Associative Rule Mining in Student-centric Assessment and Evaluation

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.