A Fuzzy Inference-based Personalized Online Remedial Learning System

• Main Authors: Chun-ChihJiang, 江俊志
• Other Authors: Tzone-I Wang
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/17137047803158795552

碩士 === 國立成功大學 === 工程科學系碩博士班 === 98 === In recently years, learning environment has been changing because of the rapid development of Internet and information technology. Classroom learning and paper examinations are gradually migrating to online e-learning and assessing environments. The network access features make learners of e-learning system be able to learn at any time and in any place. With profuse and diverse learning materials, teaching quality can be effectively enhanced too. However, for the time being, most assessing system of e-learning environments can provide grades, correct answers and misconceptions of users in a test only, without any well-formed remedial instructions to the learners. This study establishes a fuzzy inference-based remedial learning system to assist learners in remedial learning after an online assessment. C++ programming courses are used as a testing platform in this study. First, the system finds, from the Internet, the related concept set by apriori algorithm according to a learner’s misconceptions in a test and uses a fuzzy inference mechanism to decide a suitable learning path, comprising the concepts, for the learner. Then, the system searches learning materials and resources from the Internet for the concepts, based on the individual learner’s learning style, for conducting remedial learning of the learner. The system, proven by several conducted experiments, can offer a complete and stable remedial learning environment for any e-learning systems. The analysis of learners’ achievements and questionnaires has confirmed the method of this study achieve the effect of remedial learning and adaptive learning.