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Detecting Collaborative Learning Through Emotions: An Investigation Using Facial Expression Recognition

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Book cover Intelligent Tutoring Systems (ITS 2019)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 11528))

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Abstract

Providing adaptive feedback to learners engaging in collaborative learning activities is one research topic in the development of intelligent tutoring systems. However, there is a need to investigate how to systematically evaluate a learner’s activities and provide feedback on them. The present study investigates how emotional states, detected through facial recognition, can be utilized to capture the learning process in a simple jigsaw-type collaborative task. It was predicted that when learners argue with each other and reason deeply, they may experience several emotional states such as positive and negative states. The results show that when learners work harder on developing a mutual understanding through conflictive interaction, negative emotions can be used to predict this process. This study contributes to the knowledge of how emotional states detected by facial recognition technology can be applied to predict learning process in conflictive tasks. Moreover, these empirical results will impact the development of adaptive feedback mechanisms for intelligent tutoring systems for collaborative learning.

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References

  1. Aronson, E., Patnoe, S.: The Jigsaw Classroom: Building Cooperation in the Classroom, 2nd edn. Addison Wesley Longman, New York (1997)

    Google Scholar 

  2. Azevedo, R., Cromley, J.: Does training on selfregulated learning facilitate students’ learning with hypermedia? J. Educ. Psychol. 96(3), 523–535 (2004)

    Article  Google Scholar 

  3. Biswas, G., Leelawong, K., Schwartz, D., Vye, N.: Learning by teaching: a new paradigm for educational software. Appl. Artif. Intell. 19(3), 363–392 (2005)

    Article  Google Scholar 

  4. Chi, M., Leeuw, N., Chiu, M., Lavancher, C.: Eliciting self-explanations improves understanding. Cogn. Sci. 18(3), 439–477 (1994)

    Google Scholar 

  5. von Davier, A.A., Hao, J., Liu, L., Kyllonen, P.: Interdisciplinary research agenda in support of assessment of collaborative problem solving: lessons learned from developing a collaborative science assessment prototype. Comput. Hum. Behav. 76, 631–640 (2017)

    Article  Google Scholar 

  6. D’Mello, S., Lehman, B., Pekrun, R., Graesser, A.: Confusion can be beneficial for learning. Learn. Instr. 29, 153–170 (2014)

    Article  Google Scholar 

  7. Fiore, S.M., Rosen, M.A., Smith-Jentsch, K.A., Salas, E., Letsky, M., Warner, N.: Toward an understanding of macrocognition in teams: predicting processes in complex collaborative contexts. Hum. Factors 52, 203–224 (2010)

    Article  Google Scholar 

  8. Graesser, A., Chipman, P., Haynes, B., Olney, A.: AutoTutor: an intelligent tutoring system with mixed-initiative dialogue. IEEE Trans. Educ. 48(4), 612–618 (2005)

    Article  Google Scholar 

  9. Graesser, A., McNamara, D.S.: Computational analyses of multilevel discourse comprehension. Top. Cogn. Sci. 3(2), 371–398 (2011). https://doi.org/10.1111/j.1756-8765.2010.01081.x

    Article  Google Scholar 

  10. Hayashi, Y.: On pedagogical effects of learner-support agents in collaborative interaction. In: Proceeding of the 11th International Conference on Intelligent Tutoring Systems (ITS 2012), pp. 22–32 (2012)

    Chapter  Google Scholar 

  11. Hayashi, Y.: Togetherness: Multiple pedagogical conversational agents as companions in collaborative learning. In: Proceeding of the 12th International Conference on Intelligent Tutoring Systems (ITS 2014), pp. 114–123 (2014)

    Chapter  Google Scholar 

  12. Hayashi, Y.: Coordinating knowledge integration with pedagogical agents: effects of agent gaze gestures and dyad synchronization. In: Proceeding of the 13th International Conference on Intelligent Tutoring Systems (ITS 2016), pp. 254–259 (2016)

    Google Scholar 

  13. Hayashi, Y.: Gaze feedback and pedagogical suggestions in collaborative learning. In: Nkambou, R., Azevedo, R., Vassileva, J. (eds.) ITS 2018. LNCS, vol. 10858, pp. 78–87. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-91464-0_8

    Chapter  Google Scholar 

  14. Hayashi, Y.: The power of a “maverick” in collaborative problem solving: an experimental investigation of individual perspective-taking within a group. Cogn. Sci. 42(S1), 69–104 (2018). https://doi.org/10.1111/cogs.12587

    Article  Google Scholar 

  15. Hesse, F., Care, E., Buder, J., Sassenberg, K., Griffin, P.: A framework for teachable collaborative problem solving skills. In: Griffin, P., Care, E. (eds.) Assessment and Teaching of 21st Century Skills. EAIA, pp. 37–56. Springer, Dordrecht (2015). https://doi.org/10.1007/978-94-017-9395-7_2

    Chapter  Google Scholar 

  16. Koedinger, K.R., Anderson, J.R., Hadley, W.H., Mark, M.A.: Intelligent tutoring goes to school in the big city. Int. J. Artif. Intell. Educ. (IJAIED) 8, 30–43 (1997)

    Google Scholar 

  17. Kuilenburg, v.H., Wiering, M., Uyl, d.M.: A model based method for automatic facial expression recognition. In: Proceedings of the European Conference on Machine Learning (ECML2005), pp. 194–205 (2005)

    Google Scholar 

  18. Kumar, R., Rose, C.: Architecture for building conversational architecture for building conversational agents that support collaborative learning. IEEE Trans. Learn. Technol. 4(1), 21–34 (2011)

    Article  Google Scholar 

  19. Lave, J., Wenger, E.: Situated Learning - Legitimate Peripheral Participation. Cambridge University Press, Cambridge (1991)

    Book  Google Scholar 

  20. Leelawong, K., Biswas, G.: Designing learning by teaching agents: the Betty’s brain system. Int. J. Artif. Intell. Educ. 18(3), 181–208 (2008)

    Google Scholar 

  21. Matsuda, N., Yarzebinski, E., Keiser, V., Raizada, R., Stylianides, G.J., Koedinger, K.R.: Studying the effect of a competitive game show in a learning by teaching environment. Int. J. Artif. Intell. Educ. 23(1), 1–21 (2013)

    Article  Google Scholar 

  22. McNamara, D., O’Reilly, T., Rowe, M.: iSTART: A Web-Based Tutor that Teaches Self-explanation and Metacognitive Reading Strategies. Lawrence Erlbaum Associates, Mahwah (2007)

    Google Scholar 

  23. Meier, A., Spada, H., Rummel, N.: A rating scheme for assessing the quality of computer-supported collaboration processes. Int. J. Comput.-Support. Collab. Learn. 2(1), 63–86 (2007). https://doi.org/10.1007/s11412-006-9005-x

    Article  Google Scholar 

  24. Metcalfe, J., Wiebe, D.: Intuition in insight and noninsight problem solving. Mem. Cogn. 15(3), 238–246 (1987)

    Article  Google Scholar 

  25. Miyake, N.: Constructive interaction and the interactive process of understanding. Cogn. Sci. 10(2), 151–177 (1986)

    Article  Google Scholar 

  26. OECD: PISA 2015 Results (Volume V): Collaborative Problem Solving. OECD Publishing, Paris (2017). https://doi.org/10.1787/9789264285521-en

  27. Shirouzu, H., Miyake, N., Masukawa, H.: Cognitively active externalization for situated reflection. Cogn. Sci. 26(4), 469–501 (2002)

    Article  Google Scholar 

  28. VanLehn, K., Graesser, A.C., Jackson, G.T., Jordan, P., Olney, A., Rosé, C.P.: When are tutorial dialogues more effective than reading? Cogn. Sci. 31(1), 3–62 (2007). https://doi.org/10.1080/03640210709336984

    Article  Google Scholar 

  29. Vygotsky, L.S.: The Development of Higher Psychological Processes. Harvard University Press, Cambridge (1980)

    Google Scholar 

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Acknowledgments

This work was supported by Grant-in-Aid for Scientific Research (C), Japan Society for the Promotion of Science (JSPS) KAKENHI Grant Number 16K00219.

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Authors and Affiliations

  1. College of Comprehensive Psychology, Ritsumeikan University, 2-150 Iwakura-cho, Osaka, Ibaraki, 567-8570, Japan

    Yugo Hayashi

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  1. Yugo Hayashi
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Correspondence to Yugo Hayashi .

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Editors and Affiliations

  1. University of the West Indies, Kingston, Jamaica

    Andre Coy

  2. Ritsumeikan University, Osaka, Japan

    Yugo Hayashi

  3. Athabasca University, Edmonton, AB, Canada

    Maiga Chang

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Hayashi, Y. (2019). Detecting Collaborative Learning Through Emotions: An Investigation Using Facial Expression Recognition. In: Coy, A., Hayashi, Y., Chang, M. (eds) Intelligent Tutoring Systems. ITS 2019. Lecture Notes in Computer Science(), vol 11528. Springer, Cham. https://doi.org/10.1007/978-3-030-22244-4_12

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  • DOI: https://doi.org/10.1007/978-3-030-22244-4_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-22243-7

  • Online ISBN: 978-3-030-22244-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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