Associative Rule Mining in Student-centric Assessment and Evaluation

Abstract

Education is imparted by the established academic institutions .Nowadays the big challenge of school students are getting through the competitive examinations and it also shows the quality of our education. By the assessment and evaluation of the student‘s ability the quality of the education inculcated can be improved. This paper deals with assessments that are student centric to enhance their ability that paves the way for their career development. Data mining techniques such as association rule mining have been applied to the data to analyse and find the factors that are really needed to assess the student capability. By applying associative rule mining the association between the assessment factors that are more significantly affecting the performance of a student has been identified and it provides a decision support for teaching and the assessment curriculum.