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Understanding Physiological Responses of Students Over Different Courses (2407.14015v1)

Published 19 Jul 2024 in cs.HC

Abstract: Student engagement plays a vital role in academic success with high engagement often linked to positive educational outcomes. Traditionally, student engagement is measured through self-reports, which are both labour-intensive and not real-time. An emerging alternative is monitoring physiological signals such as Electrodermal Activity (EDA) and Inter-Beat Interval (IBI), which reflect students' emotional and cognitive states. In this research, we analyzed these signals from 23 students wearing Empatica E4 devices in real-world scenarios. Diverging from previous studies focused on lab settings or specific subjects, we examined physiological synchrony at the intra-student level across various courses. We also assessed how different courses influence physiological responses and identified consistent temporal patterns. Our findings show unique physiological response patterns among students, enhancing our understanding of student engagement dynamics. This opens up possibilities for tailoring educational strategies based on unobtrusive sensing data to optimize learning outcomes.

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References (40)
  1. Kamil Akhuseyinoglu and Peter Brusilovsky. 2021. Data-Driven Modeling of Learners’ Individual Differences for Predicting Engagement and Success in Online Learning. In Proceedings of the 29th ACM Conference on User Modeling, Adaptation and Personalization (Utrecht, Netherlands) (UMAP ’21). Association for Computing Machinery, New York, NY, USA, 201–212. https://doi.org/10.1145/3450613.3456834
  2. An Experimental Platform for Real-Time Students Engagement Measurements from Video in STEM Classrooms. Sensors 23, 3 (2023). https://doi.org/10.3390/s23031614
  3. Effect of rosary prayer and yoga mantras on autonomic cardiovascular rhythms: Comparative study. BMJ (Clinical research ed.) 323 (11 2000), 1446–9.
  4. Student Engagement and Student Learning: Testing the Linkages*. Research in Higher Education 47 (2006), 1–32. https://api.semanticscholar.org/CorpusID:16120936
  5. Handbook of Research on Student Engagement. Springer US (2012). https://api.semanticscholar.org/CorpusID:150500309
  6. Federico Cirett Galan and Carole Beal. 2012. EEG Estimates of Engagement and Cognitive Workload Predict Math Problem Solving Outcomes. User Modeling, Adaptation, and Personalization. https://doi.org/10.1007/978-3-642-31454-4_5
  7. Virginia S. Cowen and Troy B. Adams. 2007. Heart rate in yoga asana practice: A comparison of styles. Journal of Bodywork and Movement Therapies 11 (2007), 91–95. https://api.semanticscholar.org/CorpusID:52028506
  8. Hugo Critchley and Yoko Nagai. 2013. Electrodermal Activity (EDA). Springer New York, New York, NY, 666–669. https://doi.org/10.1007/978-1-4419-1005-9_13
  9. Reading the Room: Automated, Momentary Assessment of Student Engagement in the Classroom: Are We There Yet? Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6, 3, Article 112 (sep 2022), 26 pages. https://doi.org/10.1145/3550328
  10. Assessment of Heart Rates and Blood Pressure in Different Salat Positions. Journal of Physical Therapy Science 25 (2013), 211–214. https://api.semanticscholar.org/CorpusID:41515240
  11. Ruth Feldman. 2007. Parent-infant synchrony and the construction of shared timing; physiological precursors, developmental outcomes, and risk conditions. Journal of child psychology and psychiatry, and allied disciplines 48 3-4 (2007), 329–54. https://api.semanticscholar.org/CorpusID:22422275
  12. Student arousal, engagement, and emotion relative to Physical Education periods in school. Trends in Neuroscience and Education 33 (2023), 100215. https://doi.org/10.1016/j.tine.2023.100215
  13. Understanding occupants’ behaviour, engagement, emotion, and comfort indoors with heterogeneous sensors and wearables. Scientific Data 9, 1 (2022), 261.
  14. Individual and Group-Wise Classroom Seating Experience: Effects on Student Engagement in Different Courses. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6, 3, Article 115 (sep 2022), 23 pages. https://doi.org/10.1145/3550335
  15. N-Gage: Predicting in-Class Emotional, Behavioural and Cognitive Engagement in the Wild. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 4, 3, Article 79 (sep 2020), 26 pages. https://doi.org/10.1145/3411813
  16. Using Unobtrusive Wearable Sensors to Measure the Physiological Synchrony Between Presenters and Audience Members. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3 (2019), 1 – 19. https://api.semanticscholar.org/CorpusID:91186807
  17. Use of wearable devices to study activity of children in classroom; Case study — Learning geometry using movement. Computer Communications 150 (2020), 581–588. https://doi.org/10.1016/j.comcom.2019.12.019
  18. pyHRV: Development and evaluation of an open-source python toolbox for heart rate variability (HRV). In Proc. Int’l Conf. on Electrical, Electronic and Computing Engineering (IcETRAN). 822–828.
  19. Moments That Matter? On the Complexity of Using Triggers Based on Skin Conductance to Sample Arousing Events Within an Experience Sampling Framework. European Journal of Personality 34 (05 2020). https://doi.org/10.1002/per.2252
  20. Trends in Heart-Rate Variability Signal Analysis. Frontiers in Digital Health 3 (2021). https://api.semanticscholar.org/CorpusID:232051526
  21. Impact of Individual Differences on User Experience with a Visualization Interface for Public Engagement. In Adjunct Publication of the 25th Conference on User Modeling, Adaptation and Personalization (Bratislava, Slovakia) (UMAP ’17). Association for Computing Machinery, New York, NY, USA, 247–252. https://doi.org/10.1145/3099023.3099055
  22. Unobtrusive Assessment of Students’ Emotional Engagement during Lectures Using Electrodermal Activity Sensors. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2 (2018), 1 – 21.
  23. Chung Kwan Lo and Khe Foon Timothy Hew. 2021. Student Engagement in Mathematics Flipped Classrooms: Implications of Journal Publications From 2011 to 2020. Frontiers in Psychology 12 (2021). https://api.semanticscholar.org/CorpusID:235249801
  24. NeuroKit2: A Python toolbox for neurophysiological signal processing. Behavior Research Methods 53 (2020), 1689 – 1696. https://api.semanticscholar.org/CorpusID:231757711
  25. Are we together or not? The temporal interplay of monitoring, physiological arousal and physiological synchrony during a collaborative exam. International Journal of Computer-Supported Collaborative Learning 14 (2019), 467 – 490. https://doi.org/10.1007/s11412-019-09311-4
  26. Interpersonal Autonomic Physiology: A Systematic Review of the Literature. Personality and Social Psychology Review 21 (2017), 141 – 99. https://api.semanticscholar.org/CorpusID:24127860
  27. Spouses’ Cortisol Associations and Moderators: Testing Physiological Synchrony and Connectedness in Everyday Life. Family process 52 (06 2013), 284–98. https://doi.org/10.1111/j.1545-5300.2012.01413.x
  28. Li Funn Phung. 2017. Task preference, affective response, and engagement in L2 use in a US university context. Language Teaching Research 21 (2017), 751 – 766. https://api.semanticscholar.org/CorpusID:151876093
  29. Fabian T. Ramseyer and Wolfgang Tschacher. 2011. Nonverbal synchrony in psychotherapy: coordinated body movement reflects relationship quality and outcome. Journal of consulting and clinical psychology 79 3 (2011), 284–95. https://api.semanticscholar.org/CorpusID:32001201
  30. 15 Minutes of Attention in Class: Variability of Heart Rate, Personality, Emotion and Chronotype. Creative Education 10 (01 2019), 2428–2447. https://doi.org/10.4236/ce.2019.1011172
  31. Student Engagement in Adolescence: A Scoping Review of Longitudinal Studies 2010-20. Journal of Research on Adolescence 31 (05 2021), 256–272. https://doi.org/10.1111/jora.12619
  32. Stan Salvador and Philip K. Chan. 2004. FastDTW: Toward Accurate Dynamic Time Warping in Linear Time and Space. https://api.semanticscholar.org/CorpusID:6226669
  33. Feature Extraction and Selection for Emotion Recognition from Electrodermal Activity. IEEE Transactions on Affective Computing PP (02 2019), 1–1. https://doi.org/10.1109/TAFFC.2019.2901673
  34. Electroencephalographic findings during mantra meditation (transcendental meditation). A controlled, quantitative study of experienced meditators. Electroencephalography and clinical neurophysiology 51 4 (1981), 434–42. https://api.semanticscholar.org/CorpusID:4617023
  35. Analysis of the ECG Signal to Understand the Effect of Regional State Anthem of Odisha in Young Reproductively Active Odia Females. 2017 14th IEEE India Council International Conference (INDICON) (2017), 1–6. https://doi.org/10.1109/INDICON.2017.8487919
  36. Comparative Study of the Impact of Active Meditation Protocol and Silence Meditation on Heart Rate Variability and Mood in Women. International Journal of Yoga 13 (09 2020), 255–260. https://doi.org/10.4103/ijoy.IJOY_18_20
  37. Marion A. Wenger and Basu K. Bagchi. 2007. Studies of autonomic functions in practitioners of Yoga in India. Behavioral science 6 (2007), 312–23. https://api.semanticscholar.org/CorpusID:7425509
  38. The Role of Heart Rate Variability (HRV) in Different Hypertensive Syndromes. Diagnostics 13 (02 2023), 785. https://doi.org/10.3390/diagnostics13040785
  39. What Do Students’ Interactions with Online Lecture Videos Reveal about Their Learning?. In Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (Barcelona, Spain) (UMAP ’22). Association for Computing Machinery, New York, NY, USA, 295–305. https://doi.org/10.1145/3503252.3531315
  40. Modeling Intra- and Inter-individual Changes in L2 Classroom Engagement. Applied Linguistics (12 2022).
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