A MODEL TO RECOMMEND BEST CLASSIFIER AMONG DIFFERENT MACHINE LEARNING ALGORITHMS FOR AN INTERACTIVE LEARNING ENVIRONMENT

With the increased integration of technology in education process and the evolution of social media portals usage, education development professionals are challenged to personalize and create an interactive learning environment that fulfills learners’ needs to catch their minds through different pedagogical and innovative approaches.

An understanding of how the individual learning style and cognitive traits interacts with the instructional medium presented is needed.
This study explore a model functioning through multi layers to make a comparative analysis among different machine learning algorithms in order to know which one is the most fit for the used dataset which encompasses two data sources the first acquired from the Learning Management System “LMS” while the second was the Social Media portals associated with that LMS.

Also this study examined the VARK (visual, auditory, read/write, and kinesthetic) learning style inventory using the variable-centered, person-centered and social approaches.