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Erschienen in:
2008 | OriginalPaper | Buchkapitel
Soft Computing in Intelligent Tutoring Systems and Educational Assessment
verfasst von : Rodney D. Nielsen, Wayne Ward, James H. Martin
Erschienen in: Soft Computing Applications in Business
Verlag: Springer Berlin Heidelberg
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The need for soft computing technologies to facilitate effective automated tutoring is pervasive – from machine learning techniques to predict content significance and generate appropriate questions, to interpretation of noisy spoken responses and statistical assessment of the response quality, through user modeling and determining how best to respond to the learner in order to optimize learning gains. This chapter focuses primarily on the domain-independent semantic analysis of learner responses, reviewing prior work in intelligent tutoring systems and educational assessment. We present a new framework for assessing the semantics of learner responses and the results of our initial implementation of a machine learning approach based on this framework.