Hybrid CHAID a key for MUSTAS Framework in Educational Data Mining
Currently there is an increased interest in Educational Data Mining due to the compelling need for quality in higher education and the need to know student behavioural pattern to cater individual needs. The performance prediction of student kind model is quite familiar and mostly it is associated with academic performance. Our proposed framework Multi Dimensional Student Assessment (MUSTAS) has unique feature to measure the student’s performance through multidimensional attributes. Each dimension and its associated factors are carefully designed to predict the student’s behaviour. We propose the Hybrid CHAID algorithm , a combination of CHAID and Latent Class Modeling (LCM) as the best matched technique for our MUSTAS framework in educational data mining.
Keywords: Data Mining, Educational Data Mining, CHAID Prediction Model, Latent Class Model
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