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作 者:万海鹏 余胜泉 王琦 WAN Haipeng;YU Shengquan;WANG Qi(College of Education,Capital Normal University,Beijing 100048;Advanced Innovation Center for Future Education,Beijing Normal University,Beijing 100875;Artificial Intelligence and Human Languages Lab,Beijing Foreign Studies University,Beijing 100089)
机构地区:[1]首都师范大学教育学院,北京100048 [2]北京师范大学未来教育高精尖创新中心,北京100875 [3]北京外国语大学人工智能与人类语言重点实验室,北京100089
出 处:《电化教育研究》2021年第10期12-18,24,共8页E-education Research
基 金:2020年度国家自然科学青年基金项目“在线课程的知识地图构建及关键技术研究”(项目编号:62007025);2020年度教育部人文社科青年基金项目“基于文本情感识别的教师教学问题智能诊断与改进研究”(项目编号:20YJC880088)。
摘 要:智能技术的发展带来了对学习和认知的革新,学习的关键除了要构建知识并促进学习者的认知行为,在此过程中建立一个能够联通各个知识节点的社会知识网络也变得日益重要。不同于以往知识建构所秉持的行为交互层次、个体知识内化与外化水平以及社区整体知识增长的角度,研究从后现代知识观和联通主义学习观的视角出发,设计了以知识网络和社会网络为双核驱动的连接式知识建构模型。该模型强调知识建构过程中知识具有的情境性、进化性和社会性等特点,以社会知识网络为建构载体,关注知识建构活动中建立的知识与知识、人与知识、人与人之间的可视化连接。随后,基于学习元知识社区对模型的应用进行了探索,以期为知识建构领域的研究者提供理论和实践上的参考。The development of intelligent technology has brought about innovations in learning.In addition to building knowledge and facilitating learners'cognitive behavior,it has become increasingly important to establish a social knowledge network that connects the various knowledge nodes during learning process.Unlike the perspectives of the behavioral interaction level,the internalization and externalization level of individual knowledge and the overall knowledge growth of the community upheld by previous knowledge building studies,this research takes the perspectives of postmodernist view of knowledge and connectionist view of learning and designs a connected knowledge building model driven by the dual core of knowledge networks and social network.The model emphasizes the contextual,evolutionary and social characteristics of knowledge in the process of knowledge building,takes social knowledge networks as the construction vehicle,and focuses on the visual connections between knowledge and knowledge,people and knowledge,and people and people established in knowledge building activities.Subsequently,a preliminary exploration of the application of the model based on the learning meta-knowledge community is conducted with a view to providing theoretical and practical references for researchers in the field of knowledge building.
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