Educación de la inteligencia colectiva, un desafío para la universidad ecuatoriana

Formulation of knowledge strategies in Cuban management consultancy: approach to distinctive competences

  • Jaime Alcides Meza Hormaza Universitat Politécnica de Catalunya
  • Oswaldo Ortiz Aldean Universidad de las Fuerzas Armadas - ESPE
  • Karina Mendoza Bravo Universidad Técnica de Manabí

Resumen

La educación mantiene continuamente desafíos evidenciados a través de su evolución, desde sus orígenes. El proceso de aprender en la educación debe ser concebido en un contexto descentralizado del día a día y de colaboración, además, la rápida y profunda transformación tecnológica llevada a cabo a finales del siglo XX y comienzos de XXl, especialmente en las Tecnologías de la Información y las Comunicaciones (TIC), enfrentan a las universidades a una mayor presión para demostrar la efectividad de sus esfuerzos educativos, mejorando el entorno de enseñanza- aprendizaje. La inteligencia colectiva (IC) es un campo emergente que ya tiene un impacto significativo en muchas áreas y tendrá grandes implicaciones en la educación, no sólo desde el lado de las nuevas metodologías, sino también como un reto para la educación, que actualmente está más centrado en el individuo que en el colectivo. Este artículo propone un modelo de Educación de la Inteligencia Colectiva con TIC, combinando dos estrategias: la gestión de ideas y la evaluación en tiempo real en la clase. Se ha creado una plataforma colaborativa llamada FABRICIUS que apoya estos dos elementos para fomentar la colaboración, el empoderamiento y el compromiso de los estudiantes en el proceso de aprendizaje. La investigación propone una lista de métricas para medir el rendimiento individual y colectivo en un curso. Los resultados de los hallazgos en 11 ensayos en Europa e Hispanoamérica evidencian la eficiencia del modelo. Finalmente se discute la necesidad de conectar la gestión universitaria y la innovación en este campo.


Abstrac


Education continually maintains challenges evidenced through its evolution, from its origins. The process of learning in education must be conceived in a decentralized context of day to day and collaboration, in addition, the rapid and profound technological transformation carried out at the end of the 20th century and the beginning of the 20th century, especially in Information Technologies and Communications (ICT), confronts universities with greater pressure to demonstrate the effectiveness of their educational efforts, improving the teaching-learning environment. Collective intelligence (CI) is an emerging field that already has a significant impact in many areas and will have great implications for education, not only from the side of new methodologies, but also as a challenge for education, which is currently more focused on the individual that in the collective. This article proposes a model of Collective Intelligence Education with ICT, combining two strategies: the management of ideas and the evaluation in real time in the class. A collaborative platform called FABRICIUS has been created that supports these two elements to foster collaboration, empowerment and student engagement in the learning process. The research proposes a list of metrics to measure individual and collective performance in a course. The results of the findings in 11 trials in Europe and Latin America show the efficiency of the model. Finally, the need to connect university management and innovation in this field is discussed.

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Citas

Alberola, J. M., del Val, E., Sanchez-Anguix, V., & Julian, V. (2013, September). Simulating a collective intelligence approach to student team formation. In International Conference on Hybrid Artificial Intelligence Systems (pp. 161-170). Springer, Berlin, Heidelberg.

Anderson, T., Shattuck, J., & Brown, A. (2012). Design-Based Research: A Decade of Progress in Education Research? Educational Researcher, 41(1), 16–25. http://doi.org/10.3102/0013189X11428813

Aulinger, A., & Miller, L. (2014). Collective Intelligence versus Team Intelligence. In Collective Intelligence Conference, Massachusetts Institute of Technology (pp. 1–4).

Awal, G. K., & Bharadwaj, K. K. (2014). Team formation in social networks based on collective intelligence – an evolutionary approach. Applied Intelligence, 41(2), 627–648. http://doi.org/10.1007/s10489-014-0528-y

Barab, S. (2014). Design-Based Research: A Methodological Toolkit for Engineering Change. In Handbook of the Learning Sciences (pp. 151–170). The Cambridge Handbook of the Learning Sciences, Second Edition. http://doi.org/10.1017/CBO9781139519526.011

Barlow, J. B., & Dennis, A. R. (2014). Not as Smart as We Think: A Study of Collective Intelligence in Virtual Groups. In Collective Intelligence 2014 (pp. 1–5).

Betoret. (2013). Tema 5: la enseñanza y el aprendizaje en la situación educativa, 1–11.

Cole, R., Purao, S., Rossi, M., & Sein, M. K. (2005). Being Proactive: Where Action Research meets Design Research. In ICIS 2005 Proceedings. Retrieved from http://aisel.aisnet.org/icis2005/27

Conole, G. (2007). Describing learning activities. In Rethinking Pedagogy for a Digital Age (pp. 81–91).

Design-Based Researcher. (2003). Design-based research: An emerging paradigm for educational inquiry. Educational Research, 32(1), 5–8. http://doi.org/10.3102/0013189X032001005

Doug Engelbart Insittute. (n.d.). Dynamic Knowledge Repositories. Retrieved February 16, 2014, from http://www.dougengelbart.org/about/DKRs.html

Du, H., Hao, J., Kwok, R., Wagner, C. (2010). Can a Lean Medium Enhance Large-Group Communication? Examining the Impact of Interactive Mobile Learning. American Society for Information Science and Technology, 61(10), 2122–2137.

Easterday, M. W., Lewis, D. R., & Gerber, E. M. (2014). Design-Based Research Process: Problems, Phases, and Applications Problems arising from the ill-definition of DBR.
Learning and Become in Practice (ICLS 2014), 322. Retrieved from www.isls.org/icls2014

Engel, D., Woolley, A. W., Aggarwal, I., Chabris, C. F., Takahashi, M., Nemoto, K., Malone, T. W. (2015). Collective Intelligence in Computer-Mediated Collaboration Emerges in Different Contexts and Cultures. Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems - CHI ’15, 3769–3778. http://doi.org/10.1145/2702123.2702259

Engelbart, D. C. (1995). Toward augmenting the human intellect and boosting our collective IQ. Communications of the ACM, 38(8), 30–32.

Gibelli, T. (2014). La investigación basada en diseño para el estudio de una innovación en educación superior que promueve la autorregulación del aprendizaje utilizando TIC La investigación basada en diseño para el estudio de una innovación en educación superior que promueve. Congreso Iberoamericano de Ciencia, Tecnología, Innovación Y Educación, 1–16.

Glenn, J. C. (2009). The Millennium Project - Collective Intelligence Systems for Science and Technological Convergences to Benefit Society. Futura World Future Review, 4(Fall), 1–15. http://doi.org/10.1016/j.techfore.2013.10.010

Gordon, T. J. (2009). The real-Time Delphi Method. Futures Research Methodology, 1–21.

Green, B. E. N. (2015). Testing and Quantifying Collective Intelligence. In Collective Intelligence Conference (pp. 1–4).

Gregg, D. (2009). Developing a collective intelligence application for special education. Decision Support Systems, 47(4), 455–465. http://doi.org/10.1016/j.dss.2009.04.012

Hernández-Chan, G., Rodríguez-González, A., Alor-Hernández, G., Gómez-Berbís, J. M., Mayer-Pujadas, M. A., & Posada-Gómez, R. (2012). Knowledge Acquisition for Medical Diagnosis Using Collective Intelligence. Journal of Medical Systems, 36, 1–5. http://doi.org/10.1007/s10916-012-9886-3

Ilon, L. (2012). How collective intelligence redefines education. (J. Altmann, U. Baumöl, & B. J. Krämer, Eds.) Advances in Intelligent and Soft Computing (Vol. 113). Berlin,

Heidelberg: Springer Berlin Heidelberg. http://doi.org/10.1007/978-3-642-25321-8

Johnson, D.W., Johnson, R.T., Smith, K. (2007). The state of cooperative learning in postsecondary and professional settings. Educational Psychology Review, 19(1), 15–29.

Johnson, D.W., Johnson, R. T. (2009). An educational psychology success story: Social interdependence theory and cooperative learning. Educational Researcher, 38(5), 365–379.

Young, K., Martin, M., & Yates, T. (2014). Real-time engagement in a learning environment. Nternational Journal of Instructional Technology and Distance Learning Return, 11(10), 55-62.

Levy, P. (2015). Collective Intelligence for Educators. Educational Philosophy and Theory, 47(8), 749–754. http://doi.org/10.1080/00131857.2015.1053734

Lévy, P. (2009). Toward a Self-referential Collective Intelligence Some Philosophical Background of the IEML Research Program. In First International Conference, ICCCI 2009 (Vol. 5796, pp. 22–35). Wrocław, Poland: Lecture Notes in Artificial Intelligence.

Lykourentzou, I., Vergados, D. J., & Loumos, V. (2009). Collective intelligence system engineering. Proceedings of the International Conference on Management of Emergent Digital EcoSystems - MEDES ’09, 134. http://doi.org/10.1145/1643823.1643848

Maffioli, F., Augusti, G. (2003). Tuning engineering education into the european higher education orchestra. European Journal of Engineering Education, 28(3), 251–273.

Malone, T. W., Laubacher, R., & Dellarocas, C. (2010). The Collective Intelligence Genome THE LEADING. MIT Sloan Management Review, 51(51303), 21–31. http://doi.org/10.1109/EMR.2010.5559142

McGrath, J. E. (1983). A Typology of Task. In D. A. Josephson (Ed.), Groups: Interaction and Performance (pp. 61, 66). Prentice - Hall, Inc.; Englewood Cliffs, New Jersey.

McGrath, J. E., Arrow, H., & Berdahl, J. L. (2000). The Study of Groups: Past, Present, and Future. Personality and Social Psychology Review, 4(1), 95–105. http://doi.org/10.1207/S15327957PSPR0401_8

Meza, J., Vaca, L., Simó, E., Monguet, J.M., (2017). Toward a collective intelligence recommender system for education. In EDULEARN17 proceedings: 9th International Conference on Education and New Learning Technologies: Barcelona, Spain, 3-5 July, 2017 (pp. 5946-5955). International Association of Technology, Education and Development (IATED).

Meza, J., Ortiz, O., Vaca-Cardenas, M., Roman, S., & Monguet, J. M. (2017). CIR: Fostering Collective Creativity. In G. Vincenti, A. Bucciero, M. Helfert, & M. Glowatz (Eds.), E-Learning, E-Education, and Online Training: Third International Conference, eLEOT 2016, Dublin, Ireland, August 31 -- September 2, 2016, Revised Selected Papers (pp. 145–152). Cham: Springer International Publishing. http://doi.org/10.1007/978-3-319-49625-2_18

Meza, J., Ortiz, O., Simo, E., Monguet, J.M., (2017). Measuring the collective intelligence education index. In EDULEARN17 proceedings: 9th International Conference on Education and New Learning Technologies: Barcelona, Spain, 3-5 July, 2017 (pp. 3066–3074). International Association of Technology, Education and Development (IATED). http://doi.org/10.21125/edulearn.2017.1647

Meza, J. (2017). Modelo de educación de la inteligencia colectiva. Universitat politécnica de catalunya.

Meza, J., Monguet, J. M., Grimón, F., & Trejo, A. (2016). Fostering Collective Intelligence Education. In G. Vincenti, A. Bucciero, & C. de Carvalho (Eds.), E-Learning, E-Education, and Online Training: Second International Conference, eLEOT 2015, Novedrate, Italy, September 16-18, 2015, Revised Selected Papers (pp. 165–172). Cham: Springer International Publishing. http://doi.org/10.1007/978-3-319-28883-3_21

MIT Center For Collective Intelligence. (2006). MIT Center for Collective Intelligence. Retrieved March 10, 2014, from http://cci.mit.edu

Molina, M., Castro, E., Molina, J. L., & Castro, E. (2011). Un acercamiento a la investigación de diseño a través de los experimentos de enseñanza. Ensenanza de Las Ciencias, 29(1), 75–88.

Monguet, J. M., & Meza, J. (2014). Guess the Score, fostering collective intelligence in the class. In E-Learning, E-Education, and Online Training (pp. 116–122). Springer International Publishing. http://doi.org/10.1007/978-3-319-13293-8_14

Ortiz, O., Meza, J., Simo, E., J. M. (2017). Fostering the classroom attention using collective intelligence education tools. In edulearn17 Proceedings (pp. 3182–3188). IATED. http://doi.org/10.21125/edulearn.2017.1675

O’reilly, T. (2005). Design Patterns and Business Models for the Next Generation of Software. Retrieved May 30, 2014, from http://www.oreilly.com/pub/a/web2/archive/what-is-web-20.html

Pajares, S., Torreño, A., & Esparcia, S. (2011). A Novel Teaching-Learning Strategy for Teamwork based on Agreement Technologies. In Design and Evaluation of Digital Content for Education (DEDCE) 2011 (pp. 21–30).

Pérez-Gallardo, Y., Alor-Hernández, G., Cortes-Robles, G., & Rodríguez-González, A. (2013). Collective intelligence as mechanism of medical diagnosis. Expert Systems with Applications, 40(7), 2726–2737.

Pourhosein Gilakjani, A., Mei Leong, L., & Nizam Ismail, H. (2013). Teachers’ Use of Technology and Constructivism. International Journal of Modern Education and Computer Science, 5(May), 49–63. http://doi.org/10.5815/ijmecs.2013.04.07

Rahimi, E., Berg, J. Van Den, & Veen, W. (2014). A Pedagogy-driven Framework for Integrating Web 2.0 tools into Educational Practices and Building Personal Learning Environments. Journal of Literacy and Tecnology, 15(2), 54–79.

Szuba, T. (2001). A formal definition of the phenomenon of collective intelligence and its IQ measure. Future Generation Computer System, 17, 489–500.

Tarricone, P., Luca, J. (2002). Employees, teamwork and social interdependence–a formula for successful business? Team Performance Management, 8(3/4), 54–59.

UNESCO. (1998). Declaración Mundial sobre la Educación Superior para el Siglo XXI: Visión y Acción. Conferencia Mundial de la Educación Superior. Retrieved from http://www.unesco.org/ education/educprog/wche/declaration_spa.htm

Vries, M. F. R. K. De. (1999). High-performance teams: Lessons from the pygmies. Organizational Dynamics, 27(3), 66–77. http://doi.org/http://dx.doi.org/10.1016/S0090-2616 (99)90022-0

Woolley, A. W., Chabris, C. F., Pentland, A., Hashmi, N., & Malone, T. W. (2010). Evidence for a collective intelligence factor in the performance of human groups. Science (New York, N.Y.), 330(6004), 686–8. http://doi.org/10.1126/science.1193147

Zheng, L. (2015). A Systematic Literature Review of Design-based Research from 2004 to 2013. Journal of Computers in Education, 2(4), 399–420. http://doi.org/10.1007/s40692-015-0036-z
Publicado
2018-08-20
Sección
Cooperación interinstitucional y gestión universitaria