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Research on Sequential Patterns Mining in Self-Adaptive Learning System

Author: LiangJiZuo
Tutor: XuPeiJuan
School: Jilin University
Course: Computer Software and Theory
Keywords: Adaptive Learning Adaptive Learning System Personalized learning Learner Characteristics Sequential pattern mining AprioriAll algorithm DAprioriAll algorithm
CLC: TP311.13
Type: Master's thesis
Year: 2008
Downloads: 105
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Traditional form of distance education is relatively simple because only attach importance to teach ignore learning from there in teaching both interactive rather poor , and this has been far from satisfying the needs of learners . Learner-centered learning methods , has drawn increasing attention of educational researchers . In order to solve the problems of distance education , education researchers have proposed an adaptive learning system to solve this problem . Adaptive learning system , the computer system as the role of teachers and learners to provide personalized self- learning environment . As online education in China started late , so there are many problems in the process of its development , mainly in the following aspects : 1 . Single contempt of teaching content presentation learning environment design . 2 . Autonomous learning resources . 3 dynamic interactive features . The 4 . Targeted , low intelligence , lack of effective Tutoring mechanism . In order to solve the above problem , this paper proposes to improve the function of the adaptive learning system should continue to strengthen the construction of adaptive learning systems . Thereby increasing the intelligent adaptive learning system , to enhance adaptive systems guide learners learn . The key problem of the adaptive learning system is the characteristics of learners . The core Learners'Characteristics regular research on personalized learning . The key to personalized learning law is on the learner 's learning style and learning content selection strategy . In this paper, the adaptive learning system framework , focusing on the characteristics of learners in adaptive learning system analysis model . Learner Characteristics personalized learning law mining is actually the convection data mining . The flow of data mining mining pattern sequence pattern mining . Sequential pattern mining in AprioriAll algorithm has been studied less than for AprioriAll algorithm , an improved algorithm . Improved algorithm to reduce the number of database sequences set to improve the efficiency of the algorithm . The algorithm can be deleted database -Africa frequent subsequence length is less than the K sequence set , when such support in the the scan candidate sequence set , you can reduce the number of records in the database scanning , reducing the burden on the system , and improve the efficiency of the algorithm .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer software > Program design,software engineering > Programming > Database theory and systems
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