Abstract
Most research on emotions and behaviors in science education has used observational or declarative methods. These approaches present certain strengths, but they have important limitations for deepening our understanding of the affective domain. In this work, we develop a method for analyzing the dynamics of affective variables during an inquiry-based activity with an artificial intelligence system that recognizes facial expressions. Although the study was carried out on 12 students, here we analyze data from one person to describe the method in detail. The videos were processed with a software which outputs behavioral and emotional signals. To analyze them, we applied centered moving averages with different widths. This allowed us to align and interpret the dynamics of emotional, behavioral, and learning actions. We found spikes of Surprise when the student seemingly implemented their models, and their predictions were not met. Our analysis suggests the existence of four phases in the inquiry-based activity with specific dynamic profiles. This work lays the foundations for researchers and teachers to develop tools to monitor emotions and behaviors.
License
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Article Type: Research Article
EURASIA J Math Sci Tech Ed, Volume 18, Issue 4, April 2022, Article No: em2099
https://doi.org/10.29333/ejmste/11927
Publication date: 26 Mar 2022
Article Views: 2693
Article Downloads: 1941
Open Access Disclosures References How to cite this article