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Towards emotion awareness tools to support emotion and appraisal regulation in academic contexts


This paper studies learners’ emotion awareness in university level academic contexts as a first step to help learners regulate their emotions. Existing emotion awareness tools offer little information on learners’ emotions and their antecedents. This study created an emotion-reporting grid for university students based on the emotions they experienced daily. Students were interviewed based on their self-reported grid. A quantitative descriptive analysis of these retrospective interviews was conducted based on Pekrun’s control-value theory of achievement emotions. Student transcripts were analyzed based on the focus of their emotions (retrospective, activity, or prospective), the causes they attribute to their emotions (agent or external circumstances) and how they appraised the situation in which they experienced the emotions (value and control). We discuss the results with regard to the types of emotion-oriented and appraisal-oriented regulation strategies used in learning contexts and draw implications for the design of emotion awareness tools to support emotion regulation processes.

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  1. Boden, M. T., & Thompson, R. J. (2015). Facets of emotional awareness and associations with emotion regulation and depression. Emotion,15(3), 399–410.

  2. Boekaerts, M. (2010). The crucial role of motivation and emotion in classroom learning. In H. Dumont, D. Istance, & F. Benavides (Eds.), The nature of learning: Using research to inspire practice (pp. 91–111). Paris: OECD Publishing.

  3. Cernea, D., & Kerren, A. (2015). A survey of technologies on the rise for emotion-enhanced interaction. Journal of Visual Languages & Computing,31, 70–86.

  4. Cernea, D., Weber, C., Ebert, A., & Kerren, A. (2013). Emotion scents—A method of representing user emotions on GUI widgets. In Proceedings of the SPIE 2013 conference on visualization and data analysis (VDA’13), Burlingame, CA: SPIE.

  5. Dandoy, A. C., & Goldstein, A. G. (1990). The use of cognitive appraisal to reduce stress reactions: A replication. Journal of Social Behavior & Personality,5(4), 275–285.

  6. D’Mello, S., Lehman, B., Pekrun, R., & Graesser, A. (2014). Confusion can be beneficial for learning. Learning and Instruction,29, 153–170.

  7. Ez-Zaouia, M., & Lavoué, E. (2017). EMODA: A tutor oriented multimodal and contextual emotional dashboard. In Proceedings of the seventh international learning analytics & knowledge conference (pp. 429–438). Vancouver. ACM.

  8. Fessl, A., Rivera-Pelayo, V., Pammer, V., & Braun, S. (2012). Mood tracking in virtual meetings. In 21st century learning for 21st century skills (Vol. 7563, pp. 377–382). Saarbrücken: Springer.

  9. Goetz, T., Frenzel, A. C., Stoeger, H., & Hall, N. C. (2010). Antecedents of everyday positive emotions: An experience sampling analysis. Motivation and Emotion,34(1), 49–62.

  10. Greenberg, L. (2008). Emotion and cognition in psychotherapy: The transforming power of affect. Canadian Psychology/Psychologie Canadienne,49(1), 49.

  11. Gross, J. J. (1998). Antecedent- and response-focused emotion regulation: Divergent consequences for experience, expression, and physiology. Journal of Personality and Social Psychology,74(1), 224–237.

  12. Gross, J. J. (2008). Emotion regulation. In M. Lewis, J. M. Haviland-Jones, & L. F. Barrett (Eds.), Handbook of emotions (Vol. 3, pp. 497–513). New-York: Guilford Press.

  13. Gross, J. J. (2015). Emotion regulation: Current status and future prospects. Psychological Inquiry, 26(1), 1–26.

  14. Gross, J. J., & John, O. P. (2003). Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being. Journal of Personality and Social Psychology,85(2), 348.

  15. Hadwin, A. F., Järvelä, S., & Miller, M. (2011). Self-regulated, co-regulated, and Socially Shared Regulation of Learning. In B. Zimmerman, D. Schunk, & N. Perry (Eds.), Handbook of self-regulation of learning and performance (pp. 65–82). Routledge: Taylor & Francis.

  16. Jarvela, S., & Hadwin, A. F. (2013). New frontiers: Regulating learning in CSCL. Educational Psychologist,48(1), 25–39.

  17. Lajoie, S. P., Lee, L., Bassiri, M., Cruz-Panesso, I., Kazemitabar, M., Poitras, E., Hmelo-Silver, C., Wiseman, J., Chan, L., & Lu, J. (2015). The role of regulation in medical student learning in small groups: Regulating oneself and others’ learning and emotions. In Järvelä, S. & Hadwin, A. (Eds.) Special issue Examining the emergence and outcomes of regulation in CSCL. Journal of Computer and Human Behavior, 52, 601–616.

  18. Lane, R. D., Quinlan, D. M., Schwartz, G. E., Walker, P. A., & Zeitlin, S. B. (1990). The levels of Emotional Awareness Scale: A cognitive-developmental measure of emotion. Journal of Personality Assessment,55(1–2), 124–134.

  19. Lane, R. D., & Schwartz, G. E. (1987). Levels of emotional awareness: A cognitive-developmental theory and its application to psychopathology. The American Journal of Psychiatry.

  20. Lavoué, É., Molinari, G., Prié, Y., & Khezami, S. (2015). Reflection-in-action markers for reflection-on-action in computer-supported collaborative learning settings. Computers & Education,88, 129–142.

  21. Leony, D., Muñoz-Merino, P. J., Pardo, A., & Delgado Kloos, C. (2013). Provision of awareness of learners’ emotions through visualizations in a computer interaction-based environment. Expert Systems with Applications,40(13), 5093–5100.

  22. Linnenbrink-Garcia, L., Patall, E. A., & Pekrun, R. (2016). Adaptive motivation and emotion in education research and principles for instructional design. Policy Insights from the Behavioral and Brain Sciences,3(2), 228–236.

  23. McDuff, D., Karlson, A., Kapoor, A., Roseway, A., & Czerwinski, M. (2012). AffectAura: An intelligent system for emotional memory. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 849–858). New York: ACM.

  24. Meinhardt, J., & Pekrun, R. (2003). Attentional resource allocation to emotional events: An ERP study. Cognition and Emotion,17(3), 477–500.

  25. Miron-Shatz, T., Stone, A., & Kahneman, D. (2009). Memories of yesterday’s emotions: Does the valence of experience affect the memory-experience gap? Emotion,9(6), 885.

  26. Molinari, G., Chanel, G., Bétrancourt, M., Pun, T., & Bozelle, C. (2013). Emotion feedback during computer-mediated collaboration: Effects on self-reported emotions and perceived interaction. In Proceedings of the 10th international conference on computer supported collaborative learning, CSCL 2013 (Vol. 1, pp. 336–344)

  27. Paris, S. G., & Paris, A. H. (2001). Classroom applications of research on self-regulated learning. Educational Psychologist,36(2), 89–101.

  28. Pekrun, R. (2006). The control-value theory of achievement emotions: Assumptions, corollaries, and implications for educational research and practice. Educational Psychology Review,18(4), 315–341.

  29. Pekrun, R. (2014). Emotions and learning. Belley: International Academy of Education.

  30. Pekrun, R. (2016). Academic emotions. Handbook of Motivation at School,2, 120–144.

  31. Pekrun, R., Elliot, A. J., & Maier, M. A. (2006). Achievement goals and discrete achievement emotions: A theoretical model and prospective test. Journal of Educational Psychology,98(3), 583.

  32. Pekrun, R., Elliot, A. J., & Maier, M. A. (2009). Achievement goals and achievement emotions: Testing a model of their joint relations with academic performance. Journal of Educational Psychology,101(1), 115–135.

  33. Pekrun, R., Goetz, T., Titz, W., & Perry, R. P. (2002). Academic emotions in students’ self-regulated learning and achievement: A program of qualitative and quantitative research. Educational Psychologist,37(2), 91–105.

  34. Pekrun, R., Lichtenfeld, S., Marsh, H. W., Murayama, K., & Goetz, T. (2017). Achievement emotions and academic performance: Longitudinal models of reciprocal effects. Child Development,88(5), 1653–1670.

  35. Pintrich, P. R. (2004). A Conceptual framework for assessing motivation and self-regulated learning in college students. Educational Psychology Review,16(4), 385–407.

  36. Rheinberg, F., Vollmeyer, R., & Rollett, W. (2000). Motivation and action in self-regulated learning. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 503–529). New York: Academic Press.

  37. Rieffe, C. J., Oosterveld, P., Miers, A. C., Meerum Terwogt, M., & Ly, V. (2008). Emotion awareness and internalizing symptoms in children and adolescents; The Emotional Awareness Questionaire revised. Personality and Individual Differences,45(8), 756–761.

  38. Ruiz, S., Charleer, S., Urretavizcaya, M., Klerkx, J., Fernández-Castro, I., & Duval, E. (2016). Supporting learning by considering emotions: Tracking and visualization a case study. In Proceedings of the sixth international conference on learning analytics & knowledge (pp. 254–263). New York: ACM.

  39. Sander, D., Grandjean, D., & Scherer, K. R. (2005). A systems approach to appraisal mechanisms in emotion. Neural Networks,18(4), 317–352.

  40. Scherer, K. R., Schorr, A., & Johnstone, T. (2001). Appraisal processes in emotion: Theory, methods, research. Oxford: Oxford University Press.

  41. Subic-Wrana, C., Beutel, M. E., Brähler, E., Stöbel-Richter, Y., Knebel, A., Lane, R. D., et al. (2014). How is emotional awareness related to emotion regulation strategies and self-reported negative affect in the general population? PLoS ONE,9(3), e91846.

  42. Sun, S., Lavoué, E., Aritajati, C., Tabard, A., Rosson, M.-B. (2019. Using and perceiving emoji in design peer feedback. In Proceedings of the 13th international conference on computer supported collaborative learning (CSCL 2019) (pp. 296–303), Lyon, France,

  43. Tian, F., Zhang, H., Li, L., Zheng, Q., & Yang, Y. (2011). Visualizing e-Learner emotion, topic, and group structure in chinese interactive texts. In 2011 IEEE 11th international conference on advanced learning technologies (pp. 587–589).

  44. Tong, E. M. W., Bishop, G. D., Enkelmann, H. C., Why, Y. P., Diong, S. M., Khader, M., et al. (2007). Emotion and appraisal: A study using ecological momentary assessment. Cognition and Emotion,21(7), 1361–1381.

  45. Valiente, C., Swanson, J., & Eisenberg, N. (2012). Linking students’ emotions and academic achievement: When and why emotions matter. Child Development Perspectives,6(2), 129–135.

  46. Versluis, A., Verkuil, B., Lane, R. D., Hagemann, D., Thayer, J. F., & Brosschot, J. F. (2018). Ecological momentary assessment of emotional awareness: Preliminary evaluation of psychometric properties. Current Psychology.

  47. Volet, S., & Vauras, M. (2013). Interpersonal regulation of learning and motivation: Methodological advances. New York: Routledge.

  48. Wolters, C. A. (2003). Regulation of motivation: Evaluating an underemphasized aspect of self-regulated learning. Educational Psychologist,38(4), 189–205.

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Our research was conducted as part of the EmoViz project funded by the Région Auvergne-Rhône-Alpes. We thank the students who volunteered to participate to this study.


This study was funded by the Region Auvergne Rhône-Alpes, Coopera Program (Grant Number 15.005444.01).

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Correspondence to Elise Lavoué.

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Appendix 1: Emotion recording grid


Appendix 2: Interviews—coding schemes

Analysis: The analysis unit is an emotion felt by the participant.


  • We keep only academic related emotions (not professional or personal), i.e. emotions students experienced in academic situations.

  • We keep non-academic emotions when accompanying academic related emotions.

  • If the emotion is formulated by the interviewer, we identify it as a unit if it is linked to the content of a participant’s sentence (not just rewording or inciting participant to develop ideas).

Categories for coding

Emotion (D’Mello et al. 2014)Anxiety, boredom, confusion, curiosity, delight, engagement, frustration, surprise, neutral
SettingIndividualThe participant is working alone (even in class)SI“I was a bit anxious coz I had to do a lot of things”
GroupThe participant is working in groupSG“I was like bored and neutral because we were not doing anything”

Academic related emotions: object focus, causalities and appraisal (Pekrun 2006)

Object focusRetrospectiveEmotions pertain to the outcomes of achieved activities (e.g., pride or shame experienced after feedback of achievement)
Attention is on the past
OTR“I felt like I was going through the work at a, at a decent rate, and yea, so I was happy about that”
ActivityEmotions felt during ongoing activities, the attentional focus is on the action, not on outcomes.
Attention is on the present
OTA“I get frustrated because they started to talk about stuff I don’t remember”
ProspectiveEmotions pertain to the outcomes of ongoing activities or activities to come (e.g., hope for success, anxiety of failure)
Attention is on the future
OTP“a bit of like anxiety, coz like the exam coming up”
AgentSelfEmotion is caused by the selfAS“I felt anxiety, umm, because I’ve never, never did that before”
OthersEmotion is caused by other personsAO“I felt anxious when I realized that the others were stressed by the exams”
GroupEmotion is caused by the group, including the participantAG“I was not frustrating or exciting because we were not doing anything”
External circumstancesEmotion is caused by external circumstances (independent of self and others)AC“a bit of like anxiety, coz like the exam coming up”
Subjective valuePositivePositive subjective value of activities and outcomes (e.g. high importance of success)PV“Yea I was actually interested in the material”
“This activity is very important for me”
NegativeNegative subjective value of activities and outcomes (e.g. low importance of success)NV“This course doesn’t matter for me”
“I’m not really interested in this course material.
Subjective controlHighHigh subjective control over achievement activities and their outcomes (e.g., expectations that persistence at studying can be enacted, and that it will lead to success)HC“I can do well in school if I want to”
“I felt engaged with the material. I actually understood”
“I feel very confident about this course, I have well prepared the exam”
LowLow subjective control over achievement activities and their outcomes (e.g., few expectations about enaction of activities, and that it will lead to failure)LC“I can’t get good grades no matter what I do”
“I felt anxiety, umm, because I’ve never, never did that before, like applying for a lab, that I wasn’t really sure if I was qualified for”

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Lavoué, E., Kazemitabar, M., Doleck, T. et al. Towards emotion awareness tools to support emotion and appraisal regulation in academic contexts. Education Tech Research Dev 68, 269–292 (2020).

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  • Emotion awareness tool
  • Emotion regulation
  • Appraisal regulation
  • Causal attributions
  • Academic context
  • Quantitative descriptive study