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The acceptance of Educational Data Mining (EDM) technology is on the rise due to, its ability to extract new knowledge from large amounts of students’ data. This knowledge is important for educational stakeholders, such as policy makers, educators, and students themselves to enhance efficiency and achievements. However, previous studies on EDM have focused more on technical aspects, such as evaluating methods and techniques, while ignoring the end-users’ acceptance of the technology. Realising its importance, this study has analysed the determinants that could influence the acceptance of EDM technology, particularly among undergraduate students since they are the most affected by the technology. For this reason, 11 hypotheses have been formulated based on determinants of technology readiness index (TRI) and technology acceptance model 3 (TAM3), which could render an in-depth …