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Why and how do middle school students exchange ideas during science inquiry?

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Abstract

Science is increasingly characterized by participation in knowledge communities. To meaningfully engage in science inquiry, students must be able to evaluate diverse sources of information, articulate informed ideas, and share ideas with peers. This study explores how technology can support idea exchanges in ways that value individuals’ prior ideas, and allow students to use these ideas to benefit their own and their peers’ learning. We used the Idea Manager, a curriculum-integrated tool that enables students to collect and exchange ideas during science inquiry projects. We investigated how students exchanged ideas, how these exchanges impacted the explanations they ultimately produced, and how the tool impacted teachers’ instruction. We implemented the tool with 297 grade 7 students, who were studying a web-based unit on cancer and cell division. Among other results, we found a relationship between the diversity of students’ ideas, and the sources of those ideas (i.e., whether they came from the students themselves or from their peers), and the quality of students’ scientific explanations. Specifically, students who collected more unique ideas (i.e., ideas not already represented in their private idea collections) as opposed to redundant ideas (i.e., ideas that reiterated ideas already present in their private idea collections) tended to write poorer explanations; and students who generated their own redundant ideas, as opposed to choosing peers’ ideas that were redundant, tended to write better explanations. We discuss implications for formative assessment, and for the role of technology in supporting students to engage more meaningfully with peers’ ideas.

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References

  • American Library Association. (2015). Framework for Information Literacy for Higher Education. Document ID: b910a6c4-6c8a-0d44-7dbc-a5dcbd509e3f. Retrieved from http://www.ala.org/acrl/standards/ilframework. Accessed 20 July 2018.

  • Amigues, R. (1988). Peer interaction in solving physics problems: Sociocognitive confrontation and metacognitive aspects. Journal of Experimental Child Psychology, 45(1), 141–158.

    Google Scholar 

  • Andriessen, J. (2006). Collaboration in computer conferencing. In A. M. O'Donnell, C. E. Hmelo-Silver, & G. Erkens (Eds.), Collaborative learning, reasoning, and technology (pp. 197–230). Mahwah: Erlbaum.

    Google Scholar 

  • Asterhan, C. S., & Schwarz, B. B. (2009). Argumentation and explanation in conceptual change: Indications from protocol analyses of peer‐to‐peer dialog. Cognitive Science, 33(3), 374–400.

  • Bailin, S. (2002). Critical thinking and science education. Science & Education, 11(4), 361–375.

    Google Scholar 

  • Bargh, J. A., & Schul, Y. (1980). On the cognitive benefits of teaching. Journal of Educational Psychology, 72(5), 593.

    Google Scholar 

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

    Google Scholar 

  • Barzilai, S., & Zohar, A. (2012). Epistemic thinking in action: Evaluating and integrating online sources. Cognition and Instruction, 30, 39–85. https://doi.org/10.1080/07370008.2011.636495.

    Google Scholar 

  • Bell, P. (1997). Using argument representations to make thinking visible for individuals and groups. In Proceedings of the 2nd international conference on Computer Support for Collaborative Learning (pp. 10–19). International Society of the Learning Sciences.

  • Bell, P. (2013). Promoting students' argument construction and collaborative debate in the science classroom. In Internet environments for science education (pp. 143–172). Routledge.

  • Bell, P., & Linn, M. C. (2000). Scientific arguments as learning artifacts: Designing for learning from the web with KIE. International Journal of Science Education [Special Issue], 22(8), 797–817.

    Google Scholar 

  • Bereiter, C. (2002). Education and mind in the knowledge age. Mahwah: Lawrence Erlbaum Associates.

    Google Scholar 

  • Bereiter, C., & Scardamalia, M. (1989). Intentional learning as a goal of instruction. In L. B. Resnick (Ed.), Knowing, learning, and instruction: Essays in honor of Robert Glaser (pp. 361–392). Hillsdale: Lawrence Erlbaum Associates.

    Google Scholar 

  • Bereiter, C., & Scardamalia, M. (1993). Surpassing ourselves: An inquiry into the nature and implications of expertise. Chicago and La Salle: Open Court.

    Google Scholar 

  • Berland, L. K., & Reiser, B. J. (2009). Making sense of argumentation and explanation. Science Education, 93(1), 26–55.

    Google Scholar 

  • Blatchford, P., Kutnick, P., Baines, E., & Galton, M. (2003). Toward a social pedagogy of classroom group work. International Journal of Educational Research, 39(1), 153–172.

    Google Scholar 

  • Carey, S. (2009). The Origin of Concepts. Oxford: Oxford University Press. https://doi.org/10.1093/acprof:oso/9780195367638.001.0001.

    Google Scholar 

  • Chen, Z., & Klahr, D. (1999). All other things being equal: Acquisition and transfer of the control of variables strategy. Child Development, 70, 1098–1120.

    Google Scholar 

  • Chi, M. (2000). Self-explaining expository texts: The dual processes of generating inferences and repairing mental models. Advances in instructional psychology, 5, 161–238.

    Google Scholar 

  • Chi, M. T., Bassok, M., Lewis, M. W., Reimann, P., & Glaser, R. (1989). Self-explanations: How students study and use examples in learning to solve problems. Cognitive Science, 13(2), 145–182.

    Google Scholar 

  • Chi, M. T., De Leeuw, N., Chiu, M. H., & LaVancher, C. (1994). Eliciting self-explanations improves understanding. Cognitive Science, 18(3), 439–477.

    Google Scholar 

  • Chi, M. T. H., Siler, S. A., Jeong, H., Yamauchi, T., & Hausmann, R. G. (2001). Learning from human tutoring. Cognitive Science, 25(4), 471–533.

    Google Scholar 

  • Chin, C., & Osborne, J. (2010). Students’ questions and discursive interaction: Their impact on argumentation during collaborative group discussions in science. Journal of Research in Science Teaching, 47, 883–908. https://doi.org/10.1002/tea.20385.

    Google Scholar 

  • Chinn, C. A., & Brewer, W. F. (1998). An empirical test of a taxonomy of responses to anomalous data in science. Journal of Research in Science Teaching, 35(6), 623–654.

    Google Scholar 

  • Cohen, E. G. (1994). Restructuring the classroom: Conditions for productive small groups. Review of Educational Research, 64(1), 1–35.

    Google Scholar 

  • Coirier, P., Andriessen, J., & Chanquoy, L. (1999). From planning to translating: The specificity of argumentative writing. Foundations of argumentative text processing, 1–28.

  • Cropley, A. (2006). In praise of convergent thinking. Creativity Research Journal, 18(3), 391–404.

    Google Scholar 

  • Cypress, B. S. (2017). Rigor or reliability and validity in qualitative research: Perspectives, strategies, reconceptualization, and recommendations. Dimensions of Critical Care Nursing, 36(4), 253–263.

    Google Scholar 

  • De Jonge, K. M., Rietzschel, E. F., & Van Yperen, N. W. (2018). Stimulated by novelty? The role of psychological needs and perceived creativity. Personality and Social Psychology Bulletin, 44(6), 851–867.

  • Derry, S. J., Pea, R. D., Barron, B., Engle, R. A., Erickson, F., Goldman, R., et al. (2010). Conducting video research in the learning sciences: Guidance on selection, analysis, technology, and ethics. The Journal of the Learning Sciences, 19(1), 3–53.

    Google Scholar 

  • Dillenbourg, P. (2002). Over-scripting CSCL: The risks of blending collaborative learning with instructional design. In P. A. Kirschner. Three worlds of CSCL. Can we support CSCL?, Heerlen, Open Universiteit Nederland, pp. 61–91.

  • diSessa, A. A. (2000). Changing minds: Computers, learning, and literacy. Cambridge: MIT Press.

    Google Scholar 

  • Duschl, R. A., & Osborne, J. (2002). Supporting and promoting argumentation discourse in science education. Studies in Science Education, 38(1), 39–72. https://doi.org/10.1080/03057260208560187.

    Google Scholar 

  • Eylon, B. S., & Linn, M. C. (1988). Learning and instruction: An examination of four research perspectives in science education. Review of Educational Research, 58(3), 251–301.

    Google Scholar 

  • Facione, P. (1990). Critical thinking: A statement of expert consensus for purposes of educational assessment and instruction (The Delphi Report).

  • Fischer, F., & Mandl, H. (2005). Knowledge convergence in computer-supported collaborative learning: The role of external representation tools. The Journal of the Learning Sciences, 14(3), 405–441.

  • Fitzgerald, J. (1992). Variant views about good thinking during composing: Focus on revision. In M. Pressley, K. R. Harris, & J. T. Guthrie (Eds.), Promoting Academic Competence and Literacy in School (pp. 337–358). New York: Academic.

  • Forman, E. A., Cazden, C. B., & Wertsch, J. V. (1985). Exploring Vygotskian perspectives in education. In D. Faulkner, K. Littleton, & M. Woodhead (Eds.), Learning Relationships in the Classroom. London and New York: Routledge.

    Google Scholar 

  • Furberg, A. (2016). Teacher support in computer-supported lab work: Bridging the gap between lab experiments and students’ conceptual understanding. International Journal of Computer-Supported Collaborative Learning, 11, 89–113. https://doi.org/10.1007/s11412-016-9229-3.

    Google Scholar 

  • Furtak, E. M., Kiemer, K., Circi, R. K., Swanson, R., de León, V., Morrison, D., & Heredia, S. C. (2016). Teachers’ formative assessment abilities and their relationship to student learning: findings from a four-year intervention study. Instructional Science, 44(3), 267–291.

    Google Scholar 

  • Furtak, E. M., & Ruiz-Primo, M. A. (2008). Making students’ thinking explicit in writing and discussion: An analysis of formative assessment prompts. Science Education, 92(5), 799–824. https://doi.org/10.1002/sce.v92:5.

    Google Scholar 

  • Gerard, L. F., Ryoo, K., McElhaney, K. W., Liu, O. L., Rafferty, A. N., & Linn, M. C. (2016). Automated guidance for student inquiry. Journal of Educational Psychology, 108(1), 60.

    Google Scholar 

  • Gillies, R. M., & Haynes, M. (2011). Increasing explanatory behaviour, problem-solving, and reasoning within classes using cooperative group work. Instructional Science, 39(3), 349–366.

    Google Scholar 

  • Glachan, M., & Light, P. (1982). Peer interaction and learning: Can two wrongs make a right. Social cognition: Studies of the development of understanding, 238–262.

  • Halatchliyski, I., Kimmerle, J., & Cress, U. (2011). Divergent and convergent knowledge processes on Wikipedia. In Proceedings of the Computer Supported Collaborative Learning conference (pp. 566–570).

  • Halverson, K., Siegel, M., & Freyermuth, S. (2009). Lenses for framing decisions: Undergraduates’ decision making about stem cell research. International Journal of Science Education, 31(9), 1249–1268. https://doi.org/10.1080/09500690802178123.

    Google Scholar 

  • Hargittai, E., Fullerton, L., Menchen-Trevino, E., & Thomas, K. Y. (2010). Trust online: Young adults’ evaluation of web content. International Journal of Communication, 4, 468–494.

    Google Scholar 

  • Hatano, G. (1993). Time to merge Vygotskian and constructivist conceptions of knowledge acquisition. In E. A. Forman, N. Minick, & C. A. Stone (Eds.), Contexts for learning: Sociocultural dynamics in children’s development (pp. 153–166). New York: Oxford University Press.

    Google Scholar 

  • Hausmann, R. G., Chi, M. T., & Roy, M. (2004). Learning from collaborative problem solving: An analysis of three hypothesized mechanisms. In Proceedings of the Cognitive Science Society (Vol. 26, No. 26).

  • Herrenkohl, L. R., Palincsar, A. S., DeWater, L. S., & Kawasaki, K. (1999). Developing scientific communities in classrooms: A sociocognitive approach. The Journal of the Learning Sciences, 8, 451–493. https://doi.org/10.1080/10508406.1999.9672076.

    Google Scholar 

  • Hashweh, M. Z. (2016). The complexity of teaching density in middle school. Research in Science & Technological Education, 34(1), 1–24.

    Google Scholar 

  • Hmelo-Silver, C., Jeong, H., Faulkner, R., & Hartley, K. (2017). Computer-supported collaborative learning in STEM domains: Towards a meta-synthesis. In Proceedings of the 50th Hawaii International Conference on System Sciences.

  • Hogan, K., Nastasi, B. K., & Pressley, M. (1999). Discourse patterns and collaborative scientific reasoning in peer and teacher-guided discussions. Cognition and Instruction, 17(4), 379–432.

    Google Scholar 

  • Hong, H. Y., Chen, B., & Chai, C. S. (2016). Exploring the development of college students' epistemic views during their knowledge building activities. Computers & Education, 98, 1–13.

    Google Scholar 

  • Hong, H. Y., & Chiu, C. H. (2016). Understanding how students perceive the role of ideas for their knowledge work in a knowledge-building environment. Australasian Journal of Educational Technology, 32(1).

  • Howe, C., Tolmie, A., & Rodgers, C. (1990). Physics in the primary school: Peer interaction and the understanding of floating and sinking. European Journal of Psychology of Education, 5(4), 459–475.

    Google Scholar 

  • Howe, C., Tolmie, A., & Rodgers, C. (1992). The acquisition of conceptual knowledge in science by primary school children: Group interaction and the understanding of motion down an incline. British Journal of Developmental Psychology, 10(2), 113–130.

    Google Scholar 

  • Hsi, S., & Hoadley, C. M. (1997). Productive discussion in science: Gender equity through electronic discourse. Journal of Science Education and Technology, 6(1), 23–36.

    Google Scholar 

  • Hynd, C., & Alvermann, D. E. (1986). The role of refutation text in overcoming difficulty with science concepts. Journal of Reading, 29(5), 440–446.

    Google Scholar 

  • Iding, M. K., Crosby, M. E., Auernheimer, B., & Klemm, E. B. (2009). Web site credibility: Why do people believe what they believe? Instructional Science, 37, 43–63. https://doi.org/10.1007/s11251008-9080-7.

    Google Scholar 

  • Johnson, P. (1998). Progression in Children's Understanding of a ‘Basic’ Particle Theory: A Longitudinal Study. International Journal of Science Education, 20(4), 393–412. https://doi.org/10.1080/0950069980200402.

    Google Scholar 

  • Kang, H., Scharmann, L. C., Kang, S., & Noh, T. (2010). Cognitive Conflict and Situational Interest as Factors Influencing Conceptual Change. International Journal of Environmental and Science Education, 5(4), 383–405.

    Google Scholar 

  • Kang, S., Scharmann, L. C., & Noh, T. (2004). Reexamining the Role of Cognitive Conflict in Science Concept Learning. Research in Science Education, 34(1), 71–96. https://doi.org/10.1023/B:RISE.0000021001.77568.b3.

    Google Scholar 

  • Kapur, M., Voiklis, J., & Kinzer, C. K. (2008). Sensitivities to early exchange in synchronous computer supported collaborative learning (CSCL) groups. Computers and Education, 51(1), 54–66.

  • Kazemi, E., & Stipek, D. (2001). Promoting conceptual thinking in four upper-elementary mathematics classrooms. Elementary School Journal, 102, 59–80.

    Google Scholar 

  • Keil, F. C. (2006). Explanation and understanding. Annual Review of Psychology, 57, 227–254.

    Google Scholar 

  • Kennedy, C. A., Brown, NJS, Draney, K. & Wilson, M. (2005). Using progress variables and embedded assessment to improve teaching and learning. Annual meeting of the American Education Research Association, in Montreal, Canada.

  • Knudson, R. E. (1992). The development of written argumentation: An analysis and comparison of argumentative writing at four grade levels. Child Study Journal, 22(3), 167–184.

  • Koschmann, T. (2003). CSCL, argumentation, and Deweyan inquiry. In Arguing to learn (pp. 261–269). Springer, Dordrecht.

  • Kuhn, D. (1989). Children and adults as intuitive scientists. Psychological Review, 96(4), 674.

    Google Scholar 

  • Kuhn, D. (1991). The skills of argument. Cambridge, England: Cambridge University Press.

    Google Scholar 

  • Kuhn, D., Garcia-Mila, M., Zohar, A., & Andersen, C. (1995). Strategies of knowledge acquisition. Monographs of the Society for Research in Child Development, 60(4, Serial No. 245).

  • Kuhn, D., & Pearsall, S. (2000). Developmental origins of scientific thinking. Journal of Cognition and Development, 1(1), 113–129.

    Google Scholar 

  • Ladd, B. C. (2003). It's all writing: Experience using rewriting to learn in introductory computer science. Journal of Computing Sciences in Colleges, 18(5), 57–64.

    Google Scholar 

  • Latour, B., & Woolgar, S. (2013). Laboratory life: The construction of scientific facts. Princeton University Press.

  • Leitão, S. (2003). Evaluating and selecting counterarguments: Studies of children's rhetorical awareness. Written Communication, 20(3), 269–306.

  • Lemke, J. (1990). Talking science: Language, learning and values. Norwood: Ablex.

    Google Scholar 

  • Linn, M. C., & Eylon, B.-S. (2011). Science Learning and Instruction: Taking Advantage of Technology to Promote Knowledge Integration. New York: Routledge.

    Google Scholar 

  • Linn, M. C. & Hsi, S. (2000). Computers, teachers, peers: Science learning partners. Psychology Press.

  • Mayer, R. E. (2002). Multimedia learning. Psychology of Learning and Motivation, 41, 85–139.

    Google Scholar 

  • Liu, O. L., Lee, H. S., & Linn, M. C. (2011). Measuring knowledge integration: Validation of four-year assessments. Journal of Research in Science Teaching, 48(9), 1079–1107.

    Google Scholar 

  • Liu, X., & Lesniak, K. (2006). Progression in Children’s Understanding of the Matter Concept from Elementary to High School. Journal of Research in Science Teaching, 43(3), 320–347. https://doi.org/10.1002/(ISSN)1098-2736.

    Google Scholar 

  • Lombardi, D., Bickel, E. S., Bailey, J. M., & Burrell, S. (2018). High school students’ evaluations, plausibility (re) appraisals, and knowledge about topics in Earth science. Science Education, 102(1), 153–177.

    Google Scholar 

  • Matuk, C. F. & King Chen, J. (2011). The WISE Idea Manager: A Tool to Scaffold the Collaborative Construction of Evidence-Based Explanations from Dynamic Scientific Visualizations. In, Proceedings of the 9th International Conference on Computer Supported Collaborative Learning CSCL2011: Connecting computer supported collaborative learning to policy and practice, July 4–8, 2011. The University of Hong Kong, Hong Kong, China.

  • Matuk, C. F. & Linn, M. C. (2013, April 27–May 1). Technology integration to scaffold and assess students use of visual evidence in science inquiry. Paper presented at the American Educational Research Association Meeting (AERA2013): Education and Poverty: Theory, Research, Policy and Praxis, San Francisco, CA, USA.

  • Matuk, C. & Linn, M. C. (2015). Examining the real and perceived impacts of a public idea repository on literacy and science inquiry. In CSCL’15: Proceedings of the 11th International Conference for Computer Supported Collaborative Learning, (Vol. 1, pp. 150–157). Gothenburg, Sweden: International Society of the Learning Sciences.

  • Matuk, C., McElhaney, K. W., Chen, J. K., Lim-Breitbart, J., Kirkpatrick, D., & Linn, M. C. (2016). Iteratively Refining a Science Explanation Tool Through Classroom Implementation and Stakeholder Partnerships. International Journal of Designs for Learning, 7(2).

  • Matuk, C., McElhaney, K., Miller, D., King Chen, J., Lim-Breitbart, J., Terashima, H., Kwan, G., & Linn, M.C. (2013). Reflectively prototyping a tool for exchanging ideas. In CSCL’13: Proceedings of the 10th International Conference on Computer Supported Collaborative Learning, (Vol. 2, pp. 101–104). Madison, WI, 2013. International Society of the Learning Sciences.

  • Mayer, R. E. (1984). Aids to text comprehension. Educational Psychologist, 19(1), 30–42.

  • McElhaney, K., Miller, D., Matuk, C., & Linn, M. C. (2012). Using the Idea Manager to promote coherent understanding of inquiry investigations. In ICLS'12: Proceedings of the 10th International Conference for the Learning Sciences, (Vol. 1, pp. 323–330). Sydney: International Society of the Learning Sciences.

  • McGrew, S., Breakstone, J., Ortega, T., Smith, M., & Wineburg, S. (2018). Can students evaluate online sources? Learning from assessments of civic online reasoning. Theory & Research in Social Education, 1–29.

  • McNeill, K. L., Lizotte, D. J., Krajcik, J., & Marx, R. W. (2006). Supporting students' construction of scientific explanations by fading scaffolds in instructional materials. The Journal of the Learning Sciences, 15(2), 153–191.

    Google Scholar 

  • McNeill, K. L., & Krajcik, J. (2008). Inquiry and scientific explanations: Helping students use evidence and reasoning. Science as inquiry in the secondary setting, 121–134.

  • McNeill, K. L., & Pimentel, D. S. (2010). Scientific discourse in three urban classrooms: The role of the teacher in engaging high school students in argumentation. Science Education, 94(2), 203–229.

    Google Scholar 

  • Mercer, N., Wegerif, R., & Dawes, L. (1999). Children's talk and the development of reasoning in the classroom. British Educational Research Journal, 25(1), 95–111.

    Google Scholar 

  • Metzger, M. J., Flanagin, A. J., & Medders, R. B. (2010). Social and heuristic approaches to credibility evaluation online. Journal of Communication, 60(3), 413–439.

    Google Scholar 

  • Miles, M. B., Huberman, A. M., & Saldaña, J. (2014). Qualitative data analysis: A method sourcebook. CA, US: Sage Publications.

    Google Scholar 

  • Mittlefehldt, S. & Grotzer, T. (2003). Using metacognition to facilitate the transfer of causal models in learning density and pressure. National Association of Research in Science Teaching Conference. Philadelphia, PA.

  • Mortimer, E., & Scott, P. (2003). Meaning making in secondary science classrooms. Maidenhead: Open University Press.

  • Morse, J. M., Barrett, M., Mayan, M., Olson, K., & Spiers, J. (2002). Verification strategies for establishing reliability and validity in qualitative research. International Journal of Qualitative Methods, 1(2), 13–22.

    Google Scholar 

  • Moskaliuk, J., Kimmerle, J., & Cress, U. (2012). Collaborative knowledge building with wikis: The impact of redundancy and polarity. Computers & Education, 58(4), 1049–1057, ISSN 0360-1315. https://doi.org/10.1016/j.compedu.2011.11.024.

    Google Scholar 

  • NGSS Lead States. (2013). Next Generation Science Standards: For States, By States. Washington, DC: The National Academies Press.

    Google Scholar 

  • Nussbaum, E. M., & Kardash, C. M. (2005). The effects of goal instructions and text on the generation of counterarguments during writing. Journal of Educational Psychology, 97, 157–169.

    Google Scholar 

  • O’Donnell, A. M., & Dansereau, D. F. (1992). Scripted cooperation in student dyads: A method for analyzing and enhancing academic learning and performance. Interaction in cooperative groups: The theoretical anatomy of group learning, 120–141.

  • O’Keefe, D. J. (1999). How to handle opposing arguments in persuasive messages: A meta-analytic review of the effects of one-sided and two-sided messages. Annals of the International Communication Association, 22(1), 209–249.

  • Osborne, J., Erduran, S., & Simon, S. (2004). Enhancing the quality of argumentation in school science. Journal of Research in Science Teaching, 41, 994–1020.

    Google Scholar 

  • O’Connor, M. C., Michaels, S., & Chapin, S. H. (2015). “Scaling down” to explore the role of talk in learning: From district intervention to controlled classroom study. In L. B. Resnick, C. Asterhan, & S. N. Clarke (Eds.), Socializing Intelligence Through Talk and Dialogue. Washington, DC: American Educational Research Association.

    Google Scholar 

  • Osborne, J. (2010). Arguing to learn in science: The role of collaborative, critical discourse. Science, 328(5977), 463–466.

    Google Scholar 

  • Palinscar, A. S., & Brown, A. L. (1984). Reciprocal teaching of comprehension-fostering and comprehension-monitoring activities. Cognition and Instruction, 1(2), 117–175.

    Google Scholar 

  • Pan, B., Hembrooke, H., Joachims, T., Lorigo, L., Gay, G., & Granka, L. (2007). In Google we trust: Users’ decisions on rank, position, and relevance. Journal of Computer-Mediated Communication, 12, 801–823. https://doi.org/10.1111/j.1083-6101.2007.00351.x.

    Google Scholar 

  • Perkins, D. N. (1987). Reasoning as it is and could be: An empirical perspective. In D. M. Topping, D. C. Crowell, & V. N. Kobayashi (Eds.), Thinking across cultures: The third international conference on thinking (pp. 175–194). Hillsdale: Erlbaum.

    Google Scholar 

  • Perkins, D. N., Farady, M., & Bushey, B. (1991). Everyday reasoning and the roots of intelligence. In J. F. Voss, D. N. Perkins, & J. W. Segal (Eds.), Informal reasoning and education (pp. 83–105). Hillsdale: Lawrence Erlbaum Associates, Inc..

  • Piaget, J., & Inhelder, B. (1974). The Child’s Construction of Quantities: Conservation and Atomism. London: Routledge and Kegan Paul.

    Google Scholar 

  • Rau, M. A., Bowman, H. E., & Moore, J. W. (2017). An adaptive collaboration script for learning with multiple visual representations in chemistry. Computers & Education, 109, 38–55.

  • Roscoe, R. D., & Chi, M. (2008). Tutor learning: The role of instructional explaining and responding to questions. Instructional Science, 36(4), 321–350.

    Google Scholar 

  • Rowe, M. B. (1974). Relation of wait-time and rewards to the development of language, logic, and fate control: Part II-Rewards. Journal of Research in Science Teaching, 11(4), 291–308.

    Google Scholar 

  • Ruiz-Primo, M. A., & Furtak, E. M. (2007). Exploring teachers’ informal formative assessment practices and students’ understanding in the context of scientific inquiry. Journal of Research in Science Teaching, 44(1), 57–84.

    Google Scholar 

  • Rummel, N., & Spada, H. (2005). Learning to collaborate: An instructional approach to promoting collaborative problem solving in computer-mediated settings. The Journal of the Learning Sciences, 14(2), 201–241.

    Google Scholar 

  • Ryoo, K., & Linn, M. C. (2016). Designing automated guidance for concept diagrams in inquiry instruction. Journal of Research in Science Teaching, 53(7), 1003–1035.

    Google Scholar 

  • Sampson, V., Grooms, J., & Walker, J. P. (2011). Argument-driven inquiry as a way to help students learn how to participate in scientific argumentation and craft written arguments: An exploratory study. Science Education, 95, 217–257. https://doi.org/10.1002/sce.20421.

    Google Scholar 

  • Sandelowski, M. (2010). What's in a name? Qualitative description revisited. Research in Nursing & Health, 33(1), 77–84.

    Google Scholar 

  • Sandoval, W. A., & Millwood, K. A. (2005). The quality of students' use of evidence in written scientific explanations. Cognition and Instruction, 23(1), 23–55.

    Google Scholar 

  • Scardamalia, M. (2002). Collective cognitive responsibility for the advancement of knowledge. In B. Smith (Ed.), Liberal education in a knowledge society (pp. 76–98). Chicago: Open Court.

    Google Scholar 

  • Scardamalia, M., & Bereiter, C. (2014). Knowledge building and knowledge creation: Theory, pedagogy, and technology. Cambridge Handbook of the Learning Sciences, 397–417.

  • Scardamalia, M., & Bereiter, C. (2006). Knowledge building: Theory, pedagogy, and technology. The Cambridge Handbook of the Learning Sciences, 97–115.

  • Scardamalia, M., & Bereiter, C. (1994). Computer support for knowledge-building communities. Journal of the Learning Sciences, 3(3), 265–283.

    Google Scholar 

  • Scardamalia, M., Bereiter, C., McLean, R. S., Swallow, J., & Woodruff, E. (1989). Computer supported intentional learning environments. Journal of Educational Computing Research, 5, 51–68.

    Google Scholar 

  • Schauble, L. (1996). The development of scientific reasoning in knowledge-rich contexts. Developmental Psychology, 32(1), 102.

    Google Scholar 

  • Schellens, T., Van Keer, H., De Wever, B., & Valcke, M. (2007). Scripting by assigning roles: Does it improve knowledge construction in asynchronous discussion groups? International Journal of Computer-Supported Collaborative Learning, 2, 225–246.

    Google Scholar 

  • Schwarz, B. B., Neuman, Y., & Biezuner, S. (2000). Two wrongs may make a right… if they argue together! Cognition and Instruction, 18(4), 461–494.

    Google Scholar 

  • Shavelson, R. J., Young, D. B., Ayala, C. C., Brandon, P. R., Furtak, E. M., Ruiz-Primo, M. A., Tomita, M. K., & Yin, Y. (2008). On the Impact of Curriculum-embedded Formative Assessment on Learning: A Collaboration between Curriculum and Assessment Developers. Applied Measurement in Education, 21(4), 295–314. https://doi.org/10.1080/08957340802347647.

    Google Scholar 

  • Siegler, R. S. (2002). Microgenetic studies of self-explanation. Microdevelopment: Transition processes in development and learning, 31–58.

  • Silver, E. A., Ghousseini, H., Gosen, D., Charalambous, C., & Strawhun, B. T. F. (2005). Moving from rhetoric to praxis: Issues faced by teachers in having students consider multiple solutions for problems in the mathematics classroom. The Journal of Mathematical Behavior, 24(3–4), 287–301.

    Google Scholar 

  • Simon, D., & Holyoak, K. J. (2002). Structural dynamics of cognition: From consistency theories to constraint satisfaction. Personality and Social Psychology Review, 6(4), 283–294.

  • Simon, S., Erduran, S., & Osborne, J. (2006). Learning to teach argumentation: Research and development in the science classroom. International Journal of Science Education, 28(2–3), 235–260.

    Google Scholar 

  • Skoumios, M. (2009). The effect of sociocognitive conflict on students’ dialogic argumentation about floating and sinking. International Journal of Environmental and Science Education, 4(4), 381–399.

    Google Scholar 

  • Slotta, J. D., Chi, M. T., & Joram, E. (1995). Assessing students' misclassifications of physics concepts: An ontological basis for conceptual change. Cognition and Instruction, 13(3), 373–400.

    Google Scholar 

  • Slotta, J. D., & Linn, M. C. (2009). WISE science: Web-based inquiry in the classroom. Teachers College Press.

  • Smith, C., Carey, S., & Wiser, M. (1985). On Differentiation: A Case Study of the Development of the Concepts of Size, Weight, and Density. Cognition, 21(3), 177–237. https://doi.org/10.1016/0010-0277(85)90025-3.

    Google Scholar 

  • Smith, C., Maclin, D., Grosslight, L., & Davis, H. (1997). Teaching for Understanding: A Study of Students’ Preinstruction Theories of Matter and a Comparison of the Effectiveness of Two Approaches to Teaching about Matter and Density. Cognition and Instruction, 15(3), 317–393.

    Google Scholar 

  • Smith, C., Snir, J., & Grosslight, L. (1992). Using Conceptual Models to Facilitate Conceptual Change: The Case of Weight-density Differentiation. Cognition and Instruction, 9(3), 221–283. https://doi.org/10.1207/s1532690xci0903_3.

    Google Scholar 

  • Stanford, C., Moon, A., Towns, M., & Cole, R. (2016). Analysis of Instructor Facilitation Strategies and Their influences on student argumentation: A Case Study of a process Oriented Guided inquiry learning physical chemistry classroom. Journal of Chemical Education, 93(9), 1501–1513.

    Google Scholar 

  • Tao, P.-K., & Gunstone, R. F. (1999). Conceptual change in science through collaborative learning at the computer. International Journal of Science Education, 21(1), 39–57.

    Google Scholar 

  • Tirosh, D., & Stavy, R. (1999). Intuitive Rules: A Way to Explain and Predict Students’ Reasoning. Educational Studies in Mathematics, 38(1/3), 51–66. https://doi.org/10.1023/A:1003436313032.

    Google Scholar 

  • Toth, E. E., Suthers, D. D., & Lesgold, A. M. (2002). “Mapping to know”: The effects of representational guidance and reflective assessment on scientific inquiry. Science Education, 86(2), 264–286.

    Google Scholar 

  • Toulmin, S. (1958). The uses of argument. Cambridge: Cambridge University Press.

    Google Scholar 

  • van Boxtel, C., van der Linden, J., & Kanselaar, G. (2000). Collaborative learning tasks and the elaboration of conceptual knowledge. Learning and Instruction, 10, 311–330.

    Google Scholar 

  • Veenman, S., Denessen, E., van den Akker, A., & van der Rijt, J. (2005). Effects of a cooperative learning program on the elaborations of students during help seeking and help giving. American Educational Research Journal, 42, 115–151.

    Google Scholar 

  • Vitale, J., Applebaum, L., & Linn, M. (2017). Individual Versus Shared Design Goals in a Graph Construction Activity. Philadelphia: International Society of the Learning Sciences.

    Google Scholar 

  • Vogel, F., Wecker, C., Kollar, I., & Fischer, F. (2017). Socio-cognitive scaffolding with computer-supported collaboration scripts: A meta-analysis. Educational Psychology Review, 29(3), 477–511.

    Google Scholar 

  • Walraven, A., Brand-Gruwel, S., & Boshuizen, H. (2009). How students evaluate information and sources when searching the world wide web for information. Computers & Education, 52, 234–246. https://doi.org/10.1016/j.compedu.2008.08.003.

    Google Scholar 

  • Wang, C. Y. (2015). Scaffolding middle school students’ construction of scientific explanations: Comparing a cognitive versus a metacognitive evaluation approach. International Journal of Science Education, 37(2), 237–271.

    Google Scholar 

  • Warner, L. B. (2008). How do students’ behaviors relate to the growth of their mathematical ideas? Journal of Mathematical Behavior, 27(3), 206–227.

    Google Scholar 

  • Webb, N. M., Franke, M. L., Ing, M., Wong, J., Fernandez, C. H., Shin, N., & Turrou, A. C. (2014). Engaging with others’ mathematical ideas: Interrelationships among student participation, teachers’ instructional practices, and learning. International Journal of Educational Research, 63, 79–93.

    Google Scholar 

  • Webb, N. M., Troper, J. D., & Fall, R. (1995). Constructive activity and learning in collaborative small groups. Journal of Educational Psychology, 87(3), 406–423.

    Google Scholar 

  • Wecker, C., & Fischer, F. (2014). Where is the evidence? A meta-analysis on the role of argumentation for the acquisition of domain-specific knowledge in computer-supported collaborative learning. Computers & Education, 75, 218–228.

    Google Scholar 

  • Weinberger, A., Ertl, B., Fischer, F., & Mandl, H. (2005). Epistemic and social scripts in computer–supported collaborative learning. Instructional Science, 33(1), 1–30.

    Google Scholar 

  • Weinberger, A., Stegmann, K., & Fischer, F. (2007). Knowledge convergence in collaborative learning: Concepts and assessment. Learning and Instruction, 17(4), 416–426.

  • Weinstein, C. E., & Mayer, R. E. (1986). The teaching of learning strategies. In M. Wittrock (Ed.), Handbook of Research on Teaching (pp. 315–327). New York: Macmillan.

  • Westerwick, A. (2013). Effects of sponsorship, web site design, and Google ranking on the credibility of online information. Journal of Computer-Mediated Communication, 18, 194–211. https://doi.org/10.1111/jcc4.12006.

    Google Scholar 

  • Whitebread, D., Bingham, S., Grau, V., Pino Pasternak, D., & Sangster, C. (2007). Development of metacognition and self-regulated learning in young children: Role of collaborative and peer-assisted learning. Journal of Cognitive Education and Psychology, 6(3), 433–455.

    Google Scholar 

  • Wittrock, M. C. (1990). Generative processes of comprehension. Educational Psychologist, 24(4), 345–376.

    Google Scholar 

  • Yang, S. J., & Chen, I. Y. (2008). A social network-based system for supporting interactive collaboration in knowledge sharing over peer-to-peer network. International Journal of Human-Computer Studies, 66(1), 36–50.

    Google Scholar 

  • Zhang, M., & Quintana, C. (2012). Scaffolding strategies for supporting middle school students’ online inquiry processes. Computers & Education, 58(1), 181–196.

    Google Scholar 

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Acknowledgements

A preliminary version of this analysis was presented at ICLS 2014. Portions of this manuscript are owned by the International Society for the Learning Sciences (ISLS). ISLS has granted the authors permission to reuse these portions for publication.

Funding

Funding for this research was provided by a DR K-12 award from the National Science Foundation [grant #1119670].

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Matuk, C., Linn, M.C. Why and how do middle school students exchange ideas during science inquiry?. Intern. J. Comput.-Support. Collab. Learn 13, 263–299 (2018). https://doi.org/10.1007/s11412-018-9282-1

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