Automatic Group Formation in a MOOC Based on Students’ Activity Criteria

  • Luisa Sanz-MartínezEmail author
  • Alejandra Martínez-Monés
  • Miguel L. Bote-Lorenzo
  • Juan A. Muñoz-Cristóbal
  • Yannis Dimitriadis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10474)


Although there is significant evidence regarding benefits of small group collaboration in small-scale contexts, several challenges have been detected about the use of collaborative learning in MOOCs. Group formation, which is a crucial activity in order to achieve effective collaboration, is scarcely covered in MOOC platforms, which do not allow the formation of teams using criteria defined by the instructors. This paper presents an exploratory study conducted in a seven-week MOOC, comparing our group formation proposal, based on students’ activity criteria, to a baseline grouping function provided by the platform. We analyse the impact of each grouping approach over group performance, group activity, and student satisfaction. The results show initial evidence about the advantages of using the criteria-based group formation approach regarding student satisfaction and group interactions.


MOOC Collaborative Learning Automatic group formation Criteria-based group formation 



This research has been partially supported by the Junta de Castilla y León, Spain (VA082U16) and Ministerio de Economía y Competitividad, Spain (TIN2014-53199-C3-2-R). The authors thank the rest of the GSIC/EMIC research team, as well as Roberto Castellanos and the Canvas team for their valuable ideas and support. The authors also thank the Spanish network of excellence SNOLA (TIN2015-71669-REDT).


  1. 1.
    Alario-Hoyos, C., Pérez-Sanagustín, M., Delgado-Kloos, C., Parada, G., Hugo, A., Muñoz-Organero, M.: Delving into participants’ profiles and use of social tools in MOOCs. IEEE Trans. Learn. Technol. 7(3), 260–266 (2014)CrossRefGoogle Scholar
  2. 2.
    Alario-Hoyos, C., Pérez-Sanagustín, M., Delgado-Kloos, C., Parada G., H.A., Muñoz-Organero, M., Rodríguez-de-las-Heras, A.: Analysing the impact of built-in and external social tools in a MOOC on educational technologies. In: Hernández-Leo, D., Ley, T., Klamma, R., Harrer, A. (eds.) EC-TEL 2013. LNCS, vol. 8095, pp. 5–18. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-40814-4_2 CrossRefGoogle Scholar
  3. 3.
    Blom, J., Li, N., Dillenbourg, P.: MOOCs are more social than you believe. eLearning Papers 33, 1–3 (2013)Google Scholar
  4. 4.
    Brinton, C.G., Chiang, M., Jain, S., Lam, H., Liu, Z., Wong, F.M.F.: Learning about social learning in MOOCs: from statistical analysis to generative model. IEEE Trans. Learn. Technol. 7(4), 346–359 (2013)CrossRefGoogle Scholar
  5. 5.
    Cheng, H.F., Yu, B., Park, Y.H., Zhu, H.: ProjectLens: supporting project-based collaborative learning on MOOCs (2017)Google Scholar
  6. 6.
    Creswell, J.W.: Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. SAGE Publications, Thousand Oaks (2014)Google Scholar
  7. 7.
    Daniel, J.: Making sense of MOOCs: musings in a maze of myth, paradox and possibility. J. Interact. Media Educ. 2012(3), 18 (2012)CrossRefGoogle Scholar
  8. 8.
    Dillenbourg, P., Fox, A., Kirchner, C., Wirsing, M.: Massive open online courses: current state and perspectives. Technical report 1 (2014)Google Scholar
  9. 9.
    Dillenbourg, P., Tchounikine, P.: Flexibility in macro-scripts for computer-supported collaborative learning. J. Comput. Assist. Learn. 23(1), 1–13 (2007)CrossRefGoogle Scholar
  10. 10.
    Ferguson, R., Clow, D., Beale, R., Cooper, A.J., Morris, N., Bayne, S., Woodgate, A.: Moving through MOOCS: pedagogy, learning design and patterns of engagement. In: Conole, G., Klobučar, T., Rensing, C., Konert, J., Lavoué, É. (eds.) EC-TEL 2015. LNCS, vol. 9307, pp. 70–84. Springer, Cham (2015). doi: 10.1007/978-3-319-24258-3_6 CrossRefGoogle Scholar
  11. 11.
    Grünewald, F., Meinel, C., Totschnig, M., Willems, C.: Designing MOOCs for the support of multiple learning styles. In: Hernández-Leo, D., Ley, T., Klamma, R., Harrer, A. (eds.) EC-TEL 2013. LNCS, vol. 8095, pp. 371–382. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-40814-4_29 CrossRefGoogle Scholar
  12. 12.
    Inaba, A., Supnithi, T., Ikeda, M., Mizoguchi, R., Toyoda, J.: How can we form effective collaborative learning groups? In: Gauthier, G., Frasson, C., VanLehn, K. (eds.) ITS 2000. LNCS, vol. 1839, pp. 282–291. Springer, Heidelberg (2000). doi: 10.1007/3-540-45108-0_32 CrossRefGoogle Scholar
  13. 13.
    Isotani, S., Inaba, A., Ikeda, M., Mizoguchi, R.: An ontology engineering approach to the realization of theory-driven group formation. Int. J. Comput. Support. Collab. Learn. 4(4), 445–478 (2009)CrossRefGoogle Scholar
  14. 14.
    Konert, J., Burlak, D., Steinmetz, R.: The group formation problem: an algorithmic approach to learning group formation. In: Rensing, C., de Freitas, S., Ley, T., Muñoz-Merino, P.J. (eds.) EC-TEL 2014. LNCS, vol. 8719, pp. 221–234. Springer, Cham (2014). doi: 10.1007/978-3-319-11200-8_17 Google Scholar
  15. 15.
    Mackness, J., Mak, S.F.J., Williams, R.: The ideals and reality of participating in a MOOC. In: Proceedings of the 7th International Conference on Networked Learning, Aalborg, Denmark, 3–4 May 2009, vol. 10, pp. 266–274 (2010)Google Scholar
  16. 16.
    Magnisalis, I., Demetriadis, S., Karakostas, A.: Adaptive and intelligent systems for collaborative learning support: a review of the field. IEEE Trans. Learn. Technol. 4(1), 5–20 (2011)CrossRefGoogle Scholar
  17. 17.
    Manathunga, K., Hernández-Leo, D.: Has research on collaborative learning technologies addressed massiveness? A literature review. Educ. Technol. Soc. 4522, 1–14 (2015)Google Scholar
  18. 18.
    Margaryan, A., Bianco, M., Littlejohn, A.: Instructional quality of massive open online courses (MOOCs). Comput. Educ. 80, 77–83 (2015)CrossRefGoogle Scholar
  19. 19.
    Mohamad, I.B., Usman, D.: Standardization and its effects on K-means clustering algorithm. Res. J. Appl. Sci. Eng. Technol. 6(17), 3299–3303 (2013)Google Scholar
  20. 20.
    Muehlenbrock, M.: Learning group formation based on learner profile and context. In: Duval, E., Ternier, S., Assche, F.V. (eds.) Learning Objects in Context, pp. 19–25. AACE (2008)Google Scholar
  21. 21.
    Onah, D.F., Sinclair, J., Bollat, R.: Dropout rates of massive open online courses: behavioural patterns. In: Proceedings of the 6th International Conference on Education and New Learning Technologies, Barcelona, Spain, 7–9 July 2014, pp. 14–15 (2014)Google Scholar
  22. 22.
    Ortega-Arranz, A., Sanz-Martínez, L., Álvarez-Álvarez, S., Muñoz-Cristóbal, J.A., Bote-Lorenzo, M.L., Martínez-Monés, A., Dimitriadis, Y.: From low-scale to collaborative, gamified and massive-scale courses: redesigning a MOOC. In: Delgado Kloos, C., Jermann, P., Pérez-Sanagustín, M., Seaton, D.T., White, S. (eds.) EMOOCs 2017. LNCS, vol. 10254, pp. 77–87. Springer, Cham (2017). doi: 10.1007/978-3-319-59044-8_9 CrossRefGoogle Scholar
  23. 23.
    Ounnas, A.: Enhancing the automation of forming groups for education with semantics. Ph.d. thesis, University of Southampton (2010)Google Scholar
  24. 24.
    Paredes, P., Ortigosa, A., Rodriguez, P.: A method for supporting heterogeneous-group formation through heuristics and visualization. J. Univ. Comput. Sci. 16(19), 2882–2901 (2010)Google Scholar
  25. 25.
    Peffers, K., Tuunanen, T., Rothenberger, M.A., Chatterjee, S.: A design science research methodology for information systems research. J. Manag. Inf. Syst. 24(3), 45–77 (2007)CrossRefGoogle Scholar
  26. 26.
    Roschelle, J., Teasley, S.D.: The construction of shared knowledge in collaborative problem solving. In: O’Malley, C. (ed.) Computer-Supported Collaborative Learning, vol. 128, pp. 69–97. Springer, Heidelberg (1995)CrossRefGoogle Scholar
  27. 27.
    Sanz-Martínez, L., Dimitriadis, Y., Martínez-Monés, A., Alario-Hoyos, C., Bote-Lorenzo, M.L., Rubia-Avi, B., Ortega-Arranz, A.: Influential factors for managing virtual groups in massive and variable scale courses. In: 2016 International Symposium on Computers in Education (SIIE), pp. 1–4 (2016)Google Scholar
  28. 28.
    Sharples, M., Delgado-Kloos, C., Dimitriadis, Y., Garlatti, S., Specht, M.: Mobile and accessible learning for MOOCs. J. Interact. Media Educ. 4, 1–8 (2014)Google Scholar
  29. 29.
    Sinha, T.: Together we stand, together we fall, together we win: dynamic team formation in massive open online courses. In: Proceedings of the 5th International Conference on the Applications of Digital Information and Web Technologies (ICADIWT 2014), pp. 107–112 (2014)Google Scholar
  30. 30.
    Spoelstra, H., Van Rosmalen, P., Sloep, P.: Toward project-based learning and team formation in open learning environments. J. Univ. Comput. Sci. 20(1), 57–76 (2014)Google Scholar
  31. 31.
    Wen, M.: Investigating virtual teams in massive open online courses: deliberation-based virtual team formation, discussion mining and support. Ph.d. thesis proposal, Carnegie Mellon University (2015)Google Scholar
  32. 32.
    Zheng, Z., Vogelsang, T., Berlin, B., Pinkwart, N.: The impact of small learning group composition on student engagement and success in a MOOC. In: Proceedings of the 8th International Conference of Educational Data Mining, pp. 500–503 (2015)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Luisa Sanz-Martínez
    • 1
    Email author
  • Alejandra Martínez-Monés
    • 1
  • Miguel L. Bote-Lorenzo
    • 1
  • Juan A. Muñoz-Cristóbal
    • 1
  • Yannis Dimitriadis
    • 1
  1. 1.GSIC-EMIC Research GroupUniversidad de ValladolidValladolidSpain

Personalised recommendations