Abstract
This chapter compares two multidimensional analyses of the PLTL Chemistry dataset, which each include a cognitive, relational, and motivational dimension. These multidimensional analyses serve to highlight the ways in which the complementary perspectives on collaborative processes offered by each dimension can be integrated in a way that offers deep insights into social positioning within collaborative groups. Differences revealed particularly along the relational and motivational dimensions raise important questions regarding the operationalization of interaction style as displayed through language and highlight the value of multivocality for the purpose of refining important constructs in ways that work towards theory building through integration of findings across research groups that employ different analytic frameworks coming from a common theoretical foundation.
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References
Ai, H., Sionti, M., Wang, Y. C., & Rosé, C. P. (2010). Finding transactive contributions in whole group classroom discussions. In K. Gomez, L. Lyons, & J. Radinsky (Eds.), Proceedings of the International Conference of the Learning Sciences (pp. 976–983). Chicago, IL: International Society of the Learning Sciences.
Berkowitz, M.W., & Gibbs, J.C., (1979). A Preliminary Manual for Coding Transactive Features of Dyadic Discussion. Unpublished Manuscript. Marquette University, Milwaukee, WI.
Boekaerts, M., & Minnaert, A. (2006). Affective and motivational outcomes of working in collaborative groups. Educational Psychology, 26(2), 187–208.
Boekaerts, M., & Niemivirta, M. (2000). Self-regulated learning: Finding a balance between learning goals and ego protective goals. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 417–450). New York, NY: Academic.
Dillenbourg, P., Järvelä, S., & Fischer, F. (2009). The evolution of research on computer-supported collaborative leaning: From design to orchestration. In N. Balacheff, S. Ludvigsen, T. de Jong, A. Lazonder, & S. Barnes (Eds.), Technology-enhanced learning: Principles and products (pp. 3–20). New York, NY: Springer.
Gillies, R. M. (2007). Cooperative learning: Integrating theory and practice. Thousand Oaks, CA: Sage.
Gweon, G., Jain, M., McDonogh, J., Raj, B., & Rosé, C. P. (2012). Predicting idea co-construction in speech data using insights from sociolinguistics. In M. Jacobson & P. Reimann (Eds.), Proceedings of the International Conference of the Learning Sciences. International Society of the Learning Sciences: Sydney, Australia.
Hijzen, D., Boekaerts, M., & Vedder, P. (2007). Exploring the links between students’ engagement in cooperative learning, their goal preferences and appraisals of instruction conditions in the classroom. Learning and Instruction, 17(6), 673–687.
Howley, I., Adamson, D., Dyke, G., Mayfield, E., Beuth, J., & Rosé, C. P. (2012). Group composition and intelligent dialogue tutors for impacting students’ self-efficacy. In S. Cerri, W. Clancey, G. Papadourakis, & K.-K. Panourgia (Eds.), Intelligent tutoring systems: 11th International Conference, ITS 2012. Crete, Greece: IOS Publisher.
Howley, I., Mayfield, E., & Rosé, C. P. (2013). Linguistic analysis methods for studying small groups. In C. Hmelo-Silver, A. O’Donnell, C. Chan, & C. Chin (Eds.), International handbook of collaborative learning. New York, NY: Taylor and Francis.
Järvelä, S., Volet, S., & Järvenoja, H. (2010). Research on motivation in collaborative learning: Moving beyond the cognitive-situative divide and combining individual and social processes. Educational Psychologist, 45(1), 15–27.
Johnson, D. W., & Johnson, R. T. (1994). Learning together and alone: Cooperative, competitive and individualistic learning (4th ed.). Boston, MA: Allyn & Bacon.
Joshi, M., & Rosé, C. P. (2007). Using transactivity in conversation summarization in educational dialog (Proceedings of the SLaTE Workshop on Speech and Language Technology in Education). Farmington, PA: ISCA.
Krapp, A. (2005). Basic needs and the development of interest and intrinsic motivational orientations. Learning and Instruction, 15(5), 381–395.
Kreijns, K., Kirschner, P. A., & Jochems, W. M. G. (2003). Identifying the pitfalls for social interaction in computer-supported collaborative learning: A review of the research. Computers in Human Behavior, 19(3), 335–353.
Kulhavy, R. W., & Stock, W. A. (1989). Feedback in written instruction: The place of response certitude. Educational Psychology Review, 1(4), 279–308.
Kumar, R., & Rosé, C. P. (2011). Architecture for building conversational agents that support collaborative learning. IEEE Transactions on Learning Technologies, 4(1), 21–34.
Kumpulainen, K., & Mutanen, M. (1999). The situated dynamics of peer group interaction: An introduction to an analytic framework. Learning and Instruction, 9(5), 449–473.
Martin, J. R., & Rose, D. (2003). Working with discourse: Meaning beyond the clause. London: Continuum.
Martin, J. R., & White, P. R. R. (2005). The language of evaluation: Appraisal in English. London: Palgrave.
Mayfield, E., & Rosé, C. P. (2011). Recognizing authority in dialogue with an integer linear programming constrained model. In Y. Matsumoto & R. Mihalcea (Eds.), Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies. Portland, OR: Association for Computational Linguistics.
Narciss, S. (2008). Feedback strategies for interactive learning tasks. In J. M. Spector, M. D. Merrill, J. J. G. Van Merriënboer, & M. P. Driscoll (Eds.), Handbook of research on educational communications and technology (3rd ed., pp. 125–143). Mahwah, NJ: Erlbaum.
Rosé, C. P., Wang, Y. C., Cui, Y., Arguello, J., Stegmann, K., Weinberger, A., et al. (2008). Analyzing collaborative learning processes automatically: Exploiting the advances of computational linguistics in computer-supported collaborative learning. International Journal of Computer-Supported Collaborative Learning, 3(3), 237–271.
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55(1), 68–78.
Sarmiento, J. W., & Shumar, W. (2010). Boundaries and roles: Positioning and social location in the Virtual Math Teams (VMT) online community. Computers in Human Behavior, 16(4), 524–532.
Sawyer, Frey, & Brown. (this volume). Peer led team learning in general chemistry. In Suthers, D., Lund, K., Rosé, C. P., Teplovs, C., Law, N. (Eds.), Productive multivocality in the analysis of group interactions, Chapter 9. New York, NY: Springer.
Sharan, Y., & Sharan, S. (1992). Expanding cooperative learning through group investigation. New York, NY: Teachers College Press.
Slavin, R. E. (1996). Research on cooperative learning and achievement: What we know, what we need to know. Contemporary Educational Psychology, 21(1), 43–69.
Strijbos, J. W. (2011). Assessment of (computer-supported) collaborative learning. IEEE Transactions on Learning Technologies, 4(1), 59–73.
Strijbos, J. W., & Stahl, G. (2007). Methodological issues in developing a multi-dimensional coding procedure for small group chat communication. Learning and Instruction, 17(4), 394–404.
Strijbos, J. W., Van Goozen, B., & Prins, F. (2012, August). Developing a coding scheme for analysing peer feedback messages. Paper presented at the EARLI-SIG 1 Assessment and Evaluation Conference, Brussels, Belgium.
Tolmie, Andrew Kenneth, Keith J. Topping, Donald Christie, Caroline Donaldson, Christine Howe, Emma Jessiman, Kay Livingston, and Allen Thurston. (2010). Social effects of collaborative learning in primary schools. Learning and Instruction, 20(3), 177–191.
Weinberger, A., & Fischer, F. (2006). A framework to analyze argumentative knowledge construction in computer-supported collaborative learning. Computers and Education, 46(1), 71–95.
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This work was supported in part by NSF grant SBE 0836012 to the Pittsburgh Science of Learning Center.
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Howley, I., Mayfield, E., Rosé, C.P., Strijbos, JW. (2013). A Multivocal Process Analysis of Social Positioning in Study Groups. In: Suthers, D., Lund, K., Rosé, C., Teplovs, C., Law, N. (eds) Productive Multivocality in the Analysis of Group Interactions. Computer-Supported Collaborative Learning Series, vol 15. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-8960-3_11
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