Design of a proposal for the recognition of emotional expression using Machine Learning in Education

Abstract

The advancement of technology demands training in Artificial Intelligence, Machine Learning and Computational Thinking skills. Advances in Neurocognition and Neuroeducation underline the importance of emotions
during the learning of scientific and mathematical contents. The study focuses on an educational intervention proposal using Machine Learning and Artificial Intelligence to work on Computational Thinking skills and emotional recognition and expression in Primary Education. First, an unplugged activity is designed. Subsequently, a Scratch® programming on the emotions felt by students during science and math activities is carried out. The last activity allows to update the emotional
recognition since the facial expression changes continuously, by using Machine Learning for Kids. Machine Learning can be carried out in initial stages through adapted activities, to develop Computational Thinking skills, as well as to work on emotions, which is why this type of proposal is promoted during the learning of scientific and mathematical content.