Abstract:
Abstract
Although the educational data repository of Ethiopian High schools is very large,
successfully implementing Data Mining (DM) still relatively new, which intended for
identification, extraction of new and potentially valuable knowledge which helps to
reduce student failure rates in high school subjects.
This study apply descriptive DM and hybrid DM process model used to identifying, valid
cluster analysis of students based on their academic performance in each subject they took.
Association rule mining is also used discover interesting patterns and relationships
between attributes/subjects and student gender which directs the decision making in
education sector. Firstly, cluster analysis was performed to group the student into clusters
based on its similarities. A total of four cluster analysis experiment was conducted on 5181
student academic record and 12 attribute used to build a model. The cluster result from
these four experimentations are interpreted and evaluated. Among the four models, the
one with K = 3, Seed value = 100 and Euclidean distance function has shown better
segmentation of the students. This result of the model was selected according to
objective measure SSE, number of iteration and subjective measure of expert judgments
because the resulting student cluster give more insight to tackle quality of education
problem. Secondly, association rules mining were implemented to different dataset to
discover strong, interpretable rules that shows patterns of students result in each subjects.
The PredictiveApriori algorithm generate rules with high predictive accuracy using
RapidMiner Studio (RMS) and Apriori algorithm of WEKA results simple, interpretable and
actionable rules shows strong correlation of antecedents and consequents subjects which
achieves above the minimum support, confidence metrics and lift constraints.
This new clusters pattern of students and association rules helps to give attention to
similar student clusters, plan in advance related subject tutor and also improvising the
subject score in each particular subject, in general improve quality of education and help
policy makers as inputs.
