Emotion Detection with AI: Development of Learning Media for Evaluation of Cognitive Load of Prospective Teacher in Genetics Lectures - Rahmat, Adi (Department of Biology Education, Faculty of Education and teacher Training, Maritime University of Raja Ali Haji, 2023)
Cognitive load can be measured, one of which is by emotions through facial expressions during learning. This research aims to develop learning media by integrating artificial intelligence (AI) that is able to detect the emotions of prospective teachers during genetics lectures. Using AI technology, the system can evaluate students' cognitive load in real-time through facial expression analysis. This learning media is equipped with emotion detection features, interactive learning materials, and an informative dashboard to monitor student learning progress. This research is a development research that refers to the Borg & Gall model. The data collection technique is in the form of questionnaires and questions integrated into AI media that detects student emotions, which are then analyzed using machine learning algorithms to identify the level of cognitive load during the lecture session. The results of the study showed that this learning medium was able to identify the emotional expression of each student in the genetics of mendelism with a percentage of 61.64% (surprised-happy) describing a moderately low-very low cognitive load, and 38.42% (sad-angry) describing a high cognitive load. So that with the acquisition of this data, it is known that more than 50% of students' emotional recordings (low cognitive load) can follow and understand the information obtained in the Mendelism genetics lecture. The application of this technology is expected to improve the quality of learning and help students achieve a better understanding of genetics courses.