Knowledge organization in intelligent tutoring systems for diagnostic problem solving in complex dynamic domains

Vasandani, V.; Govindaraj, T.

doi:10.1109/21.391288

Cited by 36 publications

(10 citation statements)

References 21 publications

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“…For example, Vasandani and Govindaraj developed an intelligent tutoring system that assists in the organization of system knowledge and operational information in order to enhance operator performance (Vasandani & Govindaraj, 1995); Antao et al presented their experiences in relation to the developing intelligent tutorial systems for teaching simulation in engineering education (Antao, Brodersen, Bourne, & Cantwell, 2000). While computer intelligence has inspired the development of intelligent systems, the advent of network technologies in the mean time has helped the further realization of Intelligent Internet service systems.…”

Section: Literature Reviewmentioning

confidence: 99%

An expert system approach to improving stability and reliability of web service

Tseng¹,

Wu²

2007

Expert Systems with Applications

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Section: Literature Reviewmentioning

confidence: 99%

An expert system approach to improving stability and reliability of web service

Tseng¹,

Wu²

2007

Expert Systems with Applications

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“…Thus, several researchers have developed similar cognitively oriented FRs with similar names, goals, and foci. FRs that share some aspects or elements of our SBF models include Freeman and Newell's (1971) representations of software systems, Reiger and Grinberg's (1978) representations of physical mechanisms, Rasmussen's (1985) structure-behaviorfunction representations of large-scale industrial systems, Gero's function-behavior-structure models (Gero, 1990;Gero et al, 1992;Gero & Kannengiesser, 2004), Umeda and Tomiyama's function-behavior-state models (Umeda et al, 1990(Umeda et al, , 1996Umeda & Tomiyama, 1997), Govindaraj's qualitative approximations of complex systems (Vasandani & Govindaraj, 1995), and Kitamura and Mizoguchi's functionbehavior representations (Sasajima et al, 1996;Kitamura et al, 2002Kitamura et al, , 2004. However, in this article we focus exclusively on the evolution of our SBF models over nearly 30 years.…”

Section: Introductionmentioning

confidence: 99%

A 30-year case study and 15 principles: Implications of an artificial intelligence methodology for functional modeling

Goel

2013

AIEDAM

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Research on design and analysis of complex systems has led to many functional representations with several meanings of function. This work on conceptual design uses a family of representations called structure–behavior–function (SBF) models. The SBF family ranges from behavior–function models of abstract design patterns to drawing–shape–SBF models that couple SBF models with visuospatial knowledge of technological systems. Development of SBF modeling is an instance of cognitively oriented artificial intelligence research that seeks to understand human cognition and build intelligent agents for addressing complex tasks such as design. This paper first traces the development of SBF modeling as our perspective on design evolved from that of problem solving to that of memory and learning. Next, the development of SBF modeling as a case study is used to abstract some of the core principles of an artificial intelligence methodology for functional modeling. Finally, some implications of the artificial intelligence methodology for different meanings of function are examined.

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“…The most common used techniques of domain knowledge representation in adaptive tutoring systems are hierarchies and networks of concepts. A hierarchical knowledge representation is usually used in order to specify the order in which the domain concepts of the learning material have to be taught ( Lin and Ruimin 2011 ; Siddara and Manjunath 2007 ; Vasandani and Govindury 1995 ), and can be implemented through trees ( Kumar 2005 ; Geng et al 2011 ). However, hierarchies do not give information about the dependency relations that exist between the domain concepts.…”

Section: Introductionmentioning

confidence: 99%

A knowledge representation approach using fuzzy cognitive maps for better navigation support in an adaptive learning system

Chrysafiadi

Virvou

2013

SpringerPlus

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In this paper a knowledge representation approach of an adaptive and/or personalized tutoring system is presented. The domain knowledge should be represented in a more realistic way in order to allow the adaptive and/or personalized tutoring system to deliver the learning material to each individual learner dynamically taking into account her/his learning needs and her/his different learning pace. To succeed this, the domain knowledge representation has to depict the possible increase or decrease of the learner’s knowledge. Considering that the domain concepts that constitute the learning material are not independent from each other, the knowledge representation approach has to allow the system to recognize either the domain concepts that are already partly or completely known for a learner, or the domain concepts that s/he has forgotten, taking into account the learner’s knowledge level of the related concepts. In other words, the system should be informed about the knowledge dependencies that exist among the domain concepts of the learning material, as well as the strength on impact of each domain concept on others. Fuzzy Cognitive Maps (FCMs) seem to be an ideal way for representing graphically this kind of information. The suggested knowledge representation approach has been implemented in an e-learning adaptive system for teaching computer programming. The particular system was used by the students of a postgraduate program in the field of Informatics in the University of Piraeus and was compared with a corresponding system, in which the domain knowledge was represented using the most common used technique of network of concepts. The results of the evaluation were very encouraging.

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Knowledge organization in intelligent tutoring systems for diagnostic problem solving in complex dynamic domains

Cited by 36 publications

References 21 publications

An expert system approach to improving stability and reliability of web service

An expert system approach to improving stability and reliability of web service

A 30-year case study and 15 principles: Implications of an artificial intelligence methodology for functional modeling

A knowledge representation approach using fuzzy cognitive maps for better navigation support in an adaptive learning system

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