Title of article :
ADAM: An adaptive multimedia content description mechanism and its application in web-based learning
Author/Authors :
Wang، نويسنده , , Chian and Wang، نويسنده , , Dao-Zhi and Lin، نويسنده , , Jia-Li، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2010
Pages :
11
From page :
8639
To page :
8649
Abstract :
Because the backgrounds and the requirements of web-based learners vary a lot, it is reasonable and practical to adapt the presentation contents according to each learner’s preferences or demands. The feature of presenting adaptive contents to different types of learners can significantly improve learning results through providing materials that are more suitable to the learners. In this paper, we propose ADAM, an adaptive multimedia content description mechanism and demonstrate its application in web-based learning (WBL). ADAM is based on XML and can dynamically adapt how a multimedia presentation is composed and the constituent media objects. ADAM’s main feature is that a single content description file can be applied to all types of learners. By following the statements in the description file and the learners’ preferences, ADAM can dynamically generate adaptive presentations for the various types of learners. In this way, the instructors can save a lot of effort and time in composing the courseware. Another feature of ADAM is that it does not require a specific browser to view the generated presentations. Any web browsers supporting XML, e.g., Microsoft Internet Explorer can be used. This paper also presents the development of an ADAM-based WBL system and the corresponding system evaluations. The results confirmed that ADAM can indeed generate appropriate presentations to the learners and can help them to learn more efficiently and effectively.
Keywords :
Web-based learning , XML , Content description , adaptive learning , Multimedia presentations
Journal title :
Expert Systems with Applications
Serial Year :
2010
Journal title :
Expert Systems with Applications
Record number :
2348592
Link To Document :
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