Emotion Detection with AI: Development of Learning Media for Evaluation of Cognitive Load of Prospective Teacher in Genetics Lectures

Abstract

This research aims to develop learning media by integrating artificial intelligence (AI) that is able to detect the emotions of prospective teacher during genetics lectures. Using AI technology, this system can evaluate the cognitive load of students in real-time through facial expression analysis. The method used involves collecting data from lecture sessions, which are then analyzed using machine learning algorithms to identify cognitive load levels. The results of the study show that this learning media is able to identify students' emotions. This learning media is equipped with accurate emotion detection features, interactive learning materials, and an informative dashboard to monitor student learning progress. The implementation of this technology is expected to improve the quality of learning and help students achieve a better understanding of genetics courses.