Estrategias basadas en análisis de redes sociales para optimizar el clima de aprendizaje en la universidad

  1. Garcia-Garcia, Fran J. 1
  2. Moctezuma-Ramírez, Evelyn E. 2
  3. Molla-Esparza, Cristian 1
  4. López-Francés, Inmaculada 1
  1. 1 Universitat de València
    info

    Universitat de València

    Valencia, España

    ROR https://ror.org/043nxc105

  2. 2 Universidad Autónoma del Estado de Morelos; Universitat de València
Journal:
Research in Education and Learning Innovation Archives. REALIA

ISSN: 2659-9031

Year of publication: 2021

Issue: 27

Pages: 33-46

Type: Article

DOI: 10.7203/REALIA.27.18960 DIALNET GOOGLE SCHOLAR lock_openOpen access editor

More publications in: Research in Education and Learning Innovation Archives. REALIA

Abstract

The aim of this study was to detect leaders among a group of university students based on their centrality scores and, from these scores, to distribute roles to help enhance learning climate. We understood that learning climate improved when the construction of networked knowledge was stimulated from the perspective of Computer-Supported Collaborative Learning. We conducted the educational experiment in a virtual environment. An online discussion forum was set up in a loo- sely structured format, and the students’ centrality scores were calculated from the social network they generated in the forum. Our findings show that student connectivity increased significantly and that several leadership styles were detected. Based on these leadership styles we designed strategies for optimizing learning climate in a self-regulated and stable way. Based on the type of centrality, we detected leaders in terms of their popularity, sociability, closeness to others, control of information flowing through the network, and influence. The novelty of this study resides in the incipient production of educational technology based on Social Network Analysis and, specifically, on the design of centrality-based strategies for optimizing climate in the university classroom.

Bibliographic References

  • Alzahrani, M. G. (2017). The effect of using online discussion forums on students’ learning. Turkish Online Journal of Educational Technology, 16(1), 164–176.
  • Amastini, F., Sari-Kaunang, C. P., Nefiratika, A., Sensuse, D. I., y Lusa, S. (2020). Collaborative Learning in Virtual Learning Environment using Social Network Analysis: Case study Universitas Terbuka. 2020 7th International Conference on Electrical Engineering, Computer Sciences, and Informatics (EECSI), 262–269. https://doi.org/10.23919/
  • Bandura, A. (1986). Social Foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice-Hall.
  • Bleich, M. R. (2020). The Discussion Board in Online Learning: Leadership Development Opportunities. The Journal of Continuing Education in Nursing, 51(12), 541–543. https:// doi.org/10.3928/00220124-20201113-03
  • Brandes, U. (2001). A faster algorithm for betweenness centrality. The Journal of Mathematical Sociology, 25(2), 163–177. https://doi.org/10.1080/0022250X.2001.9990249
  • Chen, L. T., y Liu, L. (2020). Social Presence in Multidimensional Online Discussion: The Roles of Group Size and Requirements for Discussions. Computers in the Schools, 37 (2), 116–140. https://doi.org/10.1080/07380569.2020.1756648
  • Dommett, E. J. (2018). Understanding student use of Twitter and online forums in higher education. Education and Information Technologies, 24, 325–343. https://dx.doi.org/ 10.1007/s10639-018-9776-5
  • Durá-Martínez, E. (2010). Una experiencia docente: la introducción del foro en la asignatura de Informática II en Biblioteconomía y Documentación. @tic revista d’innovació educativa, 4, 72–76. https://doi.org/10.7203/attic.4.183
  • Fabbri, M. (2018). Forums as a tool for negotiating knowledge in Higher Education. Research on Education and Media, 10(1), 9–19. https://doi.org/http://dx.doi.org/10.1515/rem-2018-0003
  • Freeman, L. C. (1977). A Set of Measures of Centrality Based on Betweenness. Sociometry, 40(1), 35–41. https://doi.org/10.2307/3033543
  • Freeman, L. C. (1979). Centrality in networks: I. Conceptual clarification. Social Networks, 1, 215–239. https://doi.org/10.1016/0378-8733(78)90021-7
  • Gargallo-López, B. (2017). Enseñanza centrada en el aprendizaje y diseño por competencias en la universidad. Fundamentación, procedimientos y evidencias de aplicación e investigación. Valencia, España: Tirant lo Blanc.
  • Hadwin, A., Järvelä, S., y Miller, M. (2018). Self-regulation, co-regulation, and shared regulation in collaborative learning environments. En D.-H. Schunk y J.-A. Greene (Eds.), Educational psychology handbook series. Handbook of self-regulation of learning and performance (pp. 83–106). Nueva York, NY: Routledge/Taylor & Francis.
  • Hammond, M. (2005). A review of recent papers on online discussion in teaching and learning in higher education. Journal of Asynchronous Learning Networks, 9(3), 9–23. http://dx.doi.org/10.24059/olj.v9i3.1782
  • Hwang, G. J., Wang, S. Y., y Lai, C. L. (2021). Effects of a social regulation-based online learning approach on students’ learning achievements and behaviors in mathematics. Computers and Education, 160, 1–19. https://doi.org/10.1016/j.compedu.2020.104031
  • Jan, S. K. (2018). Identifying online communities of inquiry in higher education using social network analysis. Research in Learning Technology, 26, 1–13. https://doi.org/10.25304/ rlt.v26.2064
  • Jan, S. K., y Vlachopoulos, P. (2019). Social Network Analysis: A Framework for Identifying Communities in Higher Education Online Learning. Technology, Knowledge and Learning, 24(4), 621–639. https://doi.org/10.1007/s10758-018-9375-y
  • Järvelä, S., Järvenoja, H., Malmberg, J., y Hadwin, A. F. (2013). Exploring Socially Shared Regulation in the Context of Collaboration. Journal of Cognitive Education and Psychology, 12, 267–286.
  • Lucas, M., Gunawardena, C., y Moreira, A. (2014). Assessing social construction of knowledge online: A critique of the interaction analysis model. Computers in Human Behavior, 30, 574–582. https://doi.org/10.1016/j.chb.2013.07.050
  • Mohammed, M. (2005). A review of recent papers on online discussion in teaching and learning in higher education. Journal of Asynchronous Learning Networks, 9(3), 9–23. https://doi.org/10.24059/olj.v9i3.1782
  • Onyema, E. M., Deborah, E. C., Alsayed, A. O., Naveed, Q. N., y Sanober, S. (2019). Online Discussion Forum as a Tool for Interactive Learning and Communication. International Journal of Recent Technology and Engineering, 8(4), 4852–4859. https://doi.org/10.35940/ ijrte.D8062.118419
  • Sabidussi, G. (1966). The centrality index of a graph. Psychometrika, 31(4), 581–603. https:// doi.org/10.1007/BF02289527
  • Sachdeva, C., y Gilbert, S. J. (2020). Excessive use of reminders: Metacognition and effort- minimisation in cognitive offloading. Consciousness and Cognition, 85, 1–14. https:// doi.org/10.1016/j.concog.2020.103024
  • Silva, L. F. C. D., Barbosa, M. W., y Gomes, R. R. (2019). Measuring Participation in Distance Education Online Discussion Forums Using Social Network Analysis. Journal of the Association for Information Science and Technology, 70(2), 140–150. https://doi.org/ 10.1002/asi.24080
  • Sindhgatta, R., Marvaniya, S., Dhamecha, T. I., y Sengupta, B. (2017). Inferring frequently asked questions from student question answering forums. Proceedings of the 10th International Conference on Educational Data Mining, 2017 , 256–261.
  • Sun, J., y Tang, J. (2011). A survey of models and algorithms for social influence analysis. Social Network Data Analytics, 177–214. https://doi.org/10.1007/978-1-4419-8462-3_7
  • van Heijst, H., de Jong, F.-P.-C.-M., van Aalst, J., de Hoog, N., y Kirschner, P. A. (2019). Socio-cognitive openness in online knowledge building discourse: does openness keep conversations going? International Journal of Computer-Supported Collaborative Learning, 14, 165–184. https://doi.org/10.1007/s11412-019-09303-4
  • Wang, P.-Y., y Yang, H.-C. (2012). Using collaborative filtering to support college students’ use of online forum for English learning. Computers and Education, 59(2), 628–637. https://doi.org/10.1016/j.compedu.2012.02.007
  • Wang, Z., Zhao, R., Xu, Y., Li, X., Zuo, M., y Ye, J. (2019). Interactive Discourse Analysis Based on the Forum Text Mining in Cloud Classroom. International Journal of Information and Education Technology, 9(3), 178–183. https://doi.org/10.18178/ijiet.2019.9.3.1195
  • Zhao, X., Jiang, Z., y Gray, J. (2019). Text classification and topic modeling for online discussion forums: An empirical study from the systems modeling community. En A. Fiori (Ed.), Trends and Applications of Text Summarization Techniques (pp. 151–186).
  • Zou, W., Hu, X., Pan, Z., Li, C., Cai, Y., y Liu, M. (2021). Exploring the relationship between social presence and learners’ prestige in MOOC discussion forums using automated content analysis and social network analysis. Computers in Human Behavior, 115, 1–17. https://doi.org/10.1016/j.chb.2020.106582
Data source: Dialnet