华东师范大学学报(教育科学版) ›› 2025, Vol. 43 ›› Issue (10): 84-98.doi: 10.16382/j.cnki.1000-5560.2025.10.006

• 专题:学习科学 • 上一篇    下一篇

联通主义学习中学习者学习路径挖掘及表征

杨阳1, 陈丽2   

  1. 1. 首都师范大学教育学院,北京 100048
    2. 北京师范大学教育学部,北京 100875
  • 接受日期:2025-05-09 出版日期:2025-10-01 发布日期:2025-10-09
  • 基金资助:
    国家自然科学基金委员会管理学部重点课题“‘互联网+’时代的教育改革与创新管理研究”(71834002);2025年度北京市博士后工作经费资助项目“基于大规模在线实践社区的教师成长路径及特征研究”(zz-2025-151)。

Mining and Representation of Learner’s Learning Path in Connectivist Learning

Yang Yang1, Li Chen2   

  1. 1. College of Education, Capital Normal University, Beijing 100048, China
    2. Faculty of Education, Beijing Normal University, Beijing 100875, China
  • Accepted:2025-05-09 Online:2025-10-01 Published:2025-10-09

摘要:

揭示联通主义学习的内在机理,能为建设以联通主义学习为核心的课程新形态提供支撑,从而有效回应新时代拔尖创新人才培养的需求,而联通主义学习路径挖掘及表征是其中重要且前沿的研究方向。当前研究缺乏对联通主义学习路径连续且完整的追踪与挖掘,以及对其组织结构的表征,这制约了课程实践的深入发展。为了解决这一问题,本研究立足国内首门联通主义在线课程情境,聚焦56名联通主义学习者,采用聚类分析、序列分析、网络分析等方法展开实证研究。分析发现:(1)学习者产生了三类学习路径,分别为主路径——问题导向型、学习支持路径——社群导向型、新手路径——路径依赖型,经验不同的学习者具有差异化的路径偏好,线性课程运行规则影响主题选择空间;(2)联通主义学习路径的拓扑结构具有时序与网络的双重特点;(3)学习者展现出三类学习模式,分别是问题驱动式、策展联通式、知识重组式。未来联通主义课程及相关在线学习实践需强化对学习资源的分层分类设计与个性化供给;设计引发协同知识创生的活动链;强化在线学习实践的动态运维管理;优化课程组织模式,从资源、活动、管理等方面系统优化课程建设方案。

关键词: 联通主义, cMOOC, 学习路径

Abstract:

Revealing the intrinsic mechanisms of connectivist learning is a crucial focus for supporting the construction of a new curriculum model centered on connectivist learning, in response to the new propositions of cultivating top-notch innovative talents in the current era. The mining and representation of connectivist learning paths is the essential and cutting-edge research direction within this context. Current research lacks continuous and complete tracking and structural representation of connectivist learning paths, which is hindering the depth of curriculum practice. To solve this problem, based on the first domestic connectivist online course, and focusing on 56 connectivist learners, empirical research was conducted using methods such as cluster analysis, sequence analysis, and network analysis. The study found that, first, learners produced three types of learning paths, namely, main route—problem-oriented, learning support route—community-oriented, and novice route—path-dependent; learners with different experiences have differentiated path preferences, and linear course operation rules affect the space for topic selection. Second, the topological structure of connectivist learning paths has dual characteristics of temporality and networking. Third, learners exhibited three types of learning modes, namely problem-driven, curated connectivity, and knowledge restructuring. Future construction of connectivist online courses and related online learning practices should emphasize the hierarchical classification design and personalized provision of learning resources; design activity chains that stimulate collaborative knowledge creation; enhance dynamic operation and management of online learning practices; and optimize course organizational models, ultimately systematically improving course development strategies across resources, activities, and management dimensions.

Key words: connectivism, cMOOC, learning path