Abstract
Liquid retaining structures, which are mainly used to retain domestic water, sewage, or industrial waste, are usually constructed with reinforced concrete in Hong Kong. During the design, novice engineers often encounter problems including decision-making based on rules of thumb, judgment, previous experience, heuristics, and code of practice. A computer-aided tool that incorporates engineering judgment along with algorithmic tools is highly desirable. This paper presents an intelligent tutoring system, with hybrid knowledge representation techniques including production rule system and object-oriented approach, which provides expert advice on design of liquid retaining structures. Intelligent tutoring system is a type of knowledge-based expert system with the particular purpose of teaching. It can serve the purpose for one-to-one tutoring, which is generally acknowledged to be the most effective teaching method, yet requiring high ratio of resources. This system is based on British Standards Code of Practice BS8007: 1987: Design of concrete structures for retaining aqueous liquids. Training exercises, learner model as well as tailored explanations on real design practice are furnished to help inexperienced designers or civil engineering students to learn how to design liquid retaining structures. Nowadays, with the popularity of personal computer, civil engineering students as well as novice engineers can glean hand-on knowledge on design of liquid retaining structures more effectively through this system. An evaluation of the developed system and investigation of the effectiveness to learn the domain design knowledge are undertaken.
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© 2002 Springer-Verlag Berlin Heidelberg
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Chau, K.W., Albermani, F., Chan, S.L. (2002). Development of an Intelligent Tutoring System on Design of Liquid Retaining Structures. In: McKay, B., Slaney, J. (eds) AI 2002: Advances in Artificial Intelligence. AI 2002. Lecture Notes in Computer Science(), vol 2557. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36187-1_63
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DOI: https://doi.org/10.1007/3-540-36187-1_63
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