Abstract
The national science standards call for increased focus on scientific argumentation in the classroom, and researchers have developed sophisticated online science learning environments to promote and support student engagement in scientific argumentation. Assessing the quality of scientific dialogic argumentation in these environments, however, has proven to be challenging. Existing analytic frameworks tend to assess scientific argumentation using the presence or absence of various types of comments (e.g., frequency of claims, rebuttals, and supporting statements) that do not fully convey the dynamic and dialogic nature of argumentation. In this chapter, we present a sequential analysis approach developed by Jeong (2005) that incorporates a coding scheme developed by Clark and Sampson (2007, 2008) to identify, visualize, and assess the dialogic processes of argumentation in online science learning environments in terms of transitional probabilities, transitional state diagrams, and other related measures. These measures include: (a) how and how often students respond to particular discourse moves (e.g., the probabilities that responses to claims are rebuttals vs. simple agreement vs. no response); and (b) how and to what extent observed response patterns produce extended chains of discourse moves that exhibit high levels of argumentation (claim → challenge → explain or amend claim). A sample analysis is presented to illustrate how this approach can also be used to assess how characteristics of the discourse environment affect the quality of argumentation and better understand the interplay between discourse environments and collaborative discourse.
This work was partly funded by the National Science Foundation, grant 0334199, as part of the center for Technology Enhanced Learning in Science (TELS). Any opinions, findings, and conclusions or recommendations expressed in this study are those of the researchers and do not necessarily reflect the views of the National Science Foundation.
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References
Bakeman, R., & Gottman, J. (1997). Observing interaction: An introduction to sequential analysis. Cambridge: Cambridge University Press.
Bakeman, R., & Quera, V. (1995). Analyzing interaction: Sequential analysis with SDIS and GSEQ (p. 109). Cambridge University Press: Cambridge.
Clark, D. B. (2000). Scaffolding knowledge integration through curricular depth. Unpublished doctoral dissertation, University of California, Berkeley.
Clark, D. B. (2006). Longitudinal conceptual change in students’ understanding of thermal equilibrium: An examination of the process of conceptual restructuring. Cognition and Instruction, 24(4), 467–563.
Clark, D. B., D’Angelo, C. M., & Menekse, M. (2009). Initial structuring of online discussions to improve learning and argumentation: Incorporating students’ own explanations as seed comments versus an augmented-preset approach to seeding discussions. Journal of Science Education and Technology, 18(4), 321–333.
Clark, D. B., & Linn, M. C. (2003). Scaffolding knowledge integration through curricular depth. Journal of the Learning Sciences, 12(4), 451–494.
Clark, D. B. (2004). Hands-on investigation in Internet environments: Teaching thermal equilibrium. In M. C. Linn, E. A. Davis, & P. Bell (Eds.), Internet environments for science education (pp. 175–200). Mahwah, NJ: Lawrence Erlbaum Associates.
Clark, D. B., & Sampson, V. (2005). Analyzing the quality of argumentation supported by personally-seeded discussions. Paper presented at the computer supported collaborative learning conference, Taipei, Taiwan.
Clark, D. B., & Sampson, V. D. (2007). Personally-seeded discussions to scaffold online argumentation. International Journal of Science Education, 29(3), 253–277.
Clark, D., Sampson, V., Weinberger, A., & Erkens, G. (2007). Analytic frameworks for assessing dialogic argumentation in online learning environments. Educational Psychology Review, 19(3), 343–374.
Clark, D. B., & Sampson, V. (2008). Assessing dialogic argumentation in online environments to relate structure, grounds, and conceptual quality. Journal of Research in Science Teaching, 45(3), 293–321.
Clark, D. B., Schleigh, S. P., Menekse, M., D’Angelo, C. M., & Sampson, S. (2008). Improving the quality of student argumentation through the initial structuring of online discussions. Paper presented as part of symposium organized by William Sandoval for the American Educational Research Association (AERA) 2008 meeting. New York.
Clough, E. E., & Driver, R. (1985). Secondary students’ conceptions of the conduction of heat: Bringing together scientific and personal views. Physical Educator, 20, 176–182.
Cuthbert, A. J., Clark, D. B., & Linn, M. C. (2002). WISE learning communities: Design considerations. In K. A. Renninger & W. Shumar (Eds.), Building virtual communities: Learning and change in cyberspace (pp. 215–246). Cambridge: Cambridge University Press.
deVries, E., Lund, K., & Baker, M. (2002). Computer-mediated epistemic dialogue: Explanation and argumentation as vehicles for understanding scientific notions. Journal of the Learning Sciences, 11(1), 63–103.
Erduran, S., Simon, S., & Osborne, J. (2004). TAPping into argumentation: Developments in the application of Toulmin’s argument pattern for studying science discourse. Science & Education, 88, 915–933.
Erickson, G., & Tiberghien, A. (1985). Heat and temperature. In R. Driver, E. Guesne, & A. Tiberghien (Eds.), Children’s ideas in science (pp. 52–83). Philadelphia: Open University Press.
Erkens, G., Kanselaar, G., Prangsma, M., & Jaspers, J. (2003). Computer support for collaborative and argumentative writing. In E. D. Corte, L. Verschaffel, N. Entwistle, & Jv Merriënboer (Eds.), Powerful learning environments: Unravelling basic components and dimensions (pp. 157–176). Amsterdam: Pergamon, Elsevier Science.
Harrison, A. G., Grayson, D. J., & Treagust, D. F. (1999). Investigating a grade 11 student’s evolving conceptions of heat and temperature. Journal of Research in Science Teaching, 36(1), 55–87.
Janssen, J., Erkens, G., Jaspers, J., & Kanselaar, G. (2007). Visualization of participation: Does it contribute to successful computer-supported collaborative learning? Computers & Education, 49, 1037–1065.
Jeong, A. (2004). Discussion analysis tools. Retrieved March 10 2009. http://mailer.fsu.edu/∼ajeong/DAT
Jeong, A. (2005). A guide to analyzing message-response sequences and group interaction patterns in computer-mediated communication. Distance Education, 26(3), 367–383. Retrieved December 2008 http://garnet.fsu.edu/∼ajeong/research/Jeong2005_AnalyzingInteraction.pdf.
Jeong, A. (2007). The effects of intellectual openness and gender on critical thinking processes in computer-supported collaborative argumentation. Journal of Distance Education, 22(1), 1–18.
Jeong, A. (2008). jMAP. Retrieved March 10 2009. http://jmap.wikispaces.com
Jermann, P., & Dillenbourg, P. (2003). Elaborating new arguments through a CSCL script. In J. Andriessen, M. Baker, & D. Suthers (Eds.), Arguing to learn: Confronting cognitions in computer-supported collaborative learning environments (pp. 205–226). Dordrecht: Kluwer Academic.
Lewis, E. L. (1996). Conceptual change among middle school students studying elementary thermodynamics. Journal of Science Education and Technology, 5(1), 3–31.
Linn, M. C., & Hsi, S. (2000). Computers, teachers, peers: Science learning partners. Mahwah: Lawrence Erlbaum.
Rourke, L., Anderson, T., Garrison, D. R., & Archer, W. (2001). Methodological issues in the content analysis of computer conference transcripts. International Journal of Artificial Intelligence in Education, 12, 8–22. Retrieved July 09, 2005, from http://aied.inf.ed.ac.uk/members01/archive/vol_12/rourke/full.html.
Schwarz, B. B. & Glassner, A. (in press). The role of CSCL argumentative environments for broadening and deepening understanding of the space of debate. In R. Saljo (Ed.), Information technologies and transformation of knowledge.
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Jeong, A., Clark, D.B., Sampson, V.D., Menekse, M. (2011). Sequential Analysis of Scientific Argumentation in Asynchronous Online Discussion 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_10
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