Effects of Facial Recognition and Text Semantic Recognition on Affective Tutoring System

Abstract

Facial recognition is the fastest method to detect emotions, and it can be combined with text semantic recognition to increase the accuracy of emotion detection. Emotions and creativity have often been discussed in recent years. A student will be interested in learning as long as he or she enjoys learning. Mind mapping is an active and simultaneous use of the left and right brains to stimulate the creativity and imagination of the learner, which is complementary to positive emotion. This study constructed an affective adaptive learning system that combines text emotions and facial clues in chatbot conversations to understand the emotional responses of learners during the learning process. The system is tailored to accommodate diverse learners through modules of varying difficulty scales, the incorporation of mind maps to support teaching and learning, and the implementation of asynchronous online discussion forums for discourse and feedback on course-related topics. The results revealed significant differences in critical thinking, reflective thinking, and problem-solving skills between the experimental and control groups, and students in the experimental group outperformed those in the control group on the creation of mind maps.