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    移动互联网的大规模学习服务生态环境研究

    Research on Large-scale Learning Service Ecological Environment Based on Mobile Internet

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【作      者】:

方海光, 刘嘉琪, 魏文雅, 汪时冲


【关 键 词 】:

移动互联网教育; 移动终端; 教育大数据; 学习服务; 生态环境


【栏      目】:

学习环境与资源


【中文摘要】:

不同于传统教育模式和新兴的互联网教育模式,基于移动互联网的大规模学习服务生态环境将伴随5G网络和终端产业发展成为下一代学习服务新模式。其中,如何实现学生、教师以及家长之间随时随地的学习服务和精准服务的闭环环境成为研究的关键所在。研究以教育主体和教育环境为核心,结合移动互联网的构成要素创建基于移动互联网的大规模学习服务生态环境模型(Mass Learning Service Ecological Model Based On Mobile Internet,简称3M模型),从学习空间、学习媒体、学习资源、学习支持和学习平台支持五个方面特征对其下一代学习服务生态环境进行了阐述,并分析了基于3M模型的五个典型智能学习场景:无人智能化学习环境、物联协同学习环境、智能终端学习环境、多维度空间学习环境、智能教学机器人,并构建基于学习场景划分的智能学习中心服务算法ILCSA,最后以基于移动互联网的中小学大规模学习移动终端应用案例作为验证。


【英文摘要】:

Different from the traditional education model and emerging Internet education model, with the development of 5G network and terminal industry, the mobile internet-based large-scale learning service ecological environment will become a new mode of learning service for next generation. Among them, how to realize the closed loop environment of learning service and accurate service among students, teachers and parents at any time and anywhere becomes the primary concern. Taking education subject and education environment as the core, and combined with the components of mobile Internet, this study creates a mass learning service ecological model based on mobile Internet (3M Model for short), which expounds the learning service ecological environment for next generation from learning space, learning media, learning resources, learning support and learning platform, and five typical intelligent learning scenarios based on the 3M model are analyzed: unmanned intelligent learning environment, IOT collaborative learning environment, intelligent terminal learning environment, multi-dimensional spacial learning environment, intelligent teaching robot. Then, this study constructs an intelligent learning center service algorithm ILCSA based on learning scenario division. Finally, a case of mobile terminal application of large-scale learning in primary and secondary schools is used for verification.

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