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Engagement in Mathematics MOOC Forums

  • Chiara AndràEmail author
  • Elisabetta Repossi
Chapter

Abstract

The research focuses on mathematics MOOC discussion forums, how affective instances emerge from written interactions and how they can be measured. Interactionist research, as well as the intertwining of affective and cognitive components in students’ interactions, represents the theoretical background of our investigations. In particular, we refer to engagement as the main affective element in discussion forums. The affective lens is paired with network analysis to examine how and to what extent forums may represent an occasion for a deeper understanding of mathematics for the students. This paper reports on a pilot phase of the research and considers two examples of discussion forums that involved around ten students each. The findings from a small scale analysis serve as a basis for first, general conclusions.

Keywords

Conceptual and procedural Desires Motivation Online interactions Network analysis 

References

  1. Arvaja, M., Rasku-Puttonen, H., Häkkinen, P., & Eteläpelto, A. (2003). Constructing knowledge through a role-play in a web-based learning environment. Journal of Educational Computing Research, 28, 319–341.CrossRefGoogle Scholar
  2. Bastian, M., Heymann, S. & Jacomy, M. (2009). Gephi: An open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media. https://gephi.org/
  3. Centola, D. (2010). The spread of behavior in an online social network experiment. Science, 329, 1194–1197.CrossRefGoogle Scholar
  4. Crona, B., & Bodin, Ö. (2006). What you know is who you know? Communication patterns among resource users as a prerequisite for co-management. Ecology and Society, 11, 7.CrossRefGoogle Scholar
  5. Davis, B. (1996). Teaching mathematics: Toward a sound alternative. New York & London: Garland Publishing.Google Scholar
  6. Ernest, P. (1998). Social constructivism as a philosophy of mathematics. New York: State University of New York Press.Google Scholar
  7. Gallese, V., Eagle, M. E., & Migone, P. (2007). Intentional attunement: Mirror neurons and the neural underpinnings of interpersonal relations. Journal of the American Psychoanalytic Association, 55, 131–176.CrossRefGoogle Scholar
  8. Goldin, G. A. (2017). Motivating desires for classroom engagement in the learning of mathematics. In C. Andrà, D. Brunetto, E. Levenson, & P. Liljedahl (Eds.), Teaching and learning in math classrooms—emerging themes in affect-related research: Teachers’ beliefs, students’ engagement and social interaction. Springer Nature. 219–229.Google Scholar
  9. Goos, M. (2004). Learning mathematics in a classroom community of inquiry. Journal for Research in Mathematics Education, 35(4), 258–291.CrossRefGoogle Scholar
  10. Lave, J. (1988). Cognition in practice: Mind, mathematics and culture in everyday life. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  11. Leavitt, H. J. (1951). Some effects of certain communication patterns on group performance. The Journal of Abnormal and Social Psychology, 46, 38–50.CrossRefGoogle Scholar
  12. Naidu, S. (in press). Open educational practice: Caveat emptor. In D. Singh (Ed.), Responsible leadership: Higher education. Globethics.net.
  13. Nicolini, M., & Ocenasek, C. (1998). Environmental impact assessment with public participation: The case of a proposed landfill site in the Austrian Pinzgau. In H. Weidner (Ed.), Alternative dispute resolution in environmental conflicts: Experiences in 12 countries (pp. 330–339). Berlin, DE, Edition Sigma.Google Scholar
  14. Resnick, L. B., Levine, J. M., & Teasley, S. D. (1993). Perspectives on socially shared cognition. Washington, DC: American Psychological Association.Google Scholar
  15. Roth, W.-M., & Radford, L. (2011). A cultural historical perspective on teaching and learning. Rotterdam, NL: Sense Publishers.CrossRefGoogle Scholar
  16. Scott, J. (2000). Social network analysis: A handbook (2nd ed.). Thousand Oaks, CA: Sage.Google Scholar
  17. Snijders, T. A., van de Bunt, G. G., & Steglich, C. E. (2010). Introduction to stochastic actor-based models for network dynamics. Social Networks, 32, 44–60.CrossRefGoogle Scholar
  18. Todo, Y., Matous, P., & Mojo, D. (2015). Effects of social network structure on the diffusion and adoption of agricultural technology: Evidence from rural Ethiopia (WINPEC Working Paper Series No. E 1505).Google Scholar
  19. Vertegaal, R., Van der Veer, G. C., & Vons, H. (2000). Effects of gaze on multiparty mediated communication. Proceedings of GI 2000. Montreal, CA, 95–102.Google Scholar
  20. Zhang, J., Skryabin, M., & Song, X. (2016). Understanding the dynamics of MOOC discussion forums with simulation investigation for empirical network analysis (SIENA). Distance Education, 37(3), 270–286.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.MOX-Dipartimento di MatematicaPolitecnico di MilanoMilanItaly
  2. 2.Istituto di Cultura e Lingue “Marcelline”—sede TommaseoMilanItaly

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