Acceptance and use of artificial intelligence for self-directed research learning among postgraduate students in Nigerian public universities

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Source: OpenAlex

Last checked: 2026-03-29 23:59:32

Abstract

Research competence is a cornerstone of postgraduate education, yet many Nigerian students continue to struggle with essential processes such as literature review, methodological design, and data analysis. While artificial intelligence (AI) holds considerable promise in supporting self-directed research learning (SDRL), its adoption and practical use among postgraduate students in Nigeria remain underexplored. This study addresses that gap by investigating both the acceptance and use of AI tools for SDRL among postgraduate students in Nigerian public universities. Adopting a predictive correlational design, data were collected from 456 students across two institutions using stratified random sampling. Two validated instruments (10-item scales; $$ = 0.85 and $$ = 0.87) were administered both physically and digitally to assess students' acceptance of AI and their actual use of AI for SDRL. Descriptive statistics and linear regression were used to analyse patterns and predict usage based on acceptance. Findings revealed a high level of AI acceptance (M = 3.30/4.00), yet a considerably lower level of actual AI usage (M = 2.26/4.00) for self-directed research learning. A weak but statistically significant relationship was observed between acceptance and use of AI for self-directed research learning (R2 = 0.01, $$ = 0.11, p < 0.05), suggesting that acceptance alone does not translate into meaningful engagement. These results highlight a pressing need to move beyond enthusiasm and address practical barriers to AI usage for self-directed research learning, such as limited training opportunities, inadequate mentorship, and infrastructural constraints. Targeted institutional interventions aimed at building AI literacy and integrating AI tools into research support systems could bridge this gap, thereby strengthening postgraduate research capacity and improving learning outcomes in Nigerian higher education.

Keywords

Artificial intelligence,Graduate education,Nigeria,Self-directed learning,Technology acceptance

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