Differences in academic performance based on emotions in mathematics classes
DOI:
https://doi.org/10.22201/fesa.29928273e.2025.10.82Keywords:
Facial expresions, Analytic Geometric, Math performance, Control Value Theory, Affective Learning Framework.Abstract
The use of technologies to analyze facial expressions for emotion recognition and performance enhancement in education is widespread. The aim is to gain deeper insights into mathematical learning within this context, especially Analytical Geometry, integrating emotions and academic achievement. To achieve this, the study employs the Control- Value Theory and the Affective Framework for Learning as theoretical frameworks. A study involving 95 students was conducted, recording their facial expressions, and extracting emotions, alongside objective and subjective performance metrics. The findings reveal that high-performing students exhibit more emotional variability than their low-performing counterparts in objective assessment, whereas the latter express greater confidence in their abilities in subjective evaluations. The study concludes with recommendations for improving mathematical learning based on these insights.
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