Provide Individualized E-learning Services through Text Mining
Vast amount of high quality online resources have been developed to improve science education, while studies have shown that learners have difficulties to precisely locate and timely utilize pedagogical information from these resources. This paper describes an individualized E-learning service to scaffold learning process based on learners needs through text mining and concept extraction. We propose a framework to automatic articulate learners prior misconceptions and to generate instructions from web resources based on their own knowledge states. A personalized learning interface is implemented to support this service.
text mining personalization distance education user interface information extraction
Qianyi Gu Faisal Ahmad Tamara Sumner
Visual Computing and Virtual Reality Key Laboratory of Sichuan Province College of Computer Science, Department of Computer Science University of Colorado Boulder, USA
国际会议
桂林
英文
388-391
2010-11-17（万方平台首次上网日期，不代表论文的发表时间）