Learner centric feedback-based learning analytics

Now a day, E-learning is a widely used way of learning. After the wide spread availability of Internet, e-learning became the first choice of a large group of learners as it provides the facility to learn anytime anywhere. The only thing that makes a difference in e -learning and traditional face- to- face learning is learner gets the proper feedback from teachers in traditional way of learning, but today’s e-learning systems also facilitates the feedback-based guidance to the learners. In this paper, we collected feedbacks of 120 undergraduate students of Department of Computer Science, Aligarh Muslim University, India and analyzed the role of learner centric feedback and proposed learner centric feedback based e-learning model to facilitate the overall e-learning objectives and improved performance of learner consequently to enhance learner’s cognitive abilities. Learner centric feedback-based e-Learning Model facilitates to achieve multidimensional improvement in learner. Learner centric feedback provided by different stakeholders makes this model special. A prediction system has been developed to predict low performance learner on the basis of analysis of feedback given by the learners on different video tutorials using various machine learning algorithms. Results and findings of our study conclude that Support Vector Machine classifier chives the accuracy of 91.30% that is the highest among other classifiers used in this study. This study specifies the importance and requirement of learner centric feedback in e-learning tutorials and the scope of personalized feedbacks. This model can be further improved for analyzing audio and video feedbacks.