A Framework for the Generation of Adaptive Courses Based on Semantic Metadata
Abstract This approach proposes the creation and management of adaptive learning systems by combining component technology, semantic metadata, and adaptation rules. A component model allows interaction among components that share consistent assumptions about what each provides and each requires of t...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Duitama, Freddy [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2005 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science + Business Media, Inc. 2005 |
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| Übergeordnetes Werk: |
Enthalten in: Multimedia tools and applications - Kluwer Academic Publishers, 1995, 25(2005), 3 vom: März, Seite 377-390 |
|---|---|
| Übergeordnetes Werk: |
volume:25 ; year:2005 ; number:3 ; month:03 ; pages:377-390 |
| Links: |
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| DOI / URN: |
10.1007/s11042-005-6541-8 |
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OLC2034997492 |
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10.1007/s11042-005-6541-8 doi (DE-627)OLC2034997492 (DE-He213)s11042-005-6541-8-p DE-627 ger DE-627 rakwb eng 070 004 VZ Duitama, Freddy verfasserin aut A Framework for the Generation of Adaptive Courses Based on Semantic Metadata 2005 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science + Business Media, Inc. 2005 Abstract This approach proposes the creation and management of adaptive learning systems by combining component technology, semantic metadata, and adaptation rules. A component model allows interaction among components that share consistent assumptions about what each provides and each requires of the other. It allows indexing, using, reusing, and coupling of components in different contexts powering adaptation. Our claim is that semantic metadata are required to allow a real reusing and assembling of educational component. Finally, a rule language is used to define strategies to rewrite user query and user model. The former allows searching components developing concepts not appearing in the user query but related with user goals, whereas the last allow inferring user knowledge that is not explicit in user model. adaptive learning system semantic metadata learning objects composition of learning objects Defude, Bruno aut Bouzeghoub, Amel aut Lecocq, Claire aut Enthalten in Multimedia tools and applications Kluwer Academic Publishers, 1995 25(2005), 3 vom: März, Seite 377-390 (DE-627)189064145 (DE-600)1287642-2 (DE-576)052842126 1380-7501 nnns volume:25 year:2005 number:3 month:03 pages:377-390 https://doi.org/10.1007/s11042-005-6541-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-BUB SSG-OLC-MKW GBV_ILN_70 GBV_ILN_100 GBV_ILN_2020 GBV_ILN_4318 AR 25 2005 3 03 377-390 |
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10.1007/s11042-005-6541-8 doi (DE-627)OLC2034997492 (DE-He213)s11042-005-6541-8-p DE-627 ger DE-627 rakwb eng 070 004 VZ Duitama, Freddy verfasserin aut A Framework for the Generation of Adaptive Courses Based on Semantic Metadata 2005 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science + Business Media, Inc. 2005 Abstract This approach proposes the creation and management of adaptive learning systems by combining component technology, semantic metadata, and adaptation rules. A component model allows interaction among components that share consistent assumptions about what each provides and each requires of the other. It allows indexing, using, reusing, and coupling of components in different contexts powering adaptation. Our claim is that semantic metadata are required to allow a real reusing and assembling of educational component. Finally, a rule language is used to define strategies to rewrite user query and user model. The former allows searching components developing concepts not appearing in the user query but related with user goals, whereas the last allow inferring user knowledge that is not explicit in user model. adaptive learning system semantic metadata learning objects composition of learning objects Defude, Bruno aut Bouzeghoub, Amel aut Lecocq, Claire aut Enthalten in Multimedia tools and applications Kluwer Academic Publishers, 1995 25(2005), 3 vom: März, Seite 377-390 (DE-627)189064145 (DE-600)1287642-2 (DE-576)052842126 1380-7501 nnns volume:25 year:2005 number:3 month:03 pages:377-390 https://doi.org/10.1007/s11042-005-6541-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-BUB SSG-OLC-MKW GBV_ILN_70 GBV_ILN_100 GBV_ILN_2020 GBV_ILN_4318 AR 25 2005 3 03 377-390 |
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10.1007/s11042-005-6541-8 doi (DE-627)OLC2034997492 (DE-He213)s11042-005-6541-8-p DE-627 ger DE-627 rakwb eng 070 004 VZ Duitama, Freddy verfasserin aut A Framework for the Generation of Adaptive Courses Based on Semantic Metadata 2005 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science + Business Media, Inc. 2005 Abstract This approach proposes the creation and management of adaptive learning systems by combining component technology, semantic metadata, and adaptation rules. A component model allows interaction among components that share consistent assumptions about what each provides and each requires of the other. It allows indexing, using, reusing, and coupling of components in different contexts powering adaptation. Our claim is that semantic metadata are required to allow a real reusing and assembling of educational component. Finally, a rule language is used to define strategies to rewrite user query and user model. The former allows searching components developing concepts not appearing in the user query but related with user goals, whereas the last allow inferring user knowledge that is not explicit in user model. adaptive learning system semantic metadata learning objects composition of learning objects Defude, Bruno aut Bouzeghoub, Amel aut Lecocq, Claire aut Enthalten in Multimedia tools and applications Kluwer Academic Publishers, 1995 25(2005), 3 vom: März, Seite 377-390 (DE-627)189064145 (DE-600)1287642-2 (DE-576)052842126 1380-7501 nnns volume:25 year:2005 number:3 month:03 pages:377-390 https://doi.org/10.1007/s11042-005-6541-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-BUB SSG-OLC-MKW GBV_ILN_70 GBV_ILN_100 GBV_ILN_2020 GBV_ILN_4318 AR 25 2005 3 03 377-390 |
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10.1007/s11042-005-6541-8 doi (DE-627)OLC2034997492 (DE-He213)s11042-005-6541-8-p DE-627 ger DE-627 rakwb eng 070 004 VZ Duitama, Freddy verfasserin aut A Framework for the Generation of Adaptive Courses Based on Semantic Metadata 2005 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science + Business Media, Inc. 2005 Abstract This approach proposes the creation and management of adaptive learning systems by combining component technology, semantic metadata, and adaptation rules. A component model allows interaction among components that share consistent assumptions about what each provides and each requires of the other. It allows indexing, using, reusing, and coupling of components in different contexts powering adaptation. Our claim is that semantic metadata are required to allow a real reusing and assembling of educational component. Finally, a rule language is used to define strategies to rewrite user query and user model. The former allows searching components developing concepts not appearing in the user query but related with user goals, whereas the last allow inferring user knowledge that is not explicit in user model. adaptive learning system semantic metadata learning objects composition of learning objects Defude, Bruno aut Bouzeghoub, Amel aut Lecocq, Claire aut Enthalten in Multimedia tools and applications Kluwer Academic Publishers, 1995 25(2005), 3 vom: März, Seite 377-390 (DE-627)189064145 (DE-600)1287642-2 (DE-576)052842126 1380-7501 nnns volume:25 year:2005 number:3 month:03 pages:377-390 https://doi.org/10.1007/s11042-005-6541-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-BUB SSG-OLC-MKW GBV_ILN_70 GBV_ILN_100 GBV_ILN_2020 GBV_ILN_4318 AR 25 2005 3 03 377-390 |
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Abstract This approach proposes the creation and management of adaptive learning systems by combining component technology, semantic metadata, and adaptation rules. A component model allows interaction among components that share consistent assumptions about what each provides and each requires of the other. It allows indexing, using, reusing, and coupling of components in different contexts powering adaptation. Our claim is that semantic metadata are required to allow a real reusing and assembling of educational component. Finally, a rule language is used to define strategies to rewrite user query and user model. The former allows searching components developing concepts not appearing in the user query but related with user goals, whereas the last allow inferring user knowledge that is not explicit in user model. © Springer Science + Business Media, Inc. 2005 |
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Abstract This approach proposes the creation and management of adaptive learning systems by combining component technology, semantic metadata, and adaptation rules. A component model allows interaction among components that share consistent assumptions about what each provides and each requires of the other. It allows indexing, using, reusing, and coupling of components in different contexts powering adaptation. Our claim is that semantic metadata are required to allow a real reusing and assembling of educational component. Finally, a rule language is used to define strategies to rewrite user query and user model. The former allows searching components developing concepts not appearing in the user query but related with user goals, whereas the last allow inferring user knowledge that is not explicit in user model. © Springer Science + Business Media, Inc. 2005 |
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Abstract This approach proposes the creation and management of adaptive learning systems by combining component technology, semantic metadata, and adaptation rules. A component model allows interaction among components that share consistent assumptions about what each provides and each requires of the other. It allows indexing, using, reusing, and coupling of components in different contexts powering adaptation. Our claim is that semantic metadata are required to allow a real reusing and assembling of educational component. Finally, a rule language is used to define strategies to rewrite user query and user model. The former allows searching components developing concepts not appearing in the user query but related with user goals, whereas the last allow inferring user knowledge that is not explicit in user model. © Springer Science + Business Media, Inc. 2005 |
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