Identification of Student Groups for Smart Tutoring and Collaborative Learning Based on Online Activities Using Neural Networks

Abstract

As the current education scenario has transformed itself to online mode, all learning and assessment activities including quizzes, report submissions, problem solving, peer assessment are done online. Identification of students' characteristics in terms of their academic performance and attitude is the need of the hour for personal tutoring. Also, collaborative learning, which forms an integral part of learning, has group formation as an influential activity for the success of learning. This work proposes an intelligent solution to group learners based on their outcomes and participation in various online assessment activities. This chapter considers the online assessment results of the learners and uses Kohonen self-organizing map neural network (SOM) to group the learners. The proposed method is experimented with a student set in the course “Digital Systems” (n=84). MATLAB is used for implementing SOM and the results obtained from simulations confirm the efficacy of the proposed network with 93.33% performance metric.