學術產出-Periodical Articles

Article View/Open

Publication Export

Google ScholarTM

政大圖書館

Citation Infomation

  • No doi shows Citation Infomation
題名 Considering Model-based Adaptivity for Learning Objects
作者 H-C- Wang
李蔡彥
日期 2004-04
上傳時間 16-Dec-2008 16:42:14 (UTC+8)
摘要 Adaptive Hypermedia (AH) and IMS Simple Sequencing (SS) are different approaches but
     both intend to attain a similar goal: tailored content for learning, just as Abdullah et al. discussed
     in [1]. However, these two distinct approaches have their own merits and defects. For
     SS, it takes the conformity with learning objects (LO) as the prime principle, and thus become
     the main approach to achieve dynamic presentation under the paradigm of using LOs to wrap
     up learning materials. But due to the absence of explicit domain and user models, SS cannot
     perform adaptivity in terms of learners’ cognition, such as prior knowledge, learning styles,
     etc. On the other hand, AH systems focus on constructing explicit models that represent various
     aspects of information related to decision making, such as user’s prior knowledge, preferences,
     learning domain, pedagogical knowledge, etc. Therefore, AH systems could perform
     elaborate decision making based on these models. However, issues like interoperability and
     reusability remain challenging to researchers in the AH field.
關聯 Learning Technology newsletter, 6(2),
資料類型 article
dc.creator (作者) H-C- Wangen_US
dc.creator (作者) 李蔡彥zh_TW
dc.date (日期) 2004-04en_US
dc.date.accessioned 16-Dec-2008 16:42:14 (UTC+8)-
dc.date.available 16-Dec-2008 16:42:14 (UTC+8)-
dc.date.issued (上傳時間) 16-Dec-2008 16:42:14 (UTC+8)-
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/14992-
dc.description.abstract (摘要) Adaptive Hypermedia (AH) and IMS Simple Sequencing (SS) are different approaches but
     both intend to attain a similar goal: tailored content for learning, just as Abdullah et al. discussed
     in [1]. However, these two distinct approaches have their own merits and defects. For
     SS, it takes the conformity with learning objects (LO) as the prime principle, and thus become
     the main approach to achieve dynamic presentation under the paradigm of using LOs to wrap
     up learning materials. But due to the absence of explicit domain and user models, SS cannot
     perform adaptivity in terms of learners’ cognition, such as prior knowledge, learning styles,
     etc. On the other hand, AH systems focus on constructing explicit models that represent various
     aspects of information related to decision making, such as user’s prior knowledge, preferences,
     learning domain, pedagogical knowledge, etc. Therefore, AH systems could perform
     elaborate decision making based on these models. However, issues like interoperability and
     reusability remain challenging to researchers in the AH field.
-
dc.format application/en_US
dc.format.extent 0 bytes-
dc.format.mimetype application/octet-stream-
dc.language enen_US
dc.language en-USen_US
dc.language.iso en_US-
dc.relation (關聯) Learning Technology newsletter, 6(2),en_US
dc.title (題名) Considering Model-based Adaptivity for Learning Objectsen_US
dc.type (資料類型) articleen