Development of a Simulator for Explaining Organic Chemical Reactions Based on Qualitative Process Theory
This paper discusses the development of a qualitative
simulator (abbreviated QRiOM) for predicting the behaviour of
organic chemical reactions. The simulation technique is based on the
qualitative process theory (QPT) ontology. The modelling constructs
of QPT embody notions of causality which can be used to explain the
behaviour of a chemical system. The major theme of this work is
that, in a qualitative simulation environment, students are able to
articulate his/her knowledge through the inspection of explanations
generated by software. The implementation languages are Java and
Prolog. The software produces explanation in various forms that
stresses on the causal theories in the chemical system which can be
effectively used to support learning.
[1] A.Y.C. Tang, S.M. Zain, and N.A. Rahman, "Design and Development
of a Qualitative Simulator for Learning Organic Reactions,"
International Journal of Computers, Vol. 3, Issue 1, pp. 96-103, 2009.
[2] K.D. Forbus, "Qualitative Process Theory," Artificial Intelligence, 24:
85-168, 1984.
[3] A. Bouwer and B. Bredeweg, "VisiGarp: Graphical Representation of
Qualitative Simulation Models," In Moore, J.D., Luckhardt Redfield,
G., Johnson, J.L. (eds.) Artificial Intelligence in Education: AI-ED in the
Wired and Wireless Future. IOS Press/Ohmsha, 2001, pp. 294-305,
Japan, Osaka.
[4] A. Bouwer and B. Bredeweg, "Generating Structured Explanations of
System Behaviour Using Qualitative Simulations," Looi, C.K. McCalla,
G., Bredeweg, B. and Breuker, B. (Eds.), Artificial Intelligence in
Education: Supporting Learning through Intelligent and Socially
Informed Technology, 2005, pp. 756-758, IOS press, Amsterdam.
[5] T. Horiguchi and T. Hirashima, "Robust Simulator, a Method of
Simulating Learners' Erroneous Equations for Making Error-Based
Simulation," in Proceedings of the Intelligent Tutoring Systems, 2006,
pp. 655-665.
[6] T. Horiguchi, T. Hirashima, and M. Okamoto, "Conceptual Changes in
Learning Mechanics by Error-based Simulation," in Proceedings of the
International Conference on Computers in Education (ICCE), 2005,
Singapore, pp. 138-145.
[7] T. Hirashima, T. Horiguchi, A. Kashihara, and J. Toyoda, "Error-based
Simulation for Error-visualization and its Management," International
Journal of Artificial Intelligence in Education, vol. 9, pp. 17-31, 1998.
[8] K.D. Forbus, J. Everett, L. Ureel, M. Brokowski, J. Baher, and S.
Kuehne, "Distributed Coaching for an Intelligent Learning
Environment," in Proceedings of International Workshop on Qualitative
Reasoning, 1998, Cape Cod.
[9] K.D. 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, 114: 297-
347, 1999.
[10] K.D. Forbus, "Articulate Software for Science and Engineering
Education," in Forbus, K.D., Feltovich, P., Canas, A. (eds.) Smart
Machines in Education: The Coming Revolution in Educational
Technology, 2001, AAAI Press.
[11] 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," Intl. J.
of AIED, 15(3): 229-257, 2005.
[12] A.Y.C. Tang, S.M.F.D. Syed Mustapha, R. Abdullah, S.M. Zain, and N.
A. Rahman, "Towards automating QPT model construction for reaction
mechanism simulation," in the 21st International Workshop on
Qualitative Reasoning, C. Price and N. Snooke (Eds), June 2007,
Aberystwyth, United Kingdom, pp. 27-29.
[13] A.Y.C. Tang and S.M. Zain, "OntoRM: Ontology for Supporting the
Simulation of Organic Reactions in a Qualitative Reasoning
Environment," in the proceedings of the 2nd International Conference on
Research Challenges in Computer Science, December 2010, Shanghai,
China.
[14] A.Y.C. Tang, S.M. Zain, and R. Abdullah, "Development and
Evaluation of Chemistry Educational Software for Learning Organic
Reactions Using Qualitative Reasoning," Intl. J. of Education and
Information Technologies, Issue 3, Vol. 4, pp. 9-138, 2010.
[1] A.Y.C. Tang, S.M. Zain, and N.A. Rahman, "Design and Development
of a Qualitative Simulator for Learning Organic Reactions,"
International Journal of Computers, Vol. 3, Issue 1, pp. 96-103, 2009.
[2] K.D. Forbus, "Qualitative Process Theory," Artificial Intelligence, 24:
85-168, 1984.
[3] A. Bouwer and B. Bredeweg, "VisiGarp: Graphical Representation of
Qualitative Simulation Models," In Moore, J.D., Luckhardt Redfield,
G., Johnson, J.L. (eds.) Artificial Intelligence in Education: AI-ED in the
Wired and Wireless Future. IOS Press/Ohmsha, 2001, pp. 294-305,
Japan, Osaka.
[4] A. Bouwer and B. Bredeweg, "Generating Structured Explanations of
System Behaviour Using Qualitative Simulations," Looi, C.K. McCalla,
G., Bredeweg, B. and Breuker, B. (Eds.), Artificial Intelligence in
Education: Supporting Learning through Intelligent and Socially
Informed Technology, 2005, pp. 756-758, IOS press, Amsterdam.
[5] T. Horiguchi and T. Hirashima, "Robust Simulator, a Method of
Simulating Learners' Erroneous Equations for Making Error-Based
Simulation," in Proceedings of the Intelligent Tutoring Systems, 2006,
pp. 655-665.
[6] T. Horiguchi, T. Hirashima, and M. Okamoto, "Conceptual Changes in
Learning Mechanics by Error-based Simulation," in Proceedings of the
International Conference on Computers in Education (ICCE), 2005,
Singapore, pp. 138-145.
[7] T. Hirashima, T. Horiguchi, A. Kashihara, and J. Toyoda, "Error-based
Simulation for Error-visualization and its Management," International
Journal of Artificial Intelligence in Education, vol. 9, pp. 17-31, 1998.
[8] K.D. Forbus, J. Everett, L. Ureel, M. Brokowski, J. Baher, and S.
Kuehne, "Distributed Coaching for an Intelligent Learning
Environment," in Proceedings of International Workshop on Qualitative
Reasoning, 1998, Cape Cod.
[9] K.D. 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, 114: 297-
347, 1999.
[10] K.D. Forbus, "Articulate Software for Science and Engineering
Education," in Forbus, K.D., Feltovich, P., Canas, A. (eds.) Smart
Machines in Education: The Coming Revolution in Educational
Technology, 2001, AAAI Press.
[11] 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," Intl. J.
of AIED, 15(3): 229-257, 2005.
[12] A.Y.C. Tang, S.M.F.D. Syed Mustapha, R. Abdullah, S.M. Zain, and N.
A. Rahman, "Towards automating QPT model construction for reaction
mechanism simulation," in the 21st International Workshop on
Qualitative Reasoning, C. Price and N. Snooke (Eds), June 2007,
Aberystwyth, United Kingdom, pp. 27-29.
[13] A.Y.C. Tang and S.M. Zain, "OntoRM: Ontology for Supporting the
Simulation of Organic Reactions in a Qualitative Reasoning
Environment," in the proceedings of the 2nd International Conference on
Research Challenges in Computer Science, December 2010, Shanghai,
China.
[14] A.Y.C. Tang, S.M. Zain, and R. Abdullah, "Development and
Evaluation of Chemistry Educational Software for Learning Organic
Reactions Using Qualitative Reasoning," Intl. J. of Education and
Information Technologies, Issue 3, Vol. 4, pp. 9-138, 2010.
@article{"International Journal of Chemical, Materials and Biomolecular Sciences:55111", author = "Alicia Y. C. Tang and Rukaini Hj. Abdullah and Sharifuddin M. Zain", title = "Development of a Simulator for Explaining Organic Chemical Reactions Based on Qualitative Process Theory", abstract = "This paper discusses the development of a qualitative
simulator (abbreviated QRiOM) for predicting the behaviour of
organic chemical reactions. The simulation technique is based on the
qualitative process theory (QPT) ontology. The modelling constructs
of QPT embody notions of causality which can be used to explain the
behaviour of a chemical system. The major theme of this work is
that, in a qualitative simulation environment, students are able to
articulate his/her knowledge through the inspection of explanations
generated by software. The implementation languages are Java and
Prolog. The software produces explanation in various forms that
stresses on the causal theories in the chemical system which can be
effectively used to support learning.", keywords = "Chemical reactions, explanation, qualitative processtheory, simulation", volume = "5", number = "9", pages = "777-6", }
