Department of Information and Library Science, Tamkang University Full-Time Faculty

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TitleAn Adaptive Caching Strategy for m-Learning Based on SCORM Sequencing and Navigation

Year96

Semester1

Publish Date2008/01/01

Journal NameAn Adaptive Caching Strategy for m-Learning Based on SCORM Sequencing and Navigation

Journal Name Other

All AuthorChang, Hsuan-pu; Shih, Timothy K.; Li, Qing; Wang, Chun-chia; Wang, Te-hua; Chao, Louis R.

Unit淡江大學資訊與圖書館學系

Publisher

VolumeWorld Wide Web 11(3), pp.387-406

SummaryOne of the main problems encountered in the usage of mobile devices as a learning platform is the presence of an impermanent network environment due to insufficient coverage or link failure in wireless communication. On the other hand, a persistent connection is usually offered by cellular phones using a telecommunication protocol, but with a relatively weak computing power and very limited network bandwidth which makes m-learning a time-consuming process. Moreover, learning contents are currently composed of various multimedia resources that induce long latency to display on handheld devices such as smartphones with GPRS. Recently, a lot of m-learning systems and contents have conformed to the Sharable Content Object Reference Model (SCORM) since it was introduced by ADL in the late 90s. The Sequencing and Navigation (S&N) specification is an important part of SCORM. S&N is defined to prescribe the intended student learning sequence by instructors. In this paper, we propose an adaptive course caching strategy based on the S&N specification in an m-learning environment. The system automatically switches to the corresponding course caching strategies, namely, the virtual memory management (VMM) mode and caching on disk (COD) mode, according to the current networking capability. The proposed mechanism is implemented on an m-learning system—Pocket SCORM—which received the 2005 Brandon Hall Excellence in Learning Award in the USA. Our simulation and experiments demonstrate that the proposed course caching strategy ultimately reduces the latency during the learning process and decreases the requests for Internet reconnection.

KeywordMobile learning;SCORM;Course caching strategy;SCORM sequencing

Use LangEnglish

ISSN1386-145X

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