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Type: Conference paper
Title: Revisiting Ill-definedness and the consequences for ITSs
Author: Mitrovic, A.
Weerasinghe, A.
Citation: International Journal of Computer Research, 2009, vol.200, iss.1, pp.375-382
Publisher: IOS Press
Issue Date: 2009
Series/Report no.: Frontiers in Artificial Intelligence and Applications; 200
ISBN: 9781607500285
ISSN: 0922-6389
Conference Name: 14th International Conference on Artificial Intelligence in Education (6 Jul 2009 - 10 Jul 2009 : Brighton, United Kingdom)
Statement of
Antonija Mitrovic, Amali Weerasinghe
Abstract: ITSs for ill-defined domains have attracted a lot of attention recently, which is well-deserved, as such ITSs are hard to develop. The first step towards such ITSs is reaching a wide agreement about the terminology used in the area. In this paper, we discuss the two important dimensions of ill-definedness: the domain and the instructional task. By the domain we assume declarative domain knowledge, or the domain theory, while the instructional task is the task the student is learning, in terms of problem-solving skills. It is possible to have a well-defined domain and still have ill-defined instructional tasks in the same domain. We look deeper at the features of ill-defined tasks, which all contribute to their ill/well defined nature. The paper discusses model-tracing and constraint-based modeling, in terms of their suitability for ill-defined tasks and domains. We show that constraint-based modeling can be used in both well- and illdefined domains, and illustrate our conclusion using several instructional tasks.
Rights: Copyright status unknown
DOI: 10.3233/978-1-60750-028-5-375
Appears in Collections:Aurora harvest 2
Computer Science publications

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