Performance Evaluation of an IoT-Based E-Learning Testbed Using Mean Shift Clustering Approach Considering Electroencephalogram Data

Due to the opportunities provided by the Internet, people are taking advantage of e-learning courses and enormous research efforts have been dedicated to the development of e-learning systems. So far, many e-learning systems are proposed and used practically. However, in these systems the e-learning completion rate is low. One of the reasons is the low study desire and motivation. In this work, we design and implement an IoT-Based E-Learning testbed using Raspberry Pi mounted on Raspbian. We analyze the performance of mean shift clustering algorithm considering electroencephalogram data. For evaluation we considered attention value. The evaluation results show that by the mean shift clustering algorithm the learner concentration is increased.