Association rules mining in students’ grades in degree program related courses

A variety of analysis tools exist for information extraction and knowledge mining from the students’ result database. This paper presents data mining approach applied to find association rules and discover interesting patterns from the students’ performance in programming, English, and programming courses of engineering degree program. The patterns’ analysis assures to offer some supportive and constructive direction to educational decision makers and administrators in higher education institutions for the enhancement and modification of teaching methodology, updating of curriculum, and modifying prerequisites of different courses.