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Knowledge Modelling to Support Inquiry Learning Tasks

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6291))

Abstract

In this paper we describe the SILVER toolkit, which is designed for tasks in which a user learns by analysing and interpreting a set of resources. The user categorises each resource according to the set of properties that they identify as being applicable to it. Due to the large amount of data generated by this type of task, the user may find it hard to identify patterns in their classification and tagging, to recognise their own inconsistencies or make comparisons between themselves and others. In the first SILVER task described, the ID3 decision tree algorithm is applied to the user’s data to identify patterns and generate different types of feedback. Principles of spatial hypertext are used to produce an interactive visualization of the summarized data. As the user interacts with the resources, they can see their progress and changing perspective on the task. In the second SILVER task described, a conceptual model is used to provide explanations of the model underlying the user’s classification of resources.

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© 2010 Springer-Verlag Berlin Heidelberg

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Wolff, A., Mulholland, P., Zdrahal, Z., Blasko, M. (2010). Knowledge Modelling to Support Inquiry Learning Tasks. In: Bi, Y., Williams, MA. (eds) Knowledge Science, Engineering and Management. KSEM 2010. Lecture Notes in Computer Science(), vol 6291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15280-1_20

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  • DOI: https://doi.org/10.1007/978-3-642-15280-1_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15279-5

  • Online ISBN: 978-3-642-15280-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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