Abstract
A common type of performance anxiety is the so-called “exam anxiety”, in which students can experience physical and emotional reactions before or during the exam due to the testing situation. If exam anxiety was already quite prevalent in students’ lives, one could expect that this condition got even worse due to the COVID-19 pandemic. Besides all the worrying factors that COVID-19 brought to the general population, students had to rapidly adapt to the reality of online exam modalities – introducing extra sources of stress. Therefore, our aim is to model the differences between online and offline modalities in the emotion regulation processes to overcome exam anxiety. To model these processes, we used a second-order adaptive network model. We employed reappraisal, since it is considered the most effective emotion regulation strategy to deal with this type of anxiety. We showed that, even though the reappraisal processes take place and the exam anxiety is regulated, the exam anxiety levels are higher in the online exams than in the offline exams.
I. Barradas, A. Kloc and N. Weng—The first three authors contributed equally to this research and the writing of the paper.
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Barradas, I., Kloc, A., Weng, N., Treur, J. (2022). A Second-Order Adaptive Network Model for Exam-Related Anxiety Regulation. In: Klimov, V.V., Kelley, D.J. (eds) Biologically Inspired Cognitive Architectures 2021. BICA 2021. Studies in Computational Intelligence, vol 1032. Springer, Cham. https://doi.org/10.1007/978-3-030-96993-6_4
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