Abstract
To learn and reason effectively about complex phenomena, a central goal in education, learners need opportunities to engage with them. Technology-mediated learning environment, such as simulations, can provide opportunities for learners to formulate, test, refine, and repair their mental models of complex systems. However, technology tools do not stand alone – they are situated in complex learning environments that require consideration of learning at the level of the individual, small group and whole class, as well as consideration of the roles that both the teacher and technology play in scaffolding student learning. While technology can enable the development of rich learning environments, the extent to which and how this technology can be used by teachers and how it influences the nature of student’s collaborative knowledge construction is still unclear. Appropriate analytical tools are needed to represent students’ mediated interactions in computer-supported collaborative learning (CSCL) environments. In this chapter, we present analytical tools that help us construct a comprehensive picture of how learning is mediated over time through a complex interplay of tool use, teacher scaffolding, and collaborative discourse to investigate the mediating roles of technology and teacher and peer scaffolding in CSCL. In particular, we will show how different representations (e.g., CORDTRA diagrams) can provide insight into the complexity of understanding of complex CSCL learning environments.
This research was funded by an NSF CAREER grant # 0133533 to the first author, NSF ROLE grant # 0107032, and NSF ALT Grant # 0632546. Conclusions or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the National Science Foundation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Arrow, H., Henry, K. B., Poole, M. S. S. W., & Moreland, R. (2005). Traces, trajectories, and timing: the temporal perspective on groups. In M. S. Poole & A. B. Hollingshead (Eds.), Theories of small groups: interdisciplinary perspectives (pp. 313–367). CA: Sage.
Avouris, N., Dimitracopoulou, A., & Komis, V. (2003). On analysis of collaborative problem solving: an object-oriented approach. Computers in Human Behavior, 19, 147–167.
Chernobilsky, E., Hmelo-Silver, C. E., & DelMarcelle, M. (2003). Collaborative discourse, tools, and activity in online problem-based learning. Chicago: Paper presented at the Annual meeting of the American Educational Reseach Association.
Chinn, C. A., & Anderson, R. C. (2000). The structure of discussions that promote reasoning. Teachers College Record, 100, 315–368.
Chiu, M. M. (2008). Flowing towards correct contributions during problem solving: a statistical discourse analysis. Journal of the Learning Sciences, 17, 415–463.
Cole, M., & Engeström, Y. (1993). A cultural-historical approach to distributed cognition. In G. Salomon (Ed.), Distributed cognitions: psychological and educational considerations. New York: Cambridge University Press.
Cress, U. (2008). The need for considering multilevel analysis in CSCL research—An appeal for the use of more advanced statistical methods. International Journal of Computer Supported Collaborative Learning, 3, 69–84.
De Laat, M. F., & Lally, V. (2003). Complexity, theory, and praxis: researching collaborative learning and tutoring processes in a networked learning community. Instructional Science, 31, 7–39.
De Wever, B., Schellens, T., Valcke, M., & Van Keer, H. (2006). Content analysis schemes to analyze transcripts of online asynchronous discussion groups: A review. Computers & Education, 46, 6–28.
Derry, S. (2006). STEP as a case of theory-based web course design. In A. M. O’Donnell, C. E. Hmelo-Silver, & G. Erkens (Eds.), Collaborative reasoning, learning and technology. Mahwah: Erlbaum.
Derry, S. J., Hmelo-Silver, C. E., Nagarajan, A., Chernobilsky, E., & Beitzel, B. (2006). Cognitive transfer revisited: can we exploit new media to solve old problems on a large scale? Journal of Educational Computing Research, 35, 145–162.
Duschl, R., & Osborne, J. (2002). Argumentation and Discourse Processes in Science Education. Studies in Science Education, 38, 39–72.
Engeström, Y. (1999). Activity theory and individual and social transformation. In Y. Engström, R. Miettinen, & R. Punamaki (Eds.), Perspectives on activity theory (pp. 19–38). New York: Cambridge University Press.
Engle, R. A., & Conant, F. R. (2002). Guiding principles for fostering productive disciplinary engagement: explaining an emergent argument in a community of learners classroom. Cognition and Instruction, 20, 399–484.
Fischer, F., Bruhn, J., Gräsel, C., & Mandl, H. (2002). Fostering collaborative knowledge construction with visualization tools. Learning and Instruction, 12, 213–232.
Goel, A. K., de Silva Garza, Gomez, Grué, N., Murdock, J. W., Recker, M. M., & Govinderaj, T. (1996). Towards designing learning environments -I: exploring how devices work. In C. Fraisson, G. Gauthier, & A. Lesgold (Eds.), Intelligent tutoring systems: lecture notes in computer science (pp. 42–52). NY: Springer.
Hmelo, C. E., Guzdial, M., & Turns, J. (1998). Computer support for collaborative learning: learning to support student engagement. Journal of Interactive Learning Resarch, 9, 107–130.
Hmelo-Silver, C. E. (2003). Analyzing collaborative knowledge construction: multiple methods for integrated understanding. Computers & Education, 41, 397–420.
Hmelo-Silver, C. E., Chernobilsky, E., & Jordan, R. (2008). Understanding collaborative learning processes in new learning environments. Instructional Science, 36, 409–430.
Hmelo-Silver, C. E., Katic, E., Nagarajan, A., & Chernobilsky, E. (2007a). Soft leaders, hard artifacts, and the groups we rarely see: using video to understand peer-learning processes. In R. Goldman, R. D. Pea, B. J. S. Barron, & S. J. Derry (Eds.), Video research in the learning sciences (pp. 255–270). Mahwah: Erlbaum.
Hmelo-Silver, C. E., Liu, L., Gray, S., Finkelstein, H., & Schwartz, R. (2007b). Enacting things differently: Using NetLogo models to learn about complex systems. Paper presented at the Biennial meeting of European Association for Research on Learning and Instruction.
Hmelo-Silver, C. E., Liu, L., & Jordan, R. (2009). Visual representation of a multidimensional coding scheme for understanding technology-mediated learning about complex natural systems. Research and Practice in Technology-enhanced Learning Environments, 4, 253–280.
Hmelo-Silver, C. E., Marathe, S., & Liu, L. (2007c). Fish swim, rocks sit, and lungs breathe: expert-novice understanding of complex systems. Journal of the Learning Sciences, 16, 307–331.
Janssen, J., Erkens, G., Kanselaar, G., & Jaspers, J. (2007). Visualization of participation: does it contribute to successful computer-supported collaborative learning. Computers & Education, 49, 1037–1065.
Jeong, A., Clark, D. B., Sampson, V. D., Menekse, M. this volume. Sequential analysis of scientific argumentation in asynchronous online discussion environments. In S. Puntambekar, G. Erkens, & C. E. Hmelo-Silver (Eds.) Analyzing interactions in CSCL: Methods, approaches, and issues (pp. 207–233). Springer.
Kumpulainen, K., & Mutanen, M. (1999). The situated dynamics of peer group interaction: an introduction to an analytic framework. Learning and Instruction, 9, 449–473.
Lai, M., & Law, N. (2006). Peer scaffolding of knowledge building through collaborative groups with differential learning experiences. Journal of the Educational Computing Research, 35, 123–144.
Lajoie, S. P., Garcia, B., Berdugo, G., Márquez, L., Espíndola, S., & Nakamura, C. (2006). The creation of virtual and face-to-face learning communities: an international collaboration experience. Journal of the Educational Computing Research, 35, 163–180.
Larkin, J. H., & Simon, H. A. (1987). Why a diagram is (sometimes) worth ten thousand words. Cognitive Science, 11, 65–99.
Liu, L. (2008). Trajectories of collaborative scientific conceptual change: middle school students learning about ecosystems in a CSCL environment. New Brunswick: Unpublished Dissertation.
Luckin, R. (2003). Between the lines: documenting the multiple dimension of computer-supported collaborations. Computers & Education, 41, 379–396.
Luckin, R., Plowman, L., Laurillard, D., Stratfold, M., Taylor, J., & Corben, S. (2001). Narrative evolution: learning from students’ talk about species variation. International Journal of Artificial Intelligence in Education, 12, 100–123.
Martinez, A., Dimitriadis, Y., Rubia, B., Gomez, E., & de la Fuente, P. (2003). Combining qualitative evaluation and social network analysis for the study of classroom social interactions. Computers & Education, 41, 353–368.
McGrath, J. E., Arrow, H., & Berdahl, J. L. (2000). The study of small groups, past, present, and future. Personality and Social Psychology Review, 4, 95–105.
Mercer, N. (2008). The seeds of time: why classroom dialogue needs a temporal analysis. Journal of the Learning Sciences, 17, 33–59.
Nurmela, K., Lehtinen, E., & Palonen, T. (1999). Evaluating CSCL log files by social network analysis. In C. M. Hoadley & J. Roschelle (Eds.), Proceedings of the 1999 conference on computer support for collaborative learning (pp. 54–66). Mahwah: Erlbaum.
Palincsar, A. S. (1998). Social constructivist perspectives on teaching and learning. Annual Review of Psychology, 45, 345–375.
Reimann, P. (2007). Time is precious: why process analysis is essential for CSCL (and can also help to bridge between experimental and descriptive methods). In C. A. Chinn, G. Erkens, & S. Puntambekar (Eds.), Proceedings of CSCL 2007: mice, minds, and society (Vol. 8, pp. 605–614). New Brunswick: International Society of the Learning Sciences.
Roschelle, J. (1996). Learning by collaborating: convergent conceptual change. In T. D. Koschmann (Ed.), CSCL: theory and practice of an emerging paradigm (pp. 209–248). Mahwah: Erlbaum.
Rummel, N., Meier, A., Spada, H., & Kahrimanis (2011). Analyzing collaborative interactions across domains and settings: An adaptable rating scheme. In S. Puntambekar, G. Erkens, & C. E. Hmelo-Silver (Eds.), Analyzing interactions in CSCL: Methodology, approaches, and issues. Springer.
Rummel, N., & Spada, H. (2005). Learning to collaborate: an instructional approach to promoting collaborative problem solving in computer-mediated settings. Journal of the Learning Sciences, 14, 201–241.
Schümmer, T., Strijbos, J. W., & Berkel, T. (2005). Measuring group interaction during CSCL. In T. Koschmann, D. Suthers, & T. W. Chan (Eds.), Computer supported collaborative learning 2005: the next 10 years! (pp. 567–576). Mahwah: Lawrence Erlbaum Associates.
Schwartz, D. L., & Bransford, J. D. (1998). A time for telling. Cognition and Instruction, 16, 475–522.
Stahl, G. (2006). Supporting group cognition in an online math community: a cognitive tool for small-group referencing in text chat. Journal of the Educational Computing Research, 35, 103–122.
Strijbos, J. W., Martens, R. L., Prins, F. J., & Jochems, W. M. G. (2006). Content analysis: what are they talking about? Computers & Education, 46, 29–48.
Strom, D., Kemeny, V., Lehrer, R., & Forman, E. (2001). Visualizing the emergent structure of children’s mathematical argument. Cognitive Science, 25, 733–774.
Suthers, D. D. (2006). Technology affordances for intersubjective meaning making. International Journal of Computer Supported Collaborative Learning, 1, 315–337.
Suthers, D. D., Dwyer, N., Medina, R., & Vatrapu, R. (2009). Exposing interactional processes in online learning. In K. Kumpulainen, C. E. Hmelo-Silver, & M. César (Eds.), Investigating classroom interaction: methodologies in action. Rotterdam: Sense.
Suthers, D. D., & Hundhausen, C. D. (2003). An experimental study of the effects of representational guidance on collaborative learning processes. Journal of the Learning Sciences, 12, 183–218.
Suthers, D., & Medina, R. (this volume). Tracing interaction in distributed collaborative learning. In S. Puntambekar, G. Erkens, & C. E. Hmelo-Silver (Eds.), Analyzing interactions in CSCL: Methods, approaches, and issues (pp. 341–366). Springer.
Wilensky, U., & Reisman, K. (2006). Thinking like a wolf, sheep, or firefly: learning biology through constructing and testing computational theories– an embodied modeling approach. Cognition and Instruction, 24(2), 171–209.
Zemel, A., Xhafa, F., & Cakir, M. (2007). What’s in the mix? Combining coding and conversation analysis to investigate chat-based problem-solving. Learning and Instruction, 17, 405–415.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Hmelo-Silver, C.E., Jordan, R., Liu, L., Chernobilsky, E. (2011). Representational Tools for Understanding Complex Computer-Supported Collaborative Learning Environments. In: Puntambekar, S., Erkens, G., Hmelo-Silver, C. (eds) Analyzing Interactions in CSCL. Computer-Supported Collaborative Learning Series, vol 12. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-7710-6_4
Download citation
DOI: https://doi.org/10.1007/978-1-4419-7710-6_4
Published:
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-7709-0
Online ISBN: 978-1-4419-7710-6
eBook Packages: Humanities, Social Sciences and LawEducation (R0)