Analyzing the Significance of Learner Emotions Using Data Analytics

Abstract

Research on emotional intelligence (EI) in the learning process enhances the learner progress to attain the aspirations that have been set. The proposed work helps to recognize the learners' emotional behavior owing to the hectic situation due to COVID-19. Concentrating on the motivational and psychometric characteristics of the learners, this study scrutinized the involvement of EI in learner's learning. For this, three learning environments (LEs) are defined that adopt different methodologies of learning to analyze the increased performance of different types of learners. The face emotions of several learners were captured, recognized, and grouped using naïve bayes algorithm. The learners with negative emotions are identified from the algorithm, and the inputs are assessed with cross-tabulation techniques like chi-square and ANOVA. The results confirm that the learning environment along with the teaching methodologies and emotional happenings in and around decide the performance of the learner.