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Toward A Theoretical Basis for Dynamically Driven Content: Computer-Mediated Environments and Personalised eLearning - Softcover
Synopsis
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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About the Author
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
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LAP LAMBERT Academic Publishing Mai 2010, 2010
ISBN 10: 3838310373
ISBN 13: 9783838310374
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: 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. Seller Inventory # 9783838310374
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Toward A Theoretical Basis for Dynamically Driven Content : Computer-Mediated Environments and Personalised eLearning
Published by
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838310373
ISBN 13: 9783838310374
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: 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. Seller Inventory # 9783838310374
Quantity: 1 available
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Toward A Theoretical Basis for Dynamically Driven Content
Published by
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3838310373
ISBN 13: 9783838310374
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Softcover
Seller: moluna, Greven, Germany
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Condition: 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. Seller Inventory # 5411744
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Toward A Theoretical Basis for Dynamically Driven Content
Published by
LAP LAMBERT Academic Publishing Mai 2010, 2010
ISBN 10: 3838310373
ISBN 13: 9783838310374
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: 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. Seller Inventory # 9783838310374
Quantity: 2 available