Deriving causal explanation from qualitative model reasoning

This paper discusses a qualitative simulator QRiOM that uses Qualitative Reasoning (QR) technique, and a process-based ontology to model, simulate and explain the behaviour of selected organic reactions. Learning organic reactions requires the application of domain knowledge at intuitive level, whic...

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Main Authors: Tang, A.Y.C., Zain, S.M., Rahman, N.A., Abdullah, R.
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Published: 2018
Online Access:http://dspace.uniten.edu.my/jspui/handle/123456789/9808
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spelling my.uniten.dspace-98082018-03-06T03:49:54Z Deriving causal explanation from qualitative model reasoning Tang, A.Y.C. Zain, S.M. Rahman, N.A. Abdullah, R. This paper discusses a qualitative simulator QRiOM that uses Qualitative Reasoning (QR) technique, and a process-based ontology to model, simulate and explain the behaviour of selected organic reactions. Learning organic reactions requires the application of domain knowledge at intuitive level, which is difficult to be programmed using traditional approach. The main objective of QRiOM is to help learners gain a better understanding of the fundamental organic reaction concepts, and to improve their conceptual comprehension on the subject by analyzing the multiple forms of explanation generated by the software. This paper focuses on the generation of explanation based on causal theories to explicate various phenomena in the chemistry subject. QRiOM has been tested with three classes problems related to organic chemistry, with encouraging results. This paper also presents the results of preliminary evaluation of QRiOM that reveal its explanation capability and usefulness. 2018-03-06T03:49:54Z 2018-03-06T03:49:54Z 2009 http://dspace.uniten.edu.my/jspui/handle/123456789/9808
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description This paper discusses a qualitative simulator QRiOM that uses Qualitative Reasoning (QR) technique, and a process-based ontology to model, simulate and explain the behaviour of selected organic reactions. Learning organic reactions requires the application of domain knowledge at intuitive level, which is difficult to be programmed using traditional approach. The main objective of QRiOM is to help learners gain a better understanding of the fundamental organic reaction concepts, and to improve their conceptual comprehension on the subject by analyzing the multiple forms of explanation generated by the software. This paper focuses on the generation of explanation based on causal theories to explicate various phenomena in the chemistry subject. QRiOM has been tested with three classes problems related to organic chemistry, with encouraging results. This paper also presents the results of preliminary evaluation of QRiOM that reveal its explanation capability and usefulness.
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author Tang, A.Y.C.
Zain, S.M.
Rahman, N.A.
Abdullah, R.
spellingShingle Tang, A.Y.C.
Zain, S.M.
Rahman, N.A.
Abdullah, R.
Deriving causal explanation from qualitative model reasoning
author_facet Tang, A.Y.C.
Zain, S.M.
Rahman, N.A.
Abdullah, R.
author_sort Tang, A.Y.C.
title Deriving causal explanation from qualitative model reasoning
title_short Deriving causal explanation from qualitative model reasoning
title_full Deriving causal explanation from qualitative model reasoning
title_fullStr Deriving causal explanation from qualitative model reasoning
title_full_unstemmed Deriving causal explanation from qualitative model reasoning
title_sort deriving causal explanation from qualitative model reasoning
publishDate 2018
url http://dspace.uniten.edu.my/jspui/handle/123456789/9808
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score 13.160551