Certain investigations on rough set based mechanisms for elucidating learning styles in e learning frameworks

Abstract

In an e-learning environment, the determination of learning newlinestyles of the e-learning audience has raised the potential scope of interest as newlineits exact estimation prompts a sensational improvement in the contents of the newlinelearning framework and student performance. It requires a deep investigation newlineover the learning habits of the learner. Grouping e-learners together provides newlinea more quantifiable way to analyze the learnerand#8223;s feedback and log files to newlinediscriminate them based on their learning style. This is accomplished with newlinethe help of clustering algorithms in data mining, which aids in determining newlinetheir learning styles well. The target clusters are analyzed by generating newlineuseful patterns or rules using the rule induction algorithms. newlineLearning styles refer to the differences in an individualand#8223;s ability newlineto assimilate things in education. It is the method used by the learners to newlineaccumulate and apply knowledge in a specific manner. The research work newlinestarted with exploring various models on learning styles. It utilizes the VAK newline(Visual Auditory Kinesthetic) model that uses the common practices the newlineindividuals utilize for learning. According to VAK model, learners prefer to newlinelearn in any one of the three ways namely: visual, auditory or kinesthetic. newlineVisual learner assimilates information through diagrams, videos, pictures and newlinecharts, an auditory learner has a preference over listening to voices in a newlinelecture, hears things or uses group discussions and finally kinesthetic learner newlinechooses physical experience such as moving, solving and doing things, newlinepreferring a hands-on approach for learning. newline newline