Battery-powered autonomous with no wire devices.
Published in Chapter:
The Influence of Emotion Recognition in Learning Processes: A Systematic Review
Cèlia Llurba (University Rovira i Virgili, Spain), Ramon Palau (University Rovira i Virgili, Spain), and Jordi Mogas (University Rovira i Virgili, Spain)
Copyright: © 2023
|Pages: 14
DOI: 10.4018/978-1-6684-8156-1.ch013
Abstract
In the context of smart classrooms (SC), one of the sources that can enrich data collection, analysis, real-time feedback, and decision making are students' emotions. This research tried to analyse the knowledge published over the last 5 years about the effectiveness of emotion recognition (ER) interventions in classrooms. A total of 214 articles were chosen based on the search terms and analysed according to the PRISMA statement, and finally 39 were selected. The findings of the interpretation of facial image-based ER have been upgraded with rapid and power progress of deep learning technology. As emotions can be detected using different sort of input, such as speech, facial expressions, videos, messages, and emoticons, the main point is tracking emotions while the lesson is taking place so as to warn the teacher. It is of utmost interest if one seeks to improve the student's academic performance, improve teaching, and understand students' learning behaviour.