Understanding the adoption of educational AI tools in Sub-Saharan African higher education: a theory of planned behaviour-based analysis

Based on the Theory of Planned Behaviour (TPB), this study examines the interplay between perceptions of educational artificial intelligence (EdAI) tools—specifically their perceived benefits, hedonic motivation, weaknesses, and risks—interact with TPB constructs (attitude, subjective norms, and perceived behavioural control) in shaping adoption intentions. Using a quantitative design, data were collected through an online survey of 344 students from higher education institutions (HEIs) in Sub-Saharan Africa (SSA). Partial Least Squares Structural Equation Modelling (PLS-SEM) was employed to test hypothesized relationships.Findings show that attitude (β = 0.324, p < 0.000) and perceived behavioural control (β = 0.311, p < 0.000) significantly predict behavioural intention to adopt EdAI tools, while subjective norms have no significant effect (β = 0.100, p < 0.143). Perceptions of benefits, weaknesses, and risks influenced TPB constructs, whereas hedonic motivation produced mixed effects, suggesting context-dependent impacts.This study contributes by validating the TPB framework for EdAI adoption in SSA and highlighting key drivers and barriers. It offers practical implications for policymakers, institutional leaders, and EdTech developers in formulating strategies to optimize benefits and mitigate risks. As one of the first empirical PLS-SEM applications in this context, it advances understanding of EdAI adoption in resource-constrained settings.