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Toward A Theoretical Basis for Dynamically Driven Content: Computer-Mediated Environments and Personalised eLearning - Softcover
Inhaltsangabe
The intent of dynamic learning with data driven content (DDC) in computer-mediated learning environments is to interactively adapt the flow of content so that each student receives personalised learning materials and interventions more suited to their needs than in traditional one-size-fits-all applications. Measurement technologies similar to some models underlying computer-adaptive testing approaches (CAT) are used here to create personalisation by mapping knowledge spaces and driving computer-mediated learning environments. Methods explore extensions to CAT with item response models and construct mapping, which may direct the flow and difficulty not only of assessments but also of other e- learning materials and feedback to tailor the learning experience to student needs. A measurement model, the iota model, is introduced and tested as a multifacet Rasch model to estimate "pathway" parameters through BEAR CAT testlets. Testlets are small bundles of items that act as questions and follow-up probes to interactively measure and assign scores to students. The function of the measurement models applied is mathematically equivalent to the semi-linear neural net model.
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Reseña del editor
The intent of dynamic learning with data driven content (DDC) in computer-mediated learning environments is to interactively adapt the flow of content so that each student receives personalised learning materials and interventions more suited to their needs than in traditional one-size-fits-all applications. Measurement technologies similar to some models underlying computer-adaptive testing approaches (CAT) are used here to create personalisation by mapping knowledge spaces and driving computer-mediated learning environments. Methods explore extensions to CAT with item response models and construct mapping, which may direct the flow and difficulty not only of assessments but also of other e- learning materials and feedback to tailor the learning experience to student needs. A measurement model, the iota model, is introduced and tested as a multifacet Rasch model to estimate "pathway" parameters through BEAR CAT testlets. Testlets are small bundles of items that act as questions and follow-up probes to interactively measure and assign scores to students. The function of the measurement models applied is mathematically equivalent to the semi-linear neural net model.
Biografía del autor
Kathleen Scalise received her Ph.D. in quantitative measurement at the University of California, Berkeley. An assistant professor at the University of Oregon, she served as a writer of California's K-12 Science Framework, as UC Berkeley Chancellor's speechwriter, and works on dynamically delivered content in eLearning with item response models.
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Toward A Theoretical Basis for Dynamically Driven Content
Verlag:
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838310373
ISBN 13: 9783838310374
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Scalise KathleenKathleen Scalise received her Ph.D. in quantitative measurementat the University of California, Berkeley. An assistant professor at the University ofOregon, she served as a writer of California s K-12 Science Framewor. Bestandsnummer des Verkäufers 5411744
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Toward A Theoretical Basis for Dynamically Driven Content
Verlag:
LAP LAMBERT Academic Publishing Mai 2010, 2010
ISBN 10: 3838310373
ISBN 13: 9783838310374
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Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
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Taschenbuch. Zustand: Neu. Neuware -The intent of dynamic learning with data driven content (DDC) in computer-mediated learning environments is to interactively adapt the flow of content so that each student receives personalised learning materials and interventions more suited to their needs than in traditional one-size-fits-all applications. Measurement technologies similar to some models underlying computer-adaptive testing approaches (CAT) are used here to create personalisation by mapping knowledge spaces and driving computer-mediated learning environments. Methods explore extensions to CAT with item response models and construct mapping, which may direct the flow and difficulty not only of assessments but also of other e- learning materials and feedback to tailor the learning experience to student needs. A measurement model, the iota model, is introduced and tested as a multifacet Rasch model to estimate 'pathway' parameters through BEAR CAT testlets. Testlets are small bundles of items that act as questions and follow-up probes to interactively measure and assign scores to students. The function of the measurement models applied is mathematically equivalent to the semi-linear neural net model.Books on Demand GmbH, Überseering 33, 22297 Hamburg 332 pp. Englisch. Bestandsnummer des Verkäufers 9783838310374
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Toward A Theoretical Basis for Dynamically Driven Content : Computer-Mediated Environments and Personalised eLearning
Verlag:
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838310373
ISBN 13: 9783838310374
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Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The intent of dynamic learning with data driven content (DDC) in computer-mediated learning environments is to interactively adapt the flow of content so that each student receives personalised learning materials and interventions more suited to their needs than in traditional one-size-fits-all applications. Measurement technologies similar to some models underlying computer-adaptive testing approaches (CAT) are used here to create personalisation by mapping knowledge spaces and driving computer-mediated learning environments. Methods explore extensions to CAT with item response models and construct mapping, which may direct the flow and difficulty not only of assessments but also of other e- learning materials and feedback to tailor the learning experience to student needs. A measurement model, the iota model, is introduced and tested as a multifacet Rasch model to estimate 'pathway' parameters through BEAR CAT testlets. Testlets are small bundles of items that act as questions and follow-up probes to interactively measure and assign scores to students. The function of the measurement models applied is mathematically equivalent to the semi-linear neural net model. Bestandsnummer des Verkäufers 9783838310374
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Toward A Theoretical Basis for Dynamically Driven Content
Verlag:
LAP LAMBERT Academic Publishing Mai 2010, 2010
ISBN 10: 3838310373
ISBN 13: 9783838310374
Neu
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Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The intent of dynamic learning with data driven content (DDC) in computer-mediated learning environments is to interactively adapt the flow of content so that each student receives personalised learning materials and interventions more suited to their needs than in traditional one-size-fits-all applications. Measurement technologies similar to some models underlying computer-adaptive testing approaches (CAT) are used here to create personalisation by mapping knowledge spaces and driving computer-mediated learning environments. Methods explore extensions to CAT with item response models and construct mapping, which may direct the flow and difficulty not only of assessments but also of other e- learning materials and feedback to tailor the learning experience to student needs. A measurement model, the iota model, is introduced and tested as a multifacet Rasch model to estimate 'pathway' parameters through BEAR CAT testlets. Testlets are small bundles of items that act as questions and follow-up probes to interactively measure and assign scores to students. The function of the measurement models applied is mathematically equivalent to the semi-linear neural net model. 332 pp. Englisch. Bestandsnummer des Verkäufers 9783838310374
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