Title :
Putting adaptive granularity and rich context into learning objects
Author :
Man, Haifeng ; Jin, Qun
Author_Institution :
Grad. Sch. of Human Sci., Waseda Univ., Tokorozawa, Japan
fDate :
April 29 2010-May 1 2010
Abstract :
The content granularity and context information are two important factors to the efficiency and reusability of learning objects. The context information is necessary to facilitate the discovery and reuse of learning objects stored in global and/or local repositories. However, traditional learning objects are generally not conceived to incorporate with enough context information. Users have to do some extension of the description item set to fit their special use. In this paper, in order to deal with the issue mentioned above, we firstly introduce a context-rich paradigm, the related service driven tagging strategy, and a context model of learning objects. We further explain how to use the context information to realize the adaptive granularity of the content object. Finally, we show a simple concept model for online authoring systems that support the evolution from resource objects to learning objects.
Keywords :
authoring systems; computer aided instruction; meta data; content granularity; context information; learning object efficiency; learning object reusability; online authoring systems; related service driven tagging strategy; resource objects; Authoring systems; Context modeling; Context-aware services; Education; Humans; Information retrieval; Resource management; Tagging; adaptive granularity; context model; context rich paradigm; learning object; resource object; service driven tagging;
Conference_Titel :
Information Technology Based Higher Education and Training (ITHET), 2010 9th International Conference on
Conference_Location :
Cappadocia
Print_ISBN :
978-1-4244-4810-4
DOI :
10.1109/ITHET.2010.5480044