Project summary
There are many indications that digital learning environments such as simulations, videogames and virtual reality environments may provide a cognitive bridge between concrete experiences and scientific abstractions (Furness et al., 1997; Winn, 1993). Such a bridge is crucial for enabling students to cope with complex problem solving and other high order thinking skills that are at the core of scientific and technological learning (Resnik, 2002). Ellis (1983) argues that like any popular media, videogames have become the building blocks of children’s worlds. Children usually play in groups, and when they do not, they share their experiences socially. Hence, playing videogames cannot be properly understood as simply a human-machine interaction; rather it seems to be situated in social and cultural spheres that are perhaps more important than the game itself. Moreover, Gee (2003) argues that through informal game playing, children learn to participate in what he calls ‘semiotic domains’, which are shaped by children’s interactions with virtual agents and with each other. Similarly, Nijholt (2001) claims that developments in computer science (artificial intelligence, agent technology and graphics) have paved the way for the assimilation of smart agents within learning environments, as learners become more accustomed to such agents based on their prior videogame experience. However, the study of human-human/machine interactions within videogame learning environments and virtual reality environments is in its early stages (Adobbati et al., 2001; Gazit et al., 2003). We claim that, thus far, there have been few empirical studies which have systematically studied the processes of collaborative learning within videogame environments. The results of such studies would have meaningful implications for the design of effective smart agent interaction models.
The main goal of the proposed study is to gain a better understanding of collaborative interaction processes for the design of a conceptual model of human–smart agent interactions for supporting collaborative multimodal interactions.
The study will examine the collaborative learning interactions of young students (aged 12-15 years), while they play videogames, in regular school settings (elementary school and middle school). Computerized tools and novel methodologies, such as sequential analysis, Social Networks Analysis (SNA), and growth modeling analysis will be used to examine how students construct a shared conceptual understanding of complex phenomena, how they develop their problem solving skills and their role taking dynamics, while playing videogames.
Question
Quick question--are you presenting this as a proposal for the conference? We're not quite sure what it is, though it looks very interesting. Please help.
MDB
Answer:
Yes, if its OK with U.
In School?
Hi SoniX,
Sounds like an interesting project! I think it's needed! I just have a couple of questions. I'm not familiar with sequential analysis, SNA, and growth modeling analysis. Could you briefly explain how those methods help you understand collaborative learning?
Also, I'm wondering why (just curious) you're studying kids playing the games in school rather than out of school? I think you're right (as are Gee and others) that the learning that happens with games is "situated in social and cultural spheres" so I'm wondering how those social aspects are accounted for in the in-school environments you're studying.
tyty!
-Alice
Alice J. Robison
PhD Candidate, Rhetoric & Composition Studies
Founding Member and Researcher, Room 130 and GAPPS
http://labweb.education.wisc.edu/room130
http://www.academiccolab.org/initiatives/gapps.html
University of Wisconsin-Madison
It's okay with us, SoniX
Bradley Bleck
Conference Chair
Spokane Falls CC
Sorry
Hi Bradley,
Unfortunately, these days fall within the framework of preparing and delivering a workshop at the 3rd International Conference on Multimedia and ICTs in Education (m-ICTE 2005), entitled:
Analyzing Learning and Teaching Interactions by Using Computerized Tools.
Nevertheless, Comments and remarks regarding my short intro research proj description are most welcome.
microdev, interaction analysis and more
Hi Alice,
Thanks for your kind words. I think that my study goes hand in hand with Kurt Squire's and Sasha Barab’s in-door paradigm. Additionally, we’re starting to look at the learning that takes place in informal environments, such as MMOG’s, real shopping Malls and even real/virtual Zoos. Follow this short ref list to learn more about microdev approach and interaction analysis:
Bakeman, R., & Gottman, J. M. (1986). Observing interaction: an introduction to sequential analysis. Cambridge University Press, MA.
Fischer, K. W. (1980). A Theory of Cognitive development: the control and construction of Hierarchies of skills, Psychological Review, 6, 477-531
Fischer, K. W., & Bidell, T. R. (1998). Dynamic development of psychological structures in action and thought. In R. M. Lerner (Ed.), & W. Damon (Series Ed.), Handbook of child psychology: Vol. 1. Theoretical models of human development (5th ed., pp. 467-561). New York: Wiley.
Granott, N., Fischer, K.W., & Parziale, J. (2002). Bridging to the unknown: A fundamental mechanism in learning and problem-solving. In
In N. Granott & J. Parziale (Eds.). Microdevelopment (pp. 131-156). Cambridge, U.K: Cambridge University Press.
Jeong, A.C. (2000). The sequential analysis of group interaction and critical thinking in online threaded discussions. The American Journal of Distance Education, 17(1), 25–43.
Brigitte, J., & Henderson, A.(1995).Interaction Analysis: Foundations and Practice.The Journal of the Learning Sciences, 4(1): 39-103.
Rose, S. P., & Fischer, K. W. (1998). Models and rulers in dynamical development. British Journal of Developmental Psychology, 16, 123-131.
Schwartz, M. S., & Fischer, K. W. (2003). Building vs. borrowing: The challenge of actively constructing ideas. Liberal Education, 89 (3), 22-29.
Scott, S. D., Mandryk, R.L., & Inkpen, K. M. (2003). Understanding children’s collaborative interactions in shared environments. Journal of Computer Learning Assisted, 19, 220-228.
Singer, J. D., & Willett, J. B. (2003). Applied longitudinal data analysis: Modeling change and event occurrence. New York: Oxford University Press.
Strijbos, J.W., Kirschner, P.A., & Martens, R.L. (Eds.) (2004). What we know about CSCL: And implementing it in higher education. Boston, MA: Kluwer Academic Publishers/Springer Verlag.
http://www.utwente.nl/ico/onderzoek/project/afgerond/ou/strijbos_prom.do...
Recommended!
van Geert, P. (1991). A dynamic systems model of cognitive and language growth. Psychological Review, 98, 3-53.
van Geert, P. (1998). A dynamic systems model of basic developmental mechanisms: Piaget, Vygotsky, and beyond. Psychological Review, 105, 634-677.
Yan, Z., & Fischer, K. W. (2002). Always under construction: Dynamic variations in adult cognitive development. Human Development, 45, 141-160.
Alice, Have you published or presented s.t about your own research project yet?
...Stay tuned for my coming article on the learning dynamics within Virtual Reality environments.
Best,
-Elchanan
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Elchanan Gazit
PostDoc Fellow Researcher
LIRT Lab, The Caesarea Rothschild Institute
University of Haifa
Mount Carmel, Haifa 31905, Israel
Office: Education building, room 565
E-mail: gazit@post.tau.ac.il
Homepage: http://www.tau.ac.il/~gazit/
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The Quotation of the Month:
You can discover more about a person in an hour of play than in a year of conversation.
Plato Greek author & philosopher in Athens (427 BC - 347 BC)