A Novel Adaptive E-learning System Design for Research-based Curriculum

He-xiang XU, Zhe XU

Abstract


Adaptive Learning Systems are mainly aimed at basic subjects recent years. Their main functions are to locate learners' weak knowledge and recommend learning paths. The systems can not apply to the learning mode of research-based curriculum in terms of basic theory, function design, operation mechanism or learning mode. This paper presents an intelligent kernel of adaptive learning system for research-based curriculum, and designs an intelligent Massive Open Online Research System (MOORS). The results indicate that MOORS can self-adaptively push learning resources and tasks, reduce teachers' repetitive working, let teachers guide students' research with more time and energy. In conclusion, MOORS can effectively promote the opening rate of research-oriented courses, promote the improvement of students' research level, which plays an significance role in the cultivation of innovative talents in the long run.

Keywords


Research-based curriculum, Adaptive learning system, Research-based learning, Self-adaptively push, Intelligent system


DOI
10.12783/dtssehs/eelss2020/34633

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