Real-Time Emotion Recognition in Education
Author Information
Author(s): Cèlia Llurba, Ramon Palau
Primary Institution: Department of Pedagogy, University Rovira i Virgili, Tarragona, Spain
Hypothesis
Real-time emotion recognition can improve the teaching-learning process.
Conclusion
Real-time emotion recognition has the potential to enhance student engagement and academic performance, but challenges such as privacy concerns remain.
Supporting Evidence
- Emotion recognition can help improve students' academic performance.
- Real-time emotion recognition systems can provide immediate feedback to teachers.
- Privacy concerns are a significant barrier to implementing emotion recognition in classrooms.
- Most studies reviewed show positive outcomes for using emotion recognition in education.
- Technological advancements in AI and machine learning are enhancing emotion recognition capabilities.
Takeaway
This study looks at how recognizing students' emotions in real-time can help teachers teach better and make learning more fun.
Methodology
The study is a scoping review of literature focusing on real-time emotion recognition in educational settings.
Potential Biases
Potential bias due to the exclusion of non-English studies and those not focused on educational purposes.
Limitations
The review is limited to studies published after 2018 and does not include e-learning or virtual classes.
Participant Demographics
The review includes studies with various student groups, but specific demographics are not detailed.
Digital Object Identifier (DOI)
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