Student’s Performance Prediction Using Hybrid Optimization Algorithm-based Map Reduce Framework

Learning analytics (LA) is a growing research area, which aims at selecting, analyzing and reporting student data (in their interaction with the online learning environment), finding patterns in behaviour, displaying relevant information suggestive formats; end goal prediction of performance, optimization educational platform implementation personalized interventions. According to Society Analytics Research1, LA can be defined as "the measurement, collection, analysis about learners contexts, for purposes understanding optimizing environments it occurs". The topic highly interdisciplinary, including machine techniques, mining, statistical analysis, social network natural language processing, but also knowledge from sciences, pedagogy sociology; up-to-date overviews area are provided in. Various tasks supported by analytics, identified visualization data; providing feedback supporting instructors; recommendations students; predicting student's performance; modelling; detecting undesirable behaviours; grouping analysis; developing concept maps; constructing courseware; planning scheduling. Similarly, seven main objectives summarized in: monitoring intervention; tutoring mentoring; assessment feedback; adaptation; personalization recommendation; reflection.