A framework for developing intelligent tutoring systems incorporating reusability

El-Sheikh, Eman; Sticklen, Jon

doi:10.1007/3-540-64582-9_787

Cited by 9 publications

(3 citation statements)

References 9 publications

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“…Thanks to these designed capabilities, an ITS can coach students in problem-solving; examples are Guidon in medicine (Clancey, 1987), Andes in physics (Gertner and VanLehn, 2000), TIGE in cost engineering (Morin, 1998), or the various tutors developed at Carnegie Mellon University (Anderson, 1986). Thus, ITSs were proven to be highly effective as learning aids and many ITS research and development efforts are still taking place (El-Sheikh and Sticklen, 1998).…”

Section: Intelligent Tutoring Systems Are Usefulmentioning

confidence: 99%

Like pedagogical design, educational system design can benefit from a framework-oriented approach

Lelouche

2008

IJCEELL

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Instructional designers and teachers, at all levels of education and training, try to put in common, to share and to reuse the practices affecting their pedagogical design and expertise. However, the instructional environment, and in particular the design and development of educational systems, can benefit from similar knowledge sharing, especially because of the difficulty, length and cost of this development process. In this paper, we aim to show how building educational systems can be more effective and beneficial using a frameworkoriented approach. To do so, we describe different levels of abstraction in the design and the development of an Intelligent Tutoring System (ITS). We first recall what an ITS is, showing its advantages and drawbacks, and identifying different knowledge types. To tackle the limitations of the ITS construction, we then propose to build a framework, including guidelines and tools to ease its development. We finally show that a collaborative framework-oriented approach is indeed feasible, describing how to build such a framework. We thus try to promote reusability and extensibility in many aspects of the design and development of ITSs.

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Section: Intelligent Tutoring Systems Are Usefulmentioning

confidence: 99%

Like pedagogical design, educational system design can benefit from a framework-oriented approach

Lelouche

2008

IJCEELL

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“…From the system viewpoint, an ITS can be divided into five core conceptual components [14]: the Expert Model representing the domain knowledge; the Domain Model containing the knowledge about the actual teaching material; the Student Model storing learners' profile like, for instance, details about the learner's current problem-solving state and long-term knowledge progress, which are essential for adapting the experience; the Pedagogical (Tutor or Tutoring) Model providing the knowledge to tailor the selection and the provisioning of the teaching elements according to the student model; the Communication (User Interface) Model enabling the interactions between learner and system. Nkambou et al [15] discuss the architectures of ITS.…”

Section: Introductionmentioning

confidence: 99%

Building Ontology-Driven Tutoring Models for Intelligent Tutoring Systems Using Data Mining

et al. 2020

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Pedagogical (Tutor or Tutoring) Models are an important element of Intelligent Tutoring Systems (ITS) and they can be described by sets of (tutoring) rules. The implementation of a Tutoring Model includes both the formal representation of the aforementioned rules and a mechanism able to interpret such representation and execute the rules. One of the most suitable approaches to formally represent pedagogical rules is to construct semantic web ontologies that are highly interoperable and can be integrated with other models in an ITS like the subject domain and the student model. However, the main drawback of semantic web-based approaches is that they require a considerable human effort to prepare and build relevant ontologies. This paper proposes a novel approach to maintain the benefits of the semantic web-based approach in representing pedagogical rules for an ITS, while overcoming its main drawback by employing a data mining technique to automatically extract rules from real-world tutoring sessions and represent them by means of Web Ontology Language (OWL). INDEX TERMS Classification rule mining, intelligent tutoring systems, ontologies, pedagogical rules, semantic web, web ontology language (OWL).

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“…Apontam-se na literatura duas razões principais. Uma está relacionada ao fato de que o desenvolvimento de um STI é difícil, demorado e custoso (El-Sheikh e Sticklen, 2002). A segunda refere-se à carência de um STI genérico, onde os seus componentes possam ser reutilizados para diferentes bases de conhecimento (Murray, 1999;Bruzilovsky, 1994;Clancey e Joerger, 1988).…”

Section: Introductionunclassified

Representação de Conhecimentos Centrada em Modelos para o Uso em Ambientes Complexos de Aprendizagem

Pianezzola

Mondadori

Fróes

et al. 2006

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As técnicas de Inteligência Artificial têm sido largamente empregadas na educação, especialmente para o desenvolvimento de sistemas tutores inteligentes. Estessistemas têm sido, entretanto, objeto de crítica por parte dos pedagogos por não se enquadrarem na orientação construtivista. Neste ensaio parte-se deste aspecto fundamental em busca de uma formulação para o problema da representação dos conhecimentos no âmbito dos ambientes complexos de aprendizagem. Propõe-se uma estrutura para a representação de conhecimentos centrada em modelos. Um exemplo ilustra o processo de aprendizagem baseado na estrutura proposta, que compreende a elucidação progressiva do problema através da confrontação de conhecimentos pessoais com conhecimentos teóricos e técnicos. A abordagem desenvolvida tem como objetivo a construção de ambientes efetivos de aprendizagem em Administração.

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A framework for developing intelligent tutoring systems incorporating reusability

Cited by 9 publications

References 9 publications

Like pedagogical design, educational system design can benefit from a framework-oriented approach

Like pedagogical design, educational system design can benefit from a framework-oriented approach

Building Ontology-Driven Tutoring Models for Intelligent Tutoring Systems Using Data Mining

Representação de Conhecimentos Centrada em Modelos para o Uso em Ambientes Complexos de Aprendizagem

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