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Journal of Computers in Education

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01-12-2016

Exploring individual contributions during online collaborative discussions

Authors: Chang Xu, Yafeng Zheng, Hening Hu, Yanyan Li

Published in: Journal of Computers in Education | Issue 4/2016

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Abstract

Learning via online discussion has been widely acknowledged as an effective means in interactive learning environments. Many existing studies analyze collaborative discussions at the group level. Increasingly, researchers suggest that a better understanding of individual contributions within a group could help to explain what happens within groups. However, the existing analysis on individual contributions in online collaborative discussion is not comprehensive. In addition, there are only a few studies investigating the relationship between group performance and individual contributions. By quantitatively analyzing students’ discussion content and participation behaviors, this study measured the individual contributions based on six distinguishing features: productivity, activation, activity, reactivity, persistence, and novelty. Furthermore, cluster analysis was conducted to identify four contributor clusters: prominent contributors, coordinators, self-directed learners, and peripheral participants. Combined with the deep analysis of discussion postings, this study analyzed and described the features of each cluster contributors in detail. Furthermore, implications of this study for instructors’ guidance and researchers are discussed.

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Anderson, T., Rourke, L., Garrison, D. R., & Archer, W. (2001). Assessing teaching presence in a computer conferencing context. Journal of Asynchronous Learning Networks, 5(2), 1–17.

Arvaja, M., Salovaara, H., Häkkinen, P., & Järvelä, S. (2007). Combining individual and group-level perspectives for studying collaborative knowledge construction in context. Learning and Instruction, 17(4), 448–459. doi:10.1016/j.learninstruc.2007.04.003.CrossRef

Barron, B. (2003). When smart groups fail. Journal of the Learning Sciences, 12(3), 307–359.CrossRef

Caballé, S., Daradoumis, T., Xhafa, F., & Juan, A. (2011). Providing effective feedback, monitoring and evaluation to on-line collaborative learning discussions. Computers in Human Behavior, 27(4), 1372–1381. doi:10.1016/j.chb.2010.07.032.CrossRef

Cacciamani, S., Cesareni, D., Martini, F., Ferrini, T., & Fujita, N. (2012). Influence of participation, facilitator styles, and metacognitive reflection on knowledge building in online university courses. Computers & Education, 58(3), 874–884.CrossRef

Calvani, A., Fini, A., Molino, M., & Ranieri, M. (2010). Visualizing and monitoring effective interactions in online collaborative groups. British Journal of Educational Technology, 41(2), 213–226.CrossRef

Chan, C. K., & Chan, Y.-Y. (2011). Students’ views of collaboration and online participation in Knowledge Forum. Computers & Education, 57(1), 1445–1457.CrossRef

Cheng, C. K., Paré, D. E., Collimore, L. M., & Joordens, S. (2011). Assessing the effectiveness of a voluntary online discussion forum on improving students’ course performance ☆. Computers & Education, 56(1), 253–261.CrossRef

Chiu, C.-H., & Hsiao, H.-F. (2010). Group differences in computer supported collaborative learning: Evidence from patterns of Taiwanese students’ online communication. Computers & Education, 54(2), 427–435.CrossRef

Garrison, D. R. (2007). Online community of inquiry review: Social, cognitive, and teaching presence issues. Journal of Asynchronous Learning Networks, 11(1), 61–72.

Häkkinen, P. (2013). Multiphase method for analysing online discussions. Journal of Computer Assisted learning, 29(6), 547–555. doi:10.1111/jcal.12015.CrossRef

Heo, H., Lim, K. Y., & Kim, Y. (2010). Exploratory study on the patterns of online interaction and knowledge co-construction in project-based learning. Computers & Education, 55(3), 1383–1392.CrossRef

Hong, H.-Y., & Scardamalia, M. (2014). Community knowledge assessment in a knowledge building environment. Computers & Education, 71, 279–288.CrossRef

Hou, H.-T., Chang, K.-E., & Sung, Y.-T. (2008). Analysis of problem-solving-based online asynchronous discussion pattern. Journal of Educational Technology & Society, 11(1), 17–28.

Hou, H.-T., & Wu, S.-Y. (2011). Analyzing the social knowledge construction behavioral patterns of an online synchronous collaborative discussion instructional activity using an instant messaging tool: A case study. Computers & Education, 57(2), 1459–1468.CrossRef

Hrastinski, S. (2009). A theory of online learning as online participation. Computers & Education, 52(1), 78–82. doi:10.1016/j.compedu.2008.06.009.CrossRef

Hung, J. L., & Zhang, K. (2008). Revealing online learning behaviors and activity patterns and making predictions with data mining techniques in online teaching. Journal of Online Learning & Teaching, 4(4), 426–436.

Hwang, A., & Arbaugh, J. B. (2009). Seeking feedback in blended learning: Competitive versus cooperative student attitudes and their links to learning outcome. Journal of Computer Assisted learning, 25(3), 280–293.CrossRef

Janssen, J., Erkens, G., Kirschner, P. A., & Kanselaar, G. (2012). Task-related and social regulation during online collaborative learning. Metacognition & Learning, 7(7), 25–43.CrossRef

Johnson, D. W., & Johnson, R. T. (1989). Toward a cooperative effort: A response to Slavin. Educational Leadership, 46(7), 80–81.

Li, Y., Dong, M., & Huang, R. (2009). Toward a semantic forum for active collaborative learning. Educational Technology & Society, 12(4), 71–86.

Li, Y., Liao, J., Wang, J., & Huang, R. (2007). CSCL interaction analysis for assessing knowledge building outcomes: method and tool. In Proceedings of the 8th international conference on Computer supported collaborative learning (pp. 431–440). International Society of the Learning Sciences

Li, Y., Ma, S., Zhang, Y., & Huang, R. (2013). An improved mix framework for opinion leader identification in online learning communities. Knowledge-Based Systems, 43, 43–51. doi:10.1016/j.knosys.2013.01.005.CrossRef

Lipponen, L. (2002). Exploring foundations for computer-supported collaborative learning. In Proceedings of the conference on computer support for collaborative learning: Foundations for a CSCL community (pp. 72–81)

Palomo-Duarte, M., Dodero, J. M., Medina-Bulo, I., Rodríguez-Posada, E. J., & Ruiz-Rube, I. (2014). Assessment of collaborative learning experiences by graphical analysis of wiki contributions. Interactive Learning Environments, 22(4), 444–466.CrossRef

Roschelle, J., & Teasley, S. D. (1995). The construction of shared knowledge in collaborative problem solving. In C. O'Malley (Ed.), Computer Supported Collaborative Learning (pp. 69–97). Berlin: Springer.CrossRef

Siqin, T., van Aalst, J., & Chu, S. K. W. (2015). Fixed group and opportunistic collaboration in a CSCL environment. International Journal of Computer-Supported Collaborative Learning. doi:10.1007/s11412-014-9206-7.

Smith Risser, H., & Bottoms, S. (2014). “Newbies” and “Celebrities”: Detecting social roles in an online network of teachers via participation patterns. International Journal of Computer-Supported Collaborative Learning, 9(4), 433–450. doi:10.1007/s11412-014-9197-4.CrossRef

Stahl, G. (2006). Group cognition: Computer support for building collaborative knowledge. Cambridge, MA: MIT Press.

Stahl, G., Law, N., Cress, U., & Ludvigsen, S. (2014). Analyzing roles of individuals in small-group collaboration processes. International Journal of Computer-Supported Collaborative Learning, 9(4), 365–370.CrossRef

Trausan-Matu, S., & Rebedea, T. (2010). A polyphonic model and system for inter-animation analysis in chat conversations with multiple participants. In CICLing (pp. 354–363). Berlin: Springer

Tsovaltzi, D., Judele, R., Puhl, T., & Weinberger, A. (2015). Scripts, individual preparation and group awareness support in the service of learning in Facebook: How does CSCL compare to social networking sites? Computers in Human Behavior, 53, 577–592.CrossRef

Vonderwell, S. (2003). An examination of asynchronous communication experiences and perspectives of students in an online course: A case study. Internet & Higher Education, 6(1), 77–90.CrossRef

Ward, J. H. (1963). Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association, 58(301), 236–244.CrossRef

Title: Exploring individual contributions during online collaborative discussions
Authors: Chang Xu
Yafeng Zheng
Hening Hu
Yanyan Li
Publication date: 01-12-2016
Publisher: Springer Berlin Heidelberg
Published in: Journal of Computers in Education / Issue 4/2016
Print ISSN: 2197-9987
Electronic ISSN: 2197-9995
DOI: https://doi.org/10.1007/s40692-016-0071-4

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