基于并行教育的智能辅导系统框架

Sifeng Jing, Ying Tang, Xiwei Liu, Xiaoyan Gong, Wei Cui, Joleen Liang
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引用次数: 2

摘要

尽管在线教育提高了学习者获取优质教育资源的效率,但在线个性化学习尚未实现教师与学习者之间的实时互动。本文对智能交通系统的研究现状和发展趋势进行了综述,并指出了智能交通系统研发面临的三大挑战:学习者模型、引导机制和人机交互机制。为了解决这些问题,引入并行智能理论,提出了一个基于智能系统的并行智能教育框架。
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A Parallel Education Based Intelligent Tutoring Systems Framework
although online education has improved efficiency of learners' access to high-quality educational resources, realtime interaction between instructors and learners have not yet been achieved in online personalized learning. Intelligent Tutoring Systems (ITS) provides a feasible way to realize realtime personalized learning guidance and resource recommendations by applying AI to capture and analyze online learners' characteristics and behaviors. In this paper, reviews and trends of ITS are discussed and three challenges of ITS research &development are pointed out: learner model, guidance mechanism and human-computer interaction mechanism. In order to address these issues, parallel intelligence theory is introduced and a parallel intelligence education based ITS framework is proposed.
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