Abstract
I aim to show that learning with this modeling based Educational Learning System (ELS) can accomplish the target of achieving higher order knowledge. The ELS is a system consisting of internal and external elements. The external prerequisites consist of technical and physical elements and the internal ones are shaped by the students pre-knowledge and the instructors teaching competencies including his/her social, emotional, and disciplinary knowledge necessary for teaching. The ELS is based on a theoretical framework of different theories and models such as concept mapping, elaboration of mental models, cognitive tool-approach, and self-regulated learning (SRL). Different features for visualization and modeling of the subject matter to be learned can be chosen by the students as well as the frequencies using the simulation feature to receive feedback to the model constructed. This enables the students to work self-regulated because of the feedback of the system, by providing the simulation results in desired graphical or analytical representation formats. The notation of the ELS, the symbols themselves are considered as an intuitive language because the symbols are connected to real world phenomena. It is assumed that the expression of knowledge is co-determined by the applied language. It is concluded that a less differentiated language does not hinder thinking but does not support thinking as a ‘cognitive tool’. Hence the hypothesis is: there are significant differences in the complexity of the expressed knowledge of the students using the notation in comparison to a control group using verbal protocols to express the knowledge acquired.
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References
Alessi, S.: Modeling a system and teaching a system: Enhancing what students learn from modeling. In: Blumschein, P., Hung, W., Jonassen, D., Strobel, J. (eds.) Model-based Approaches to Learning: Using Systems Models and Simulations to Improve Understanding and Problem Solving in Complex Domains, pp. 199–214. Sense Publishers, Rotterdam (2009)
Ausubel, D.P.: The use of advance organizers in the learning and retention of meaningful verbal material. Journal of Educational Psychology 51, 267–272 (1960)
Bandura, A.: Self-efficacy: The exercise of control. W.H. Freeman, New York (1997)
Beck, K., Krumm, V.: Wirtschaftskundlicher Bildungs-Test (WBT). Handanweisung. Hogrefe, Göttingen (1998)
Berendes, K.: Lenkungskompetenz in komplexen ökonomischen Systemen. Wiesbaden, Gabler (2002)
Beschluss der, K.M.K: Rahmenlehrplan für den Ausbildungsberuf Indus-triekaumann/Industriekauffrau, vom. 9 (Juni 1995)
Beschluss der, K.M.K.: Rahmenlehrplan für den Ausbildungsberuf Industriekaufmann/Industriekauffrau, vom. 14 (Juni 2002)
Bliss, J.: From mental models to modeling. In: Mellar, H., Bliss, J., Boohan, R., Ogborn, J., Tompsett, C. (eds.) Learning with Artificial Worlds, pp. 27–32. The Falmer Press, London (1994)
Byrknes, A.H., Myrtveit, M.: Learning dynamic modeling. Powersim Press (1996)
Collins, A.M., Quillian, M.R.: Retrieval time from semantic memory. Journal of Verbal Learning and Verbal Memory 8, 240–247 (1969)
Dann, H.D.: Variationen von Lege-Strukturen zur Wissensrepräsentation. In: Scheele, B. (ed.) Struktur-Lege-Verfahren als Dialog-Konsens-Methodik, pp. 3–38. Aschendorf, Münster (1992)
de Jong, T.: Instruction based on computer simulations. In: Mayer, R.E., Alexander, P.A. (eds.) Handbook of Research on Learning and Instruction, pp. 446–466. Routledge Press, New York (2010)
de Jong, T., van Joolingen, W.R.: Scientific discovery learning with computer simulations of conceptual domains. Review of Educational Research 68, 179–201 (1998)
Dochy, F., Segers, M., Buehl, M.: The relation between assessment practices and out-comes of studies: The case of research on prior knowledge. Review of Educational Research 69, 145–186 (1999)
Dörner, D.: Problemlösen als informationsverarbeitung. Kohlhammer, Stuttgart (1976)
Forrester, J.W.: Grundzüge einer systemtheorie (Principles of systems). Gabler, Wiesbaden (1972)
Forrester, J.W.: Industrial dynamics. Productivity Press, Portland (1961)
Früh, W.: Inhaltsanalyse, theorie und praxis. 5. UVK Verlag, Aufl. Konstanz (2001)
Hillen, S.: The role of worksheets in media based instruction: A didactic and diagnostic approach. In: Hillen, S., Sturm, T., Willbergh, I. (eds.) Challenges Facing Contemporary Didactics, pp. 169–184. Waxmann, Münster (2011)
Hillen, S., Breuer, K., Tennyson, R.: Gaming and learning: Theory, research, and practice. In: Hillen, S., Sturm, T., Willbergh, I. (eds.) Challenges Facing Contemporary Didactics, pp. 1185–1198. Waxmann, Münster (2011)
Hillen, S.: Die Abbildung von qualitäten des wissens zu kaufmännischen sachverhalten ein inhaltsanalytischer Zugang. In: Minnameier, G., Wuttke, E. (eds.) Berufs und wirtschaftspädagogische Grundlagenforschung. Lehr-Lern-Prozesse und Kompetenzdiag-nostik, pp. 377–389. Lang, Festschrift für K. Beck. Frankfurt a. M. (2006a)
Hillen, S.: Zum erwerb generischer erklärungsmuster zu kaufmännischen sachverhalten in orientierung an ein systemdynamisches modellunternehmen. In: bwp@ Berufs und Wirtschaftspädagogik (2006b), http://www.bwpat.de/ausgabe10/hillen_bwpat10.shtml (accessed August 20, 2011)
Hillen, S.: Systemdynamische modellbildung und simulation im kaufmännischen unterricht: Elizitation und elaboration von mentalen modellen in komplexen betrieb-swirtschaftlichen gegenstandsbereichen. Dissertation. Konzepte des Lehrens und Lernens. 10. Peter Lang Verlag, Frankfurt/Main (2004)
Hillen, S., Berendes, K., Breuer, K.: Systemdynamische modellbildung als werkzeug zur visualisierung, Modellierung und diagnose von wissensstrukturen. In: Mandl, H., Fischer, F. (eds.) Wissen sichtbar machen: Begriffsnetze als werkzeuge für das wissensmanagement in lehr- und lernprozessen, pp. 71–89. Hogrefe, Göttingen (2000)
Johnson-Laird, P.N.: The computer and the mind. An introduction to cognitive science. University Press, Cambridge (1988)
Johnson-Laird, P.N.: Mental models: Towards a cognitive science of language, inference and consciousness. University Press, Cambridge (1983)
Jonassen, D.H.: What are cognitive Tools? In: Kommers, P.A.M., Jonassen, D.H., Mayes, J.T. (eds.) Cognitive Tools for Learning, pp. 1–6. Springer, Heidelberg (1991)
Josyula, D.P., Hughes, F.C., Vadali, H., Donahue, B.J., Molla, F., Snowden, M., Miles, J., Kamara, A., Maduka, C.: Metacognition for self-regulated learning in a dynamic environment. In: Proceedings of IEEE SASOW, pp. 261–268 (2010)
Kluwe, R.H.: Cognitive knowledge and executive control: Metacognition. In: Griffin, D. (ed.) Animal Mind – Human Mind. Springer, New York (1982)
Kluwe, R.H., Haider, H.: Modelle zur internen repräsentation komplexer technischer systeme. Sprache und Kognition 9(4), 173–192 (1990)
Kolloffel, B., Eysink, T.H.S., de Jong, T.: The role of external representations in learning combinatorics and probability theory. In: Verschaffel, L., de Corte, E., de Jong, T., Elen, J. (eds.) Use of External Representations in Reasoning and Problem Solving, pp. 169–191. Routledge Press, Abingdon, Ox (2010)
Lajoie, S.P., Azevedo, R.: Teaching and learning in technology-rich environments. In: Alexander, P.A., Winne, P.H. (eds.) Handbook of Educational Psychology, 2nd edn., pp. 803–821. Erlbaum, Mahwah (2006)
Mandl, H., Spada, H.: Wissenspsychologie: Einführung. In: Mandl, H., Spada, H. (eds.) Wissenspsychologie, pp. 1–16. Psychologie Verlags Union, Münche (1988)
MacGregor, S.K.: Hypermedia navigation profiles: Cognitive characteristics and information processing strategies. Journal of Educational Computing Research 20(2), 189–206 (1999)
Molkenthin, R., Breuer, K., Tennyson, R.D.: Real-time diagnostics of problem solving behavior for business simulations. In: Baker, E.L., Dickieson, J., Wulfeck, W., O’Neil, H.F. (eds.) Assessment of Problem Solving Using Simulations, pp. 201–221. Lawrence Erlbaum Associates, London (2008)
Moos, D.C., Azevedo, R.: Self-regulated learning with hypermedia: The role of prior domain knowledge. Contemporary Educational Psychology 33(2), 270–298 (2008)
Norman, D.A.: Cognitive engineering. In: Norman, D.A., Draper, S.W. (eds.) User-Centered Design, pp. 31–62. Erlbaum, Hillsdale (1986)
Norman, D.A.: Some observations on mental models. In: Gentner, D., Stevens, A.L. (eds.) Mental Models, pp. 7–14. Erlbaum, Hillsdale (1983)
Oerter, R.: Psychologie des denkens. Auer, Donauwörth (1971)
Pintrich, P.R.: The role of goal orientation in self-regulated learning. In: Boekaerts, M., Pintrich, P.R., Zeidner, M. (eds.) Handbook of Self-Regulation, pp. 451–502. Academic, San Diego (2000)
PZ-Informationen. Nichtlineare dynamische Systeme und Chaos. Handreichungen zum neuen Lehrplan Physik in der SII, 3. PZ, Bad Kreuznach (2000)
Ryssel, J., Sommer, S., Fürstenau, B., Kunath, J.: The effect of different concept mapping techniques on promoting students’ learning processes in the field of business. In: Canas, A.J., Reiska, P., Ahlberg, M., Novak, J.D. (eds.) Proceedings of CMC Concept Mapping: Connecting Educators, pp. 238–241 (2008)
Salomon, G.: AI in reverse: Computer tools that turn cognitive. Journal of Educational Computing Research 4(2), 123–139 (1988)
Salomon, G., Perkins, D.N., Globerson, T.: Partners in cognition: Extending human intel-ligence with intelligent technologies. Educational Researcher 4, 2–9 (1991)
Scheele, B., Groeben, N.: Dialog-konsens-methoden zur rekonstruktion subjektiver theorien (Structure-laying technique for reconstructing subjective theories ”every day-life”-theories). Francke, Tübingen (1988)
Schunk, D.H., Zimmerman, B.J. (eds.): Self-regulated learning: from teaching to self-reflective practice. Guilford Press, New York (1998)
Simons, P.R.J.: Lernen selbständig zu lernen - ein rahmenmodell. In: Mandl, H., Friedrich, H.F. (eds.) Lern- und denkstrategien: Analyse und intervention, pp. 251–264. Hogrefe, Göttingen (1992)
Spector, J.M., Christensen, D.L., Sioutine, A.V., McCormack, D.: Models and simulations for learning in complex domains: Using causal loop diagrams for assessment and evaluation. Computers in Human Behavior 17, 517–545 (2001)
Sterman, J.D.: Business dynamics: Systems thinking and modeling for a complex world. McGraw-Hill, Boston (2000)
Sweller, J.: Cognitive load during problem solving: Effects on learning. Cognitive Science 12, 257–285 (1988)
Ulrich, H., Probst, G.J.B.: Anleitung zum ganzheitlichen denken und handeln 4. Haupt, Aufl. Wien (1995)
van Borkulo, S.P., van Joolingen, W.R., Savlesbergh, E.R., de Jong, T.: A framework for the assesssment of learning by modeling. In: Blumschein, P., Hung, W., Jonassen, D., Strobel, J. (eds.) Model-based approaches to learning: Using systems models and simulations to improve understanding and problem solving in complex domains, pp. 179–195. Sense Publishers, Rotterdam (2009)
van Joolingen, W.R., Lazonder, A.W., de Jong, T., Savlesbergh, E.R., Manlove, S.: Co-Lab: Research and development of an online learning environment for collaborative scientific discovery learning. Computers in Human Behavior 21, 671–688 (2005)
Vandevelde, S., van Keer, H., de Wever, B.: Exploring the impact of student tutoring on at-risk fifth and sixth graders’ on self-regulated learning. Learning and Individual Differences 21, 419–425 (2011)
Verburgh, L.D.: Participative policy modeling applied to the health care insurance industry. Benda, Nijmegen (1996)
Willerman, M., MacHarg, R.A.: The concept map as an advance organizer. Journal of Research in Science Teaching 28, 705–711 (1991)
Winters, F.I., Greene, J.A., Costich, C.M.: Self-regulation of learning within computer-based learning environments: A critical analysis. Educational Psychology Review 20(4), 429–444 (2008)
Zimmerman, B.J.: Investigating self-regulation and motivation: Historical background, methodological developments and future prospects. American Educational Research Journal 45, 166–183 (2008)
Zimmerman, B.J.: Attaining self-regulation: A social cognitive perspective. In: Boekaerts, M., Pintrich, P.R., Zeidner, M. (eds.) Handbook of self-regulation, pp. 13–39. Academic, San Diego (2000)
Zimmerman, B.J.: Models of self-regulated learning and academic achievement. In: Zimmerman, B.J., Schunk, D.H. (eds.) Self-regulated Learning and Academic Achievement. Theory, Research and Practice, pp. 1–25. Springer, Heidelberg (1989)
Zimmerman, B.J., Schunk, D.H.: Self-regulated learning and academic achievement. Theoretical perspectives, 2nd edn. Laurence Erlbaum Associates, Mahwah (2001)
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Hillen, S.A. (2013). Acquisition of Higher Order Knowledge by a Dynamic Modeling Environment Based on the Educational Concept of Self-Regulated Learning. In: Peña-Ayala, A. (eds) Intelligent and Adaptive Educational-Learning Systems. Smart Innovation, Systems and Technologies, vol 17. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30171-1_16
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