| Summary: | 碩士 === 東吳大學 === 資訊管理學系 === 99 === With advances in computer and network technology and the popularity of e-learning evolution brought us different from the stereotypes of past learning. With amount of learning resources, the learners may confuse to choose the suitable learning materials for themselves. Therefore, a good feedback learning system to meet the individual needs has become an important research topic.
The online testing system has a rapid development in the recent years. The testing results are not only the scores to evaluate the learners, the testing answers can also provide valuable information about the learners learning details. By analyzing the large number of testing results and based on the individual's testing results, to find the necessary recommendations for individuals can improve the learners learning process on the e-learning system.
This study attempts to develop an effective personalized learning feedback system. According to a large number of students test results, we applied the technology of data mining to find the association rules between chapter sections. And then, we combined with personal error rate from testing answers and impact of the chapter sections to provide students feedback information. The feedback information includes the error answered questions, the degree of misunderstanding of chapter sections, and the personal information needed to remedy the learning. Purpose is to improve the learning effect by giving users personalized learning feedback and advising about personal learning process. Experimental results showed that students using this system, the magnitude of test scores showed significant progress in the performance.
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