Contextual data mining for higher educational institutions

Abstract

Context-awareness research has been carried out by many researchers. However, little has been done in building a context-aware data mining methodology which supports decision-making in HEIs. The usefulness of Knowledge discovery data mining process (KDDM process) in HEIs were investigated to discover hidden knowledge that is contextualized, resident in student datasets and use them in decision making. It was experimented and found that not any of the KDDM processes include a contextual factor mining stage that is essential to take out hidden knowledge from datasets described by contextual factors. Therefore a new process was introduced in KDDM process that uncovered contextual data to be used to support business goal and produced a dataset at the preparation stage which generated data mining model that was contextual leading to the unearthing of course taking patterns that are contextualized. This discovery has enabled forecasting of optimum CGPA and time-to-degree.