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An Open Framework for Smart and Personalized Distance Learning
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2. An Open Framework for Smart and Personalized Distance Learning
Ruimin Shen7 , Peng Han7 , Fan Yang7 , Qiang Yang8 and Joshua Zhexue Huang9 
| (7) |
Department of Computer Science & Engineering, Shanghai Jiaotong University, Shanghai, China |
| (8) |
Department of Computer Science, Hong Kong University of Science and Technology, Hong Kong, China |
| (9) |
E-Business Technology Institute, University of Hong Kong, Hong Kong, China |
Abstract
Web based learning enables more students to have access to the distance-learning environment and provides students and teachers
with unprecedented flexibility and convenience. However, the early experience of using this new learning means in China exposes
a few problems. Among others, teachers accustomed to traditional teaching methods often find it difficult to put their courses
online and some students, especially the adult students, find themselves overloaded with too much information. In this paper,
we present an open framework to solve these two problems. This framework allows students to interact with an automated question
answering system to get their answers. It enables teachers to analyze students learning patterns and organize the webbased
contents efficiently. The framework is intelligent due to the data mining and case-based reasoning features, and user-friendly
because of its personalized services to both teachers and students.
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