Pedagogical and Elearning Logs Analyses to Enhance Students' Performance

Abstract

This paper introduces a model to analyze and predict students' performance based on two dimensions; teaching style, and eLearning activities. Such data will be collected from educational settings within an academic institution. The analyzed data is used to reveal knowledge and useful patterns from which critical decisions could be made. The suggested model should be able to: • Classify modules according to their module nature • Analyze different kinds of students' interaction with eLearning • Classify teaching styles and pedagogical approaches and their effect on students' performance • Classify students and their final grades according to their background and characteristics. • Utilize different correlation analysis and feature selection techniques