In todays world, the fast-paced changes in technology and upswing volume of organizational data in almost all domains including academe are very remarkable. This coupled with the aspiration to gain competitive advantage necessitate the utilization of data mining. This paper applies the processes in the Knowledge Discovery in Databases by Fayyad and presents in methodological way the steps performed towards finding the associations between courses failed by engineering students. It started with the preparation of data moving towards proper transformation of it for data mining and concluding with data interpretation and evaluation. Using association rule mining through Apriori algorithm, the rules were extracted from the database. The statistical significance and the strength of the rule were analyzed using 3 measures of usefulness: lift, support and confidence. All the rules generated have positive co-relation, that is, the relationships of the consequent of the rule with the antecedent are not due to chance. The over-all output of the study is expected to offer viable results that may be used by administrator, academic advisor and curriculum planners in devising worth-while strategies such as improvement of teaching methodology, re-structure of curriculum, modification of course pre-requisites or development of supplemental activities to students.
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