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<p>Students preparing for high-stakes entrance examinations and other job qualification tests often face intense academic stress, significantly affecting their emotional well-being, study habits, and overall performance. Understanding these challenges is essential for developing effective support mechanisms. This study examines students’ emotional experiences, coping strategies, study behaviours, social support systems, and engagement with learning platforms while exploring how multimodal learning analytics (MMLA) can enhance exam preparedness. A mixed-methods research design was employed, combining quantitative survey data with qualitative insights to understand students’ experiences comprehensively. The sample consisted of 417 students preparing for competitive entrance exams. Data analysis revealed that exam pressure is a major concern, with students struggling to maintain emotional balance under prolonged academic demands. Based on the findings, this study proposes an MMLA framework and its implementation guidelines to monitor academic stress and optimise study routines systematically with a structured framework validation plan. The implications emphasise the need for targeted stress management programs, adaptive learning solutions, and institutional policies integrating analytics-driven educational support for high-stakes exam aspirants.</p>

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Mastering Emotions: Multimodal Learning Analytics (MMLA) Framework for Data-Driven Insights in Exam-Based Assessments

  • 期刊论文

  • 发表日期：

    2025年12月27日

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  • S. Asha,
  • V. P. Joshith

摘要

Students preparing for high-stakes entrance examinations and other job qualification tests often face intense academic stress, significantly affecting their emotional well-being, study habits, and overall performance. Understanding these challenges is essential for developing effective support mechanisms. This study examines students’ emotional experiences, coping strategies, study behaviours, social support systems, and engagement with learning platforms while exploring how multimodal learning analytics (MMLA) can enhance exam preparedness. A mixed-methods research design was employed, combining quantitative survey data with qualitative insights to understand students’ experiences comprehensively. The sample consisted of 417 students preparing for competitive entrance exams. Data analysis revealed that exam pressure is a major concern, with students struggling to maintain emotional balance under prolonged academic demands. Based on the findings, this study proposes an MMLA framework and its implementation guidelines to monitor academic stress and optimise study routines systematically with a structured framework validation plan. The implications emphasise the need for targeted stress management programs, adaptive learning solutions, and institutional policies integrating analytics-driven educational support for high-stakes exam aspirants.