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Accepting the emergence of data mining technology by students is crucial to the successful implementation of the technology in education institutions. Although previous studies have empirically show the result of acceptance or adoption of data mining technology in numerous fields, however, they are focused at organisational-level. Hence, there is a need to explain what are the determinants could influence the acceptance of data mining technology at individual-level since they are the most affected by the technology. Therefore, this study adapts selected constructs in the Technology Acceptance Model 3 (TAM3) to conceptualise the research problem, namely in terms of perceived usefulness, perceived ease of use, relevance for analysing, anxiety of educational data mining technology, self-efficacy and facilitating conditions. To examine the model, this study surveyed 158 students from four public Institutions of Higher Learning in Malaysia. Pearson product-moment correlation coefficient is utilised to analyses the relationship between the constructs. The findings have revealed that most of the constructs have a high level of correlation.

The Acceptance of Educational Data Mining Technology among Students in Public Institutions of Higher Learning in Malaysia