Generating Qualitative Causal Graph using Modeling Constructs of Qualitative Process Theory for Explaining Organic Chemistry Reactions
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 33093
Generating Qualitative Causal Graph using Modeling Constructs of Qualitative Process Theory for Explaining Organic Chemistry Reactions

Authors: Alicia Y. C. Tang, Rukaini Abdullah, Sharifuddin M. Zain, Noorsaadah A. Rahman

Abstract:

This paper discusses the causal explanation capability of QRIOM, a tool aimed at supporting learning of organic chemistry reactions. The development of the tool is based on the hybrid use of Qualitative Reasoning (QR) technique and Qualitative Process Theory (QPT) ontology. Our simulation combines symbolic, qualitative description of relations with quantity analysis to generate causal graphs. The pedagogy embedded in the simulator is to both simulate and explain organic reactions. Qualitative reasoning through a causal chain will be presented to explain the overall changes made on the substrate; from initial substrate until the production of final outputs. Several uses of the QPT modeling constructs in supporting behavioral and causal explanation during run-time will also be demonstrated. Explaining organic reactions through causal graph trace can help improve the reasoning ability of learners in that their conceptual understanding of the subject is nurtured.

Keywords: Qualitative reasoning, causal graph, organicreactions, explanation, QPT, modeling constructs.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1077851

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1418

References:


[1] K. Forbus, and D. Gentner, "Qualitative mental models: Simulations or memories?" Proc. of the 11th International workshop on qualitative reasoning, Cortona, Italy, 1997.
[2] I. Iwasaki, "Real-world applications of qualitative reasoning", IEEE Expert, 1997, pp. 16-21.
[3] K. Forbus, P. Whalley, J. Everett, L. Ureel, M. Brokowski, J. Baher, and S. Kuehne, "CyclePad: an articulate virtual laboratory for engineering thermodynamics," Artificial Intelligence Journal, Vol. 114 , 1999, pp. 297-347.
[4] A. Bouwer, and B. Bredeweg, "VisiGarp: graphical representation of qualitative simulation models," in: J.D. Moore, G. Luckhardt Redfield, J.L. Johnson (Eds.), Artificial Intelligence in Education: AI-ED in the Wired and Wireless Future, Amsterdam, The Netherlands, 2001, pp. 294-305.
[5] S.M.F.D. Syed Mustapha, J.S. Pang, and S.M. Zain, "Application of Qualitative Process Theory to Qualitative Simulation and Analysis of Inorganic Chemical Reaction", Proc. of the 16th International Workshop of Qualitative Reasoning, Barcelona, Spain, 2002.
[6] S.M.F.D. Syed Mustapha, J.S. Pang, and S.M. Zain, "QALSIC: towards building an articulate educational software using qualitative process theory approach in inorganic chemistry for high school level," International Journal of Artificial Intelligence in Education, 15 (3): 229-257, 2005.
[7] G. Biswas, D. Schwartz, J. Bransford, and The Teachable Agents Group at Vanderbilt, "Technology Support for Complex Problem Solving: From SAD Environment to AI", in K. Forbus, and P. Feltovich, (Eds.), Smart Machines in Education, Menlo Park Calif.: AAAI Press, pp. 71- 97, 2001.
[8] I. Bratko, and D. Suc, "Qualitative explanation of controllers", Proc. of the 16th International Workshop on Qualitative Reasoning, June 10-12, Barcelona, Spain, 2002, pp. 1-2.
[9] I. Bratko, and D. Suc, "Learning Qualitative Models", AI Magazine 24(4): 107-119, 2003.
[10] LHASA research group home page. Available: http://derek.harvard.edu/.
[11] D. P. Dolata, "Artificial intelligence in Chemistry", Ohio University, Athens, OH, USA, 1993.
[12] K. Forbus, "Qualitative process theory," Artificial Intelligence, Vol. 24, 1984, pp. 85-168.
[13] Y.C. Alicia Tang, and S.M.F.D. Syed Mustapha, "Representing SN1 reaction mechanism using the qualitative process theory," in: C. Bailey- Kellogg, B. Kuipers, (Eds.), Proc. of the 20th International Workshop on Qualitative Reasoning, Hanover, USA, 2006, pp. 137-147.
[14] K. Forbus, "Articulate software for science and engineering education", in K. Forbus, P. Feltovich, and A. Canas (Eds), Smart machines in education: the coming revolution in educational technology, AAAI Press, 2001.
[15] D. Gentner, and A. Stevens, "Mental models", IEA Associates, 1983.
[16] B. Bredeweg, and K. Forbus, "Qualitative modeling in education," AI Magazine, 24(4): 35-46, 2003.
[17] D.E. Penner, "Cognition, Computers and Synthetic Science: Building knowledge and meaning through modeling", Review of research in education, 25: 1-36, 2001.
[18] Amzi! Prolog Home Page. Available: http://www.amzi.com