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Fostering Collective Intelligence Education

  • Jaime MezaEmail author
  • Josep M. Monguet
  • Francisca Grimón
  • Alex Trejo
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 160)

Abstract

New educational models are necessary to update learning environments to the digitally shared communication and information reality. Collective intelligence is an emerging field that already has a significant impact in many areas and will have great implications in education, not only from the side of new methodologies but also as a challenge for education, currently more focused on the individual than in the collective. This paper proposes an approach to a collective intelligence model of teaching using Internet to combine two strategies: idea management and real time assessment in the class. A digital tool named Fabricius has been created supporting these two elements to foster the collaboration, empowerment and engagement of students in the learning process. As a result of the research we propose a list of KPI trying to measure individual and collective performance in a course. We are conscious that this is just a first approach to define which aspects of a class following a course can be qualified and quantified. We finally discuss the need to connect research and innovation in this field.

Keywords

Collective intelligence education Learning patterns Teaching KPI 

References

  1. 1.
    Gilliver, R.S., Randall, B., Pok, Y.M.: Learning in cyberspace: Shaping the future. J. Comput. Assist. Learn. 14, 212–222 (1998)CrossRefGoogle Scholar
  2. 2.
    Li, H., Li, Z.: Emergence of collective intelligence in distance education system. In: 2010 2nd International Conference on Education Technology and Computer, vol. 1, pp. V1–333–V1–337 (2010)Google Scholar
  3. 3.
    Cornu, B.: Collective intelligence and capacity building. In: van Weert, T. (ed.) Education and the Knowledge Society SE - 3, vol. 161, pp. 27–34. Springer, New York (2005)CrossRefGoogle Scholar
  4. 4.
    Lévy, P.: From social computing to reflexive collective intelligence: the IEML research program. Inf. Sci. (Ny) 180(1), 71–94 (2010)CrossRefGoogle Scholar
  5. 5.
    Lévy, P.: Toward a self-referential collective intelligence some philosophical background of the IEML research program. In: Nguyen, N.T., Kowalczyk, R., Chen, S.-M. (eds.) ICCCI 2009. LNCS, vol. 5796, pp. 22–35. Springer, Heidelberg (2009)Google Scholar
  6. 6.
    Bonabeau, E.: Decisions 2.0: The power of collective intelligence. MIT Sloan Manage. Rev. 50(2), 45–52 (2009). no. 50211, MassachusettsGoogle Scholar
  7. 7.
    Gónzalez, F., Silvana, V.: Procesos de inteligencia colectiva y colaborativa en el marco de tecnologías web 2. 0 : , problemas y aplicaciones. Fac. Psicol. - UBA / Secr. Investig. / Anu. Investig., vol. XIX, pp. 253–270 (2012)Google Scholar
  8. 8.
    Tsai, W., Li, W., Elston, J.: Collaborative learning using wiki web sites for computer science undergraduate education: a case study. IEEE Trans. Educ. 54(1), 114–124 (2011)CrossRefGoogle Scholar
  9. 9.
    Petreski, H., Tsekeridou, S., Giannaka, E., Prasad, N.R., Prasad, R., Tan, Z.: Technology enabled social learning: A review. Int. J. Knowl. Learn. 7(3/4), 253–270 (2011)CrossRefGoogle Scholar
  10. 10.
    Thompson, C., Gray, K., Kim, H.: How social are social media technologies (SMTs)? A linguistic analysis of university students’ experiences of using SMTs for learning. Internet High. Educ. 21, 31–40 (2014)CrossRefGoogle Scholar
  11. 11.
    Paus-Hasebrink, I., Wijnen, C.W., Jadin, T.: Opportunities of web 2.0: potentials of learning. Int. J. Media Cult. Polit. 6(1), 45–62 (2010)CrossRefGoogle Scholar
  12. 12.
    Engelbart, D.C.: Toward augmenting the human intellect and boosting our collective IQ. Commun. ACM 38(8), 30–32 (1995)CrossRefGoogle Scholar
  13. 13.
    Woolley, A.W., Chabris, C.F., Pentland, A., Hashmi, N., Malone, T.W.: Evidence for a collective intelligence factor in the performance of human groups. Science 330(6004), 686–688 (2010)CrossRefGoogle Scholar
  14. 14.
    Barlow, J.B., Dennis, A.R.: Not as smart as we think : a study of collective intelligence in virtual groups. In: 2014 Collective Intelligence, pp. 1–5 (2014)Google Scholar
  15. 15.
    Pérez-Gallardo, Y., Alor-Hernández, G., Cortes-Robles, G., Rodríguez-González, A.: Collective intelligence as mechanism of medical diagnosis: the iPixel approach. Expert Syst. Appl. 40, 2726–2737 (2013)CrossRefGoogle Scholar
  16. 16.
    Ilon, L.: How collective intelligence redefines education. In: Altmann, J., Baumöl, U., Krämer, B.J. (eds.) Advances in Collective Intelligence 2011. AISC, vol. 113, pp. 91–102. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  17. 17.
    Capterra: Best Ideas Management Software. www.capterra.com/idea-management-software/
  18. 18.
  19. 19.
    Veilleroy, Y., Hoogstoel, F., Lancieri, L.: QLIM – a tool to support collective intelligence. In: 2012 International Conference on Privacy, Security Risk Trust (PASSAT), and 2012 International Conference on Social Computing, p. 322–327 (2010)Google Scholar
  20. 20.
    Martí, T., Monguet, J.M., Trejo, A., Escarrabill, J., Beitia, C.C.I.: Collective health policy making in the Catalan Health System: applying Health Consensus to priority setting and policy monitoring. In: 2014 Collective Intelligence, pp. 1–5 (2014)Google Scholar
  21. 21.
    Chounta, I.-A., Avouris, N.: It’s all about time: towards the real-time evaluation of collaborative activities. In: 2014 IEEE 14th International Conference on Advanced Learning Technologies, pp. 283–285 (2014)Google Scholar
  22. 22.
    Mathioudakis, G., Leonidis, A.: Real-time teacher assistance in technologically-augmented smart classrooms. Int. J. Adv. Life Sci. 6(1), 62–73 (2014)Google Scholar
  23. 23.
    Monguet, J.M., Meza, J.: Guess the score, fostering collective intelligence in the class. In: Vincenti, G., Bucciero, A., Vaz de Carvalho, C. (eds.) eLEOT 2014. LNICST, vol. 138, pp. 116–122. Springer, Heidelberg (2014)Google Scholar
  24. 24.
    Fahlbusch, E., Vischer, L., Lochman, J.M., Mbiti, J.S., Pelikan, J.: Llullian method. In: The Encyclopedia of Christianity, pp. 331–332 (2003)Google Scholar
  25. 25.
    Harvey, N., Holmes, C.A.: Nominal group technique: An effective method for obtaining group consensus. Int. J. Nurs. Pract. 18(2), 188–194 (2012)CrossRefGoogle Scholar

Copyright information

© Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2016

Authors and Affiliations

  • Jaime Meza
    • 1
    Email author
  • Josep M. Monguet
    • 1
  • Francisca Grimón
    • 2
  • Alex Trejo
    • 3
  1. 1.Universitat Politècnica de CatalunyaBarcelonaSpain
  2. 2.Universidad de CaraboboValenciaVenezuela
  3. 3.OnsanityBarcelonaSpain

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