Key result
Deep learning system accurately detects student stress during online exams to analyze performance impact.
Why the study?
Students experience high stress during exams, but a system was needed to accurately detect stress levels during examinations and analyze its impact on performance and scoring.
The study proposes a deep learning-based system to detect student stress levels during online examinations and analyze its impact on performance.
Should not yet change practice; leaves open prospective validation of deep learning stress detection.
Nowadays, learning has changed its mode from offline to online, i.e., e-Learning. This e-learning has become more popular during the pandemic situations. Many platforms offer online exams and proctored exams, which are used at schools and colleges. Students' stress levels will be ordinarily high during examinations, whether offline or online, and the percentage of stress levels will be based on the students' cognitive behavior, subject knowledge, and the difficulty level of the questions. This study aims to propose a system for accurate stress level detection among students during the exam, thereby analyzing the impact of stress on their exam performance and scoring.
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Prabhakar et al. (2023) studied Stress during online examinations. Deep learning system for stress level detection was evaluated on Accurate stress level detection and impact on exam performance. This study proposes a deep learning system for accurate stress level detection among students during online exams to analyze the impact of stress on performance.
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