Prompting Assessment and Quality Classification in e-learning Recommender Systems
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Feiman, H. (2008). Prompting Assessment and Quality Classification in e-learning Recommender Systems. In J. Luca & E. Weippl (Eds.), Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2008 (pp. 1885-1892). Chesapeake, VA: AACE.
Retrieved from http://www.editlib.org/p/28632.
World Conference on Educational Multimedia, Hypermedia and Telecommunications (EDMEDIA) 2008
June 30, 2008
Joseph Luca & Edgar R. Weippl
More Information on EDMEDIA
Table of Contents
Along with the popularity and development of the Internet, e-learning system is gradually taken seriously, which will become a trend in.International organization have been propose more teaching material standard. But large learning active will be the learning route tree very complex and don’t elasticity that will be the learning route tree can’t manage and useful. So how to use application theory to improve the learning route structure become the useful teaching resources also the important research problem. This paper propose the use learning Agent’s characteristic to record user learning process and this data use the senior teacher to experience Quality the classification analysis system classification analysis processing. That analysis data will to propose teacher and appraises that learning type to be possible to enable the learner to obtain the most suitable study result, the teacher elasticity’s appraisal method can be teaches students in accordance with adaptive asynchronous learning that is goal.
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