analysis, with the aid of NVivo 12 software. Findings from the study showed students’ awareness of AI through social media, classmates and lecturers. Findings also revealed that the use of AI tools influences academic learning behaviours by providing quicker access to academic materials, helping students complete assignments faster with little effort, facilitating independent study and research, and enhancing understanding through tailored explanations. Further findings highlighted difficulties students encounter in using AI tools for academic activities: misleading AI-generated information, lack of adequate AI literacy and usage skills, and overdependence. Drawing on the contextual experiences of a purposively selected qualitative sample, the findings provide exploratory insights rather than largely generalizable conclusions about AI use among Nigerian undergraduate students. Also, by exploring students’ accounts of AI awareness, use, learning-related experiences and challenges across Nigeria’s six geopolitical zones, the study extends existing AI-in-higher-education scholarship beyond mere adoption of technology to illuminate the contextual and behavioural dimensions of AI-mediated learning.