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Support options provided and required for modeling with DynaLearn—A case study

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Abstract

Science educators strongly advocate the importance of scientific modeling within science education. Although widely advocated for students, modeling is a complex task involving integration of topics, “languages” and abstraction levels. Thus support for the modeling task and for developing modeling skills is required. The goal of our study was to explore how novice modelers use several support options while performing modeling assignments with DynaLearn—an intelligent learning environment for qualitative modeling. The support options differ by the type of support, the presentation of the support, the relation to previous support, the adaptation to the learner and timing. Findings are expected to influence modifications and further development of support methods as well as providing guidelines for effective teaching using DynaLearn. Additional contributions of the study are insights on how novice modelers approach a modeling task, what type of support they are looking for, how they use each of the different support types, and what kind of instructional interventions might be required.

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References

  • Azevedo, R., Cromley, J. G., & Seibert, D. (2004). Does adaptive scaffolding facilitate students’ ability to regulate their learning with hypermedia? Contemporary Educational Psychology, 29, 344–370.

    Article  Google Scholar 

  • Beek, W., & Bredeweg, B. (2011). Diagnosis and assessment. DynaLearn, EC FP7 STREP project 231526, Deliverable D3.4.

  • Beek, W., Bredeweg, B., & Latour, S. (2011). Context-dependent help for the DynaLearn modelling and simulation workbench. In G. Biswas, et al. (Eds.), Proceedings of Artificial Intelligence in Education 15th International Conference, AIED 2011, Auckland, New Zealand, June 28–July 2011, pp. 420–422, Springer, Heidelberg.

  • Bouwer, A., & Bredeweg, B. (2010). Graphical means for inspecting qualitative models of system behaviour. Instructional Science, 38(2), 173–208.

    Article  Google Scholar 

  • Bredeweg, B., & Struss, P. (2003). Current topics in qualitative reasoning (editorial introduction). AI Magazine, 24(4), 13–16.

    Google Scholar 

  • Bredeweg, B., Linnebank, F., Bouwer, A., & Liem, J. (2009). Garp3—workbench for qualitative modelling and simulation. Ecological Informatics, 4(5–6), 263–281.

    Article  Google Scholar 

  • Bredeweg, B., Liem, J., Beek, W., Salles, P., & Linnebank, F. (2010). Learning spaces as representational scaffolds for learning conceptual knowledge of system behaviour. In M. Wolpers, P.A. Kirschner, M. Scheffel, S. Lindstaedt, & V. Dimitrova (Eds.), Lecture Notes in Computer Science, Volume 6383, 2010, Sustaining TEL: From Innovation to Learning and Practice. 5th European Conference on Technology Enhanced Learning, EC-TEL 2010, p47–61, Barcelona, Spain, September 28–October 1, 2010.

  • Elshout, J. J., Veenman, M. V. J., & Van Hall, J. G. (1993). Using the computer as a help tool during learning by doing. Computer and Education, 21(1–2), 115–122.

    Article  Google Scholar 

  • Forbus, K. D., Carney, K., Sherin, B. L., & Ureel, L. C. (2005). VModel: a visual qualitative modeling environment for middle-school students. AI Magazine, 26(3), 63–72.

    Google Scholar 

  • Gentner, D., Loewenstein, J., & Thompson, L. (2003). Learning and transfer: a general role for analogical encoding. Journal of Educational Psychology, 95(2), 393–408.

    Article  Google Scholar 

  • Gracia, J., Liem, J., Lozano, E., Corcho, O., Trna, M., Gómez-Pérez, A., et al. (2010). Semantic Techniques for Enabling Knowledge Reuse in Conceptual Modelling. Proc. of 9th International Semantic Web Conference, Shanghai (China), Springer, volume 6414, November 2010.

  • Hammersley, M., & Gomm, R. (2000). Introduction. In R. Gomm, M. Hammersley, & P. Foster (Eds.), Case study method (pp. 1–16). London: Sage.

    Google Scholar 

  • Hmelo-Silver, C. E., Duncan, R. G., & Chinn, C. A. (2007). Scaffolding and achievement in problem-based and inquiry learning: a response to Kirschner, Sweller, and Clark (2006). Educational Psychologist, 42(2), 99–107.

    Article  Google Scholar 

  • Lobato, J. (2006). Alternative perspectives on the transfer of learning: history, issues, and challenges for future research. Journal of the Learning Sciences, 15, 431–449.

    Article  Google Scholar 

  • Lozano, E., Gracia, J., Liem, J., Gómez-Pérez, A., & Bredeweg, B. (2011). Semantic feedback for the enrichment of conceptual models. K-CAP’11, June 26–29, 2011, Banff, Alberta, Canada.

  • Mehlmann, G., Häring, M., Bühling, R., Wißner, M., & André, E. (2010). Multiple agent roles in an adaptive virtual classroom environment. In Proc. of the 10th Int. Conf. on Intelligent Virtual Agents (pp. 250–256). Springer.

  • Muldner, K., & Conati, C. (2010). Scaffolding meta-cognitive skills for effective analogical problem solving via tailored example selection. International Journal of Artificial Intelligence in Education, 20(2), 99–136.

    Google Scholar 

  • Palincsar, A. S. (1998). Keeping the metaphor of scaffolding fresh—a response to C. Addison Stone’s “The metaphor of scaffolding: Its utility for the field of learning disabilities.”. Journal of Learning Disabilities, 31, 370–373.

    Article  Google Scholar 

  • Quintana, C., Reiser, B. J., Davis, E. A., Krajcik, J., Fretz, E., Duncan, R. G., et al. (2004). A scaffolding design framework for software to support science inquiry. Journal of the Learning Sciences, 13(3), 337–386.

    Article  Google Scholar 

  • Reed, S. K., Dempster, A., & Ettinger, M. (1985). Usefulness of analogous solutions for solving algebra word problems. Journal of Experimental Psychology: Learning, Memory and Cognition, 11, 106–125.

    Article  Google Scholar 

  • Schwartz, C. V., Reizer, B., Davis, E. A., Kenyon, L., Acher, A., Fortus, D., et al. (2009). Developing a learning progression for scientific modeling: making scientific modeling accessible and meaningful for learners. Journal of Research in Science Teaching, 46(6), 632–654.

    Article  Google Scholar 

  • Schwarz, C. V., & White, B. Y. (2005). Metamodeling knowledge: developing students’ understanding of scientific modeling. Cognition and Instruction, 23(2), 165–205.

    Article  Google Scholar 

  • Sins, P. H. M., Savelsbergh, E. R., & van Joolingen, W. R. (2005). The difficult process of scientific modeling: an analysis of novices’ reasoning during computer-based modeling. International Journal of Science Education, 27(14), 1695–1721.

    Article  Google Scholar 

  • Soloway, E., Guzdial, M., & Hay, K. E. (1994). Learner-centered design: the challenge for HCI in the 21st century. Interactions, 1, 36–48.

    Article  Google Scholar 

  • Stone, C. A. (1998). The metaphor of scaffolding: its utility for the field of learning disabilities. Journal of Learning Disabilities, 31, 344–364.

    Article  Google Scholar 

  • Wagner, J. F. (2010). A transfer-in-pieces consideration of the perception of structure in the transfer of learning. The Journal of the Learning Sciences, 19, 443–479.

    Article  Google Scholar 

  • Wilensky, U., & Reisman, K. (2006). Thinking like a wolf, a sheep, or a firefly: learning biology through constructing and testing computational theories—an embodied modeling approach. Cognition and Instruction, 24(2), 171–209.

    Article  Google Scholar 

  • Windschitl, M., Thompson, J., & Braaten, M. (2008). Beyond the scientific method: model-based inquiry as a new paradigm of preference for school science investigations. Science Education, 92(5), 941–967.

    Article  Google Scholar 

  • Wißner, M., Bühling, R., Linnebank, F., Beek, W., & André, E. (2011). Integrated characters with dialogue and tutorial strategies. DynaLearn, EC FP7 STREP project 231526, Deliverable D5.4.

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Acknowledgements

The work presented in this paper is co-funded by the EC within the 7th FP, Project no. 231526, and Website: http://www.DynaLearn.eu.

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Correspondence to Rachel Or-Bach.

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The study was conducted while the first author was on Sabbatical leave with the University of Amsterdam.

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Or-Bach, R., Bredeweg, B. Support options provided and required for modeling with DynaLearn—A case study. Educ Inf Technol 18, 621–639 (2013). https://doi.org/10.1007/s10639-012-9194-z

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