Abstracts
Résumé
Les simulations adisciplinaires présentent les mêmes caractéristiques que les autres simulations informatiques, sauf qu’elles ne sont associées à aucun référent ou phénomène particulier. Nous proposons d’abord un modèle des processus qu’effectuent les concepteurs et les usagers en rapport avec une simulation, ce qui permet de cerner les conditions conférant à la simulation un caractère disciplinaire (ou non), du point de vue de chacun de ces acteurs. Nous décrivons ensuite les versions successives, de moins en moins disciplinaires, d’une simulation que nous avons développée et expérimentée dans un cours d’épistémologie s’adressant à de futurs enseignants. Nous présentons enfin, comme résultats d’une recherche exploratoire, les caractéristiques des démarches de résolution de problème que nous avons observées dans une activité d’apprentissage ouverte fondée sur cette simulation.
Mots-clés:
- simulation informatique,
- résolution de problèmes,
- apprentissage ouvert,
- épistémologie
Abstract
Domain-independent simulations share the same characteristics as usual computer simulations, with the exception of being related to no particular referent or phenomenon. We first propose a model of the processes followed respectively by designers and end-users of a simulation, which reveals the conditions that make a simulation domain dependent (or not) from the perspective of each of these actors. We then present the successive, less and less domain-dependent, versions of a simulation we developed and tested in a university-level epistemology course intended for prospective teachers. Finally, we describe the main characteristics of the problem-solving processes we observed among these students, engaged in an open-ended learning activity based upon this simulation.
Keywords:
- computer simulation,
- problem-solving,
- open-ended learning,
- epistemology
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Appendices
Références
- Alessi, S. M. (1988). Fidelity in the design of instructional simulations. Journal of Computer-Based Instruction, 15, 40-47.
- Anderson, D. E. (1982). Computer simulations in the psychology laboratory. Simulation & Gaming, 13, 13-36.
- Blech, C. et Funke, J. (2005). Dynamis review: An overview about applications of the Dynamis approach in cognitive psychology. Récupéré le 24 mai 2008 du site du German Institute for Adult Education (DIE), http://www.die-bonn.de/esprid/dokumente/doc-2005/blech05_01.pdf
- Breuer, K., Molkenthin, R. et Tennyson, R. D. (2006). Role of simulation in Web-based learning. Dans H. F. O’Neil et R. S. Perez (2006), Web-based learning: Theory, research, and practice (p. 307-326). Mahwah, NJ : Lawrence Erlbaum.
- Cobb, P., Confrey, J., DiSessa, A., Lehrer, R. et Schauble, L. (2003). Design experiments in educational research. Educational Researcher, 32, 2-10.
- de Castell, S. et Jenson, J. (2007). Digital games for education: When meanings play. Intermedialities, 9, 113-132.
- de Jong, T. (2006). Technological advances in inquiry learning. Science, 312(5773), 532-533.
- de Jong, T. et van Joolingen, W. R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research, 68(2), 179-201.
- Design-Based Research Collective. (2003). Design-based research: An emerging paradigm for educational inquiry. Educational Researcher, 32(1), 5-8.
- Gijlers, H. et de Jong, T. (2005). The relation between prior knowledge and students’ collaborative discovery learning processes. Journal of Research in Science Teaching, 42(3), 264-282.
- Grossman, M. et Walter, D. (1978). Teaching with interactive computer capabilities (PLATO: Computer-based education for animal breeding). Journal of Dairy Science, 61, 1308-1311.
- Hays, R. T. et Singer, M. J. (1989). Simulation fidelity in training system design: Bridging the gap between reality and training. New York : Springer-Verlag.
- Johnson, A., Moher, T., Cho, Y., Edelson, R. et Russell, E. (2004). Learning science inquiry skills in a virtual field. Computers & Graphics, 8(3), 409-416.
- Jungck, J. R. (1991). Constructivism, computer exploratoriums, and collaborative learning: Constructing scientific knowledge. Teaching Education, 3(2), 151-170.
- Klopfer, E., Colella, V. et Resnick, M. (2002). New paths on a StarLogo adventure. Computers & Graphics, 26, 615-622.
- Kluge, A. (2008). Performance assessments with microworlds and their difficulty. Applied Psychological Measurement, 32(2),156-180.
- Kuhn, T. S. (1962). The structure of scientific revolutions. Chicago : University of Chicago Press.
- Larochelle, M. et Désautels, J. (1992). Autour de l’idée de science. Itinéraires cognitifs d’étudiants et d’étudiantes. Sainte-Foy, Canada : Presses de l’Université Laval.
- Lehti, S., Lehtinen, E. et Murtonen, M. (2005). Computer-supported problem-based learning in the research methodology domain. Scandinavian Journal of Educational Research, 49(3), 297-323.
- Lewis, R. et Bullock, P. (1972). Computing. Physics Education, 7, 457-459.
- Maxwell, N. L., Mergendoller, J. R. et Bellisimo, Y. (2004). Developing a problem-based learning simulation: An economics unit on trade. Simulation & Gaming, 35(4), 488-498.
- Mayer, R. E. et Wittrock, M. C. (1996). Problem-solving transfer. Dans D. C. Berliner et R. C. Calfee (dir.), Handbook of educational psychology (p. 47-62). New York : Simon & Schuster Macmillan.
- Meisner, G. et Hoffman, H. (2005). Virtual interactive laboratories and e-learning. Dans G. Richards (dir.), Proceedings of world conference on E-learning in corporate, government, healthcare, and higher education 2005 (p. 120-127). Chesapeake, VA : AACE.
- Meyor, C. (2006). Mise en scène de la subjectivité dans un contexte académique : de la vue de l’esprit au regard. Collection du Cirp, 2, 41-60 : http://www.cirp.uqam.ca/diffusion_collection_vol2.php
- Meyor, C. et Couture, M. (2007). Conception et expérimentation pédagogique de simulations informatiques adisciplinaires. Dans Actes du congrès Actualité de la recherche en éducation et en formation (AREF) 2007 : http://www.congresintaref.org/index.php?cont_id=8
- Morin, E. (1992). La méthode – 3. La connaissance de la connaissance. Paris : Seuil.
- Nadeau, R. et Désautels, J. (1984). Épistémologie et didactique des sciences. Ottawa : Conseil des sciences du Canada.
- Reid, D. J., Zhang, J. et Chen, Q. (2003). Supporting scientific discovery learning in a simulation environment. Journal of Computer Assisted Learning, 19(1), 9-20.
- Rendas, A., Rosado Pinto, P. et Gamboa, T. (1999). A computer simulation designed for problem-based learning. Medical Education, 33(1), 47-54.
- Rieber, L. P. (2002). Supporting discovery-based learning with simulations. Dans R. Ploetzner (dir.), Proceedings of the international workshop on dynamic visualizations and learning. Tübingen, Knowledge Media Research Center.
- Rieber, L. P. (2004). Microworlds. Dans D. H. Jonassen (dir.), Handbook of research on educational communications and technology (2e éd., p. 583-603). Mahwah, NJ : Lawrence Erlbaum.
- Rieber, L. P. (2005). Multimedia learning in games, simulations, and microworlds. Dans R. E. Mayer (dir.), The Cambridge handbook of multimedia learning (p. 549-567). New York : Cambridge University Press.
- Rivers, R. H. et Vockell, E. (1987). Computer simulations to stimulate scientific problem solving. Journal of Research in Science Teaching, 24, 403-415.
- Rouse, W. B., Rouse, S. H., Hunt, R. M., Johnson, W. B. et Pelligrino S. J. (1980). Human decision-making in computer-aided fault diagnosis (Technical Report 434). Alexandria, VA : US Army Research Institute for the Behavioral and Social Sciences.
- Sauvé, L., Renaud, L., Kaufman, D. et Marquis, J. S. (2007). Distinguishing between games and simulations: A systematic review. Educational Technology & Society, 10(3), 247-256.
- Soderberg, P. et Price, F. (2003). An examination of problem-based teaching and learning in population genetics and evolution using EVOLVE, a computer simulation. InternationalJournal of Science Education, 25(1), 35-55.
- Tennyson, R. D. et Breuer, K. (2002). Improving problem solving and creativity through use of complex-dynamic simulations. Computers in Human Behavior, 18(6), 650-668.
- van Joolingen, W. R., de Jong, T. et Dimitrakopoulos, A. (2007). Issues in computer supported inquiry learning in science. Journal of Computer Assisted Learning, 23, 111-120.
- Vogel, J. J., Vogel, D. S., Cannon-Bowers, J., Bowers, C. A., Muse, K. et Wright, M. (2006). Computer gaming and interactive simulations for learning: A meta-analysis. Journal of Educational Computing Research, 34(3), 229-243.
- White, B. Y. (1993). ThinkerTools: Causal models, conceptual change, and science education. Cognition and Instruction, 10(1), 1-100.
- Windschitl, M. et Andre, T. (1998). Using computer simulations to enhance conceptual change: The roles of constructivist instruction and student epistemological beliefs. Journal of Research in Science Teaching, 35(2), 145-160.