Abstract
Proliferation of social networks and its use in education and higher learning have become an interesting topic. In order to accommodate diverse student cohorts in the age of massification of education market, this approach has become attractive. Recent advances in learning analytics and data visualization further proved to be useful in encouraging collaborative learning. On the other hand, information of social networks can be too complex to visualize often overloading users with too much possibly unwanted information. The question is what to show and what not to show when we visualize social relationships of users. In this paper, we propose a new visualization model called learning space and develop a method for visualizing learning activities on social network in a 3D virtual learning space. We evaluate the method using questionnaires to see whether visualization of social relations of learning will improve the learning in the following ways or not: make it more fun, make it easier, motivate more. The result shows that our method of visualization of learning activities in social network made learning more fun and easier. The result also shows that it helps student engage and motivate on the subjects.
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References
Song, I., Vong, J.: Mobile collaborative experiential learning (MCEL): personalized formative assessment. In: 2013 International Conference on IT Convergence and Security (ICITCS), pp. 1–4. IEEE (2013)
Burkhard, R.A., Meier, M.: Tube map visualization: evaluation of a novel knowledge visualization application for the transfer of knowledge in long-term projects. J UCS 11(4), 473–494 (2005)
Heer, J., Boyd, D.: Vizster: visualizing online social networks. In: 2005 IEEE Symposium on Information Visualization, INFOVIS 2005, pp. 32–39. IEEE (2005)
Martınez, A., Dimitriadis, Y., Rubia, B., Gómez, E., De La Fuente, P.: Combining qualitative evaluation and social network analysis for the study of classroom social interactions. Comput. Educ. 41(4), 353–368 (2003)
Fournier, H., Kop, R., Sitlia, H.: The value of learning analytics to networked learning on a personal learning environment (2011)
Avouris, N., Fiotakis, G., Kahrimanis, G., Margaritis, M., Komis, V.: Beyond logging of fingertip actions: analysis of collaborative learning using multiple sources of data. J. Interact. Learn. Res. 18, 231–250 (2007)
Marty, J.-C., Heraud, J.-M., Carron, T., France, L.: Matching the performed activity on an educational platform with a recommended pedagogical scenario: a multi-source approach. J. Interact. Learn. Res. 18(2), 267–283 (2007)
Barre, V., El-Kechaï, H., Choquet, C.: Re-engineering of collaborative e-learning systems: evaluation of system, collaboration and acquired knowledge qualities. In: 12th Artificial Intelligence in Education AIED, pp. 9–16 (2005)
Mazza, R., Milani, C.: Gismo: a graphical interactive student monitoring tool for course management systems. In: International Conference on Technology Enhanced Learning, Milan, pp. 1–8 (2004)
Song, I., Bhati, A.S.: Automated tutoring system: mobile collaborative experiential learning (MCEL). In: 2014 IEEE 14th International Conference on Advanced Learning Technologies (ICALT), pp. 318–320. IEEE (2014)
Brady, K.P., Holcomb, L.B., Smith, B.V.: The use of alternative social networking sites in higher educational settings: a case study of the e-learning benefits of ning in education. J. Interact. Online Learn. 9(2), 151–170 (2010)
Santos, J.L., Govaerts, S., Verbert, K., Duval, E.: Goal-oriented visualizations of activity tracking: a case study with engineering students. In: Proceedings of the 2nd International Conference on Learning Analytics and Knowledge, pp. 143–152. ACM (2012)
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Ho, T.H.Y., Nguyen, T.T., Song, I. (2016). Visualizing Learning Activities in Social Network. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49381-6_10
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DOI: https://doi.org/10.1007/978-3-662-49381-6_10
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