CollabTech 2016: Collaboration Technologies and Social Computing pp 174-189 | Cite as
Social Presence Visualizer: Development of the Collaboration Facilitation Module on CSCL
Abstract
This study aims to develop and evaluate a visualization function of CSCL that is based on social presence. This function automatically categorizes the postings from learners and visually presents social interaction following a social presence indicator. Furthermore, this function seems to enhance social presence and encourage learning behavior, such as active discussion. In order to investigate the validity of auto-categorization, the inter-rater agreement rate and the ability to predict the quality of the discussion were analyzed and compared to the human-categorized data. The results demonstrated that there are several social presence indicators that have high and low inter-rater agreement, but the categorization of the function developed in this study had more prediction power than the human-conducted categorization.
Keywords
Community of inquiry Social interaction Social presence Computer-Supported Collaborative Learning (CSCL) VisualizationNotes
Acknowledgement
This research is financially supported by Grant-in-Aids for Young Scientist A (25702008) and for Scientific Research (B) (16H03080)
References
- 1.Nishimori, T., Kato, H., Mochizuki, T., Yaegashi, K., Hisamatsu, S., Ozawa, S.: Development and trial of project-based learning support system in higher education. J. Jpn. Soc. Educ. Technol. 29(3), 289–297 (2005)Google Scholar
- 2.Scardamalia, M., Bereiter, C.: Technologies for knowledge-building discourse. Commun. ACM 36(5), 37–41 (1993)CrossRefGoogle Scholar
- 3.Garrison, D.R., Anderson, T.: E-learning in the 21st Century: A Framework for Research and Practice. Routledge Falmer, London (2003)CrossRefGoogle Scholar
- 4.Shea, P., Bidjerano, T.: Community of inquiry as a theoretical framework to faster epistemic engagement and cognitive presence in online education. Comput. Educ. 52(3), 543–553 (2009)CrossRefGoogle Scholar
- 5.Garrison, D.R., Anderson, T., Archer, W.: Critical inquiry in a text-based environment: computer conferencing in higher education. Internet High. Educ. 2(2–3), 87–105 (2000)Google Scholar
- 6.Gunawardena, C.N., Zittle, F.J.: Social presence as a predictor of satisfaction within a computer-mediated conferencing environment. Am. J. Distance Educ. 11(3), 8–26 (1997)CrossRefGoogle Scholar
- 7.Shea, P., Hayes, S., Vickers, J., Gozza-Cohen, M., Uzuner, S., Mehta, R., Valchova, A., Rangan, P.: A re-examination of the community of inquiry framework: social network and content analysis. Internet High. Educ. 13, 10–21 (2010)CrossRefGoogle Scholar
- 8.Akyol, Z., Garrison, D.R.: Assessing metacognition in an online community of inquiry. Internet High. Educ. 14, 183–190 (2012)CrossRefGoogle Scholar
- 9.Goda, Y., Yamada, M.: Application of CoI to design CSCL for EFL online asynchronous discussion. In: Akyol, Z., Garrison, D.R. (eds.) Educational Community of Inquiry: Theoretical Framework, Research and Practice, pp. 295–316. IGI Global (2012)Google Scholar
- 10.Yamada, M.: The role of social presence in learner-centered communicative language learning using synchronous computer-mediated communication: experimental study. Comp. Educ. 52, 820–833 (2009)CrossRefGoogle Scholar
- 11.Yamada, M., Goda, Y.: Application of social presence principles to CSCL design for quality interactions. In: Jia, J.: (ed.) Educational Stages and Interactive Learning: From Kindergarten to Workplace Training, pp. 31–48. IGI Global (2012)Google Scholar
- 12.Yamada, M.: Development and Evaluation of CSCL Based on Social Presence. In: Sanchez, J., Zhang, K. (eds.) Proceedings of the World Conference on E-learning in Corporate, Government, Healthcare, and Higher Education, pp. 2304–2309. Association for the Advancement of Computing in Education (2010). http://www.editlib.org/p/35889
- 13.Short, J., Williams, E., Christie, B.: The Social Psychology of Telecommunications. Wiley, London (1976)Google Scholar
- 14.Phielix, C., Prins, F.J., Kirschner, P.A.: Group awareness of social and cognitive behavior in a CSCL environment. In: ICLS 2010 Proceedings of the 9th International Conference of the Learning Sciences, vol. 1, pp. 230–237 (2010)Google Scholar
- 15.Janssen, J., Erkens, G., Kanselaar, G.: Visualization of agreement and discussion processes during computer-supported collaborative learning. Comput. Hum. Behav. 23, 1105–1125 (2007)CrossRefGoogle Scholar
- 16.Mochizuki, T., Kato, H., Yaegashi, K., Nishimori, T., Nagamori, Y., Fujita, S.: ProBoPortable: does the cellular phone software promote emergent division of labor in project-based learning? In: CSCL 2007 Proceedings in the 8th International Conference on Computer-Supported Collaborative Learning, pp. 516–518 (2007)Google Scholar
- 17.Yamada, M., Goda, Y., Matsukawa, H., Hata, K., Yasunami, S.: A computer-supported collaborative learning design for quality interaction. IEEE Multimedia 23, 48–59 (2016)CrossRefGoogle Scholar
- 18.Hoppe, U.H., Gaßner, K.: Integrating collaborative concept mapping tools with group memory and retrieval functions. In: CSCL 2002 Proceedings of the Conference on Computer Support for Collaborative Learning, pp. 716–725 (2002)Google Scholar
- 19.Manning, C.D., Surdeanu, M., Bauer, J., Finkel, J., Bethard, S.J., McClosky, D.: The stanford CoreNLP natural language processing toolkit. In: Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pp. 55–60 (2014)Google Scholar
- 20.Miller, G.A.: WordNet: a lexical database for English. Commun. ACM 38(11), 39–41 (1995)CrossRefGoogle Scholar
- 21.Fellbaum, C.: WordNet: An Electronic Lexical Database. MIT Press, Cambridge (1998)MATHGoogle Scholar
- 22.Strapparava, C., Valitutti, A.: WordNet-affect: an affective extension of WordNet. In: Proceedings of the 4th International Conference on Language Resources and Evaluation (LREC 2004), Lisbon, pp. 1083–1086, May 2004Google Scholar
- 23.de Marneffe, M.C., Manning, C.D.: Stanford typed dependencies manual, September 2008 (Revised for the Stanford Parser v. 3.5.2 in April 2015). http://nlp.stanford.edu/software/dependencies_manual.pdf
- 24.Landis, J.R., Koch, G.G.: The measurement of observer agreement for categorical data. Biometrics 33(1), 159–174 (1977)MathSciNetCrossRefMATHGoogle Scholar