Q-SEE: Qualitative Simulation Support System in Economic Education
Tokuro Matsuo*, Masaki Komatsu*, Takayuki Ito*,**,
and Toramatsu Shintani*
*Graduate School of Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, Aichi 466-8555, Japan
**Division of Engineering and Applied Science, Harvard University, 33 Oxford Street, Cambridge 02446, USA
In this paper, we present a support method of economic learning system based on qualitative simulation. We employ qualitative simulations because this lets the learners can understand the conceptual principles in economic dynamics. In existing learning system with qualitative simulation, users are not supported effectively in building qualitative simulation model. To solve the problem, we propose a support process and methods based on users condition. In our system, users conditions are classified into 4 phases. Based on the phases, our system helps users make qualitative simulation model step by step. Furthermore, our system supports users through making partial-adjacent relationships/graph model and supports users displaying errors about inconsistency and incorrect rule when there are inconsistency and mistaken relationship in the graph model made by users. The work focuses on interactively helping a learner to develop a qualitative model of an economic system as a teaching tool. The system has three key advantages. (1) Our system supports users’ learning based on condition and process in which users make simulation models. (2) Users can make qualitative simulation model without their confusion because it is easy for users to make the model with consistency, propriety and adequacy using our system. (3) Users can make qualitative simulation model effectively because users can understand the detail and all over the model using our support system. The contributions of this paper are mainly showing the support process and support method in building qualitative simulation model.
-  N. Agell, and C. J. Aguado, “A hybrid qualitative-quantitative classification technique applied to aid marketing decisions,” In the proceedings of 11th International Workshop on Qualitative Reasoning, 2001.
-  B. Bredeweg, and K. Forbus, “Qualitative modeling in education,” AI magazine, Vol.24(4), 2004.
-  B. Bredeweg, and R. Winkels, “Qualitative models in interactive learning environments,” Interactive Learning Environments, Vol.5, 1998.
-  S. A. Chen, J. Wang, and C. S. Yang, “Constructing internet futures exchange for teach-ing derivatives trading in financial markets,” In the proceedings of International Conference on Computers in Education, Vol.2, pp. 1392-1395, 2002.
-  K. D. Forbus, K. Carney, R. Harris, and B. L. Sherin, “A qualitative modeling environment for middle-school students: A progress report,” In the proceedings of 11th International Workshop on Qualitative Reasoning, pp. 17-19, 2001.
-  K. Forbus, K. Carney, B. Sherin, and L. Ureel, “Vmodel: A visual qualitative modeling environment for middle-school students,” In the 16th Innovative Applications of Artificial Intelligence Conference, 2004.
-  K. D. Forbus, “Helping children become qualitative modelers,” Journal of the Japanese Society for Artificial Intelligence, Vol.17(4), 2002.
-  S. Hata, T. Ohkawa, and N. Komoda, “Backward simulation method in qualitative simulation,” IEEJ Transactions on Electronics, Information and Systems, Institute of Electrical Engineers of Japan, Vol.115-C(11), 1995.
-  B. Kuipers, “Qualitative Reasoning,” The MIT Press, 1994.
-  T. Matsuo, and T. Shintani, “A qualitative/quantitative methodsbased e-learning support system in economic education,” In the 19th National Conference on Artificial Intelligence (AAAI-2004), 2004.
-  R. S. G. Weir, “The rigours of on-line student assessment lessons from e-commerce,” In the proceedings of International Conference on Computers in Education, Vol.2, pp. 840-843, 2002.
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