ICONKAT: an integrated constructivist knowledge acquisition tool

Ford, Kenneth M.; Cañas, Alberto J.; Jones, Jeremy; Stahl, H. Phillip; Novak, Joseph D.; Adams–Webber, Jack

doi:10.1016/1042-8143(91)90005-8

Cited by 57 publications

(31 citation statements)

References 11 publications

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“…Para Ausubel, Novak e Hanesian (1978, p.159) "o aprendizado significativo acontece quando uma informação nova é adquirida mediante um esforço deliberado por parte do aluno em conectar a nova informação com os conceitos ou com as proposições relevantes que preexistem em sua estrutura cognitiva". De acordo com Ford et al (1991), esses conceitos ou proposições são definidos como registros de fenômenos que foram associados a um específico sistema retirado da realidade. Entendemos que, na aprendizagem significativa, os alunos adquirem as informações e as habilidades necessárias para a resolução de situações-problema através da interação dos mesmos com os demais alunos e com os professores que estão envolvidos no processo de ensino-aprendizagem, deflagrado no ambiente de aprendizagem da modelagem.…”

Section: A Modelagem Matemática Como Um Ambiente De Aprendizagemunclassified

A modelagem como um ambiente de aprendizagem para a conversão do conhecimento matemático

Rosa

Orey

2012

Bolema

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ResumoA investigação da modelagem como um ambiente de aprendizagem para a construção do conhecimento matemático está se tornando predominante nos meios acadêmicos. Esse ambiente facilita uma estrutura pedagógica que promove a identificação e a disseminação de ambos os conhecimentos, explícito e tácito, dos alunos, através do estudo e da codificação das ideias matemáticas presentes nos sistemas retirados da realidade. Neste artigo, discutimos as principais características da conversão dos conhecimentos matemáticos, explícito e tácito, através da utilização do ambiente de aprendizagem da modelagem.Palavras-chave: Modelagem Matemática. Conhecimento Tácito. Conhecimento Explícito. Ambiente de Aprendizagem. Conhecimento Matemático.

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Section: A Modelagem Matemática Como Um Ambiente De Aprendizagemunclassified

A modelagem como um ambiente de aprendizagem para a conversão do conhecimento matemático

Rosa

Orey

2012

Bolema

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“…Such methods do not find a one-sided implication relationship, it is not possible to infer that one construct entails another one or an element. In response to this limitation, some researchers have focused on clarifying the logical rationale underlying constructivist knowledge acquisition and they develop procedures for the logical analysis of construct entailment [7], [14]- [16] that are used in automatic knowledge acquisition tools [17].…”

Section: Limitations Current Repertory Gridsmentioning

confidence: 99%

“…When all the values have been introduced, the values and of each fuzzy value are determined on the basis of the values [ , ] of its right and left neighbor values. For example, the expert affirms that the teacher applies a lot of classroom practices, and she/he set out its core to [17,20]. After, the expert estimate will the value of the teacher , the parameters and of this value will be determined from the a few and too much values to 13 and 25 respectively.…”

Section: A First Example How the Frt Workmentioning

confidence: 99%

Fuzzy Repertory Table: A Method for Acquiring Knowledge About Input Variables to Machine Learning Algorithm

Castro-Schez

Castro

Zurita

2004

IEEE Trans. Fuzzy Syst.

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Abstract-In this paper, we develop a technique for acquiring the finite set of attributes or variables which the expert uses in a classification problem for characterising and discriminating a set of elements. This set will constitute the schema of a training data set to which an inductive learning algorithm will be applied. The technique developed uses ideas taken from psychology, in particular from Kelly's Personal Construct Theory. While we agree that Kelly's repertory grid technique is an efficient way to do this, it has several disadvantages which we shall try to solve by using a fuzzy repertory table. With the suggested technique, we aim to obtain the set of attributes and values which the expert can use to "measure" the object type (class) on the classification problem in some way. We will also acquire some general rules to identify the expert's evident knowledge; these rules will comprise concepts belonging to their conceptual structure.Index Terms-Expert systems, fuzzy repertory grid, knowledge acquisition, knowledge-based systems.

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“…Now we have come to realize that work in automated knowledge acquisition addresses the problem of designing appropriate representations and procedures to facilitate creation, validation, verification, and maintenance of knowledge bases over the lifetime of a knowledge-based system (cf. Ford et al, 1990c). Thus, it might be said that researchers are attempting to do for knowledge engineering what CASE is doing for traditional software engineering Gaines, 1988) Commercial expert system shell vendors have begun to realize the need for knowledge acquisition capabilities and many have been claiming to provide such support within their tools.…”

Section: What Is a Knowledge Acquisition Tool?mentioning

confidence: 99%

“…Shaw and Gaines (1988), for instance, have developed a methodology for analyzing areas of consensus, conflict, correspondence, and contrast between the conceptual systems of two or more experts. Many knowledge acquisition tools have also been integrated with consultation systems, making extensive performance testing of the system possible (e.g., Shema & Boose, 1988;Ford et al, 1990c;Gaines & Rappaport, 1989).…”

Section: Interviewing Techniques a Number Of Interviewing Techniquesmentioning

confidence: 99%

Knowledge acquisition techniques for decision analysis using AXOTL and AQUINAS

Bradshaw¹,

Convington²,

Russo³

et al. 1991

Knowledge Acquisition

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The effective application of current decision tree and influence diagram software requires a relatively high level of sophistication in the theory and practice of decision analysis.Research on intelligent decision systems aims to lower the cost and amount of training required to use these methods through the use of knowledge-based systems; however, application prototypes implemented to date have required time-consuming and tedious handcrafting of knowledge bases. This paper describes the development of DDUCKS, an "open architecture" problem-modeling environment that integrates components from Axotl, a knowledge-based decision analysis workbench, with those of Aquinas, a knowledge acquisition workbench based on personal construct theory. The knowledge base tools in Axotl can be configured with knowledge to provide guidance and help in formulating, evaluating, and refining decision models represented in influence diagrams. Knowledge acquisition tools in DDUCKS will allow the knowledge to be efficiently modeled, more easily maintained, and thoroughly tested. INTRODUCTION Progress in Automated Decision AnalysisThe Boeing Company has an urgent need for advanced automated decision support applications. Rapid growth in the complexity of strategic and tactical decisions has outstripped the capacity of conventional decision aids. (Langlotz, Shortliffe, and Fagan, 1986). Finally, knowledge-based system development environments do not generally provide facilities for integrating historical data with expert judgment (Spiegelhalter, Franklin, and Bull, 1990).One of the most promising approaches to dealing with decision complexity in a consistent, general-purpose manner is decision analysis (Howard, 1966;Keeney & Raiffa, 1976;Raiffa, 1968). In the past few years, researchers and developers have made important theoretical advances and have implemented several successful systems for automated support of the decision analysis process (reviews by Horvitz, Breese, & Henrion, 1988;Pearl, 1988;Neapolitan, 1990). Although a thorough discussion is beyond the scope of this paper, we wish to review three of the important developments that have led to the current state of the art. Following this, we will explain why we think that the development of automated knowledge acquisition tools is crucial to the future of efforts to deliver decision analysis methodology to a wider spectrum of decision makers and domains.Decision tree software. The development of decision tree software ( Figure 1) represented an important milestone in automated decision analysis support (Olmsted, 1982;McNamee & Celona, 1987). Through the use of general-purpose commercial tools, decision analysis techniques have become more widely known and used than ever before. At the same time,there are several drawbacks to the use of decision trees as a representation device. For one thing, they grow exponentially with problem size, making them impractical for problems of significant size. Additionally, the tree metaphor for decision problems often leads participants t...

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ICONKAT: an integrated constructivist knowledge acquisition tool

Cited by 57 publications

References 11 publications

A modelagem como um ambiente de aprendizagem para a conversão do conhecimento matemático

A modelagem como um ambiente de aprendizagem para a conversão do conhecimento matemático

Fuzzy Repertory Table: A Method for Acquiring Knowledge About Input Variables to Machine Learning Algorithm

Knowledge acquisition techniques for decision analysis using AXOTL and AQUINAS

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