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Title:
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USING TAXONOMIES IN COMPOSING LEARNING OBJECTS |
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Author(s):
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Juha Puustjärvi |
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ISBN:
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972-8924-02-X |
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Editors:
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Pedro Isaías and Miguel Baptista Nunes |
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Year:
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2005 |
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Edition:
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2 |
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Keywords:
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Learning object content models, taxonomies, metadata, composed learning objects, information retrieval models. |
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Type:
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Short Paper |
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First Page:
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288 |
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Last Page:
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291 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Generally the term learning object is understood to be a digital entity deliverable over Internet such that any number of learners can use them simultaneously. Learning object content models are taxonomies, which identify the components of learning objects. They are developed in order to increase the reusability of learning objects. We have studied the use of learning object models for automatic composing of learning object. This approach requires that we use the same taxonomy and model for classifying learning objects and the content of the composed learning objects. We have used the vector model as it allows more expression power than the Boolean model. The gain of this approach is that we can automatically produce the material of composed learning objects. Further, in automatic composition we can use the same software that we have developed for searching learning objects. |
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