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    知识建构社区中观点种群能量流动机制研究

    Research on the Energy Flow Mechanism of Idea Clusters in Knowledge Building Communities

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【作      者】:

蒋纪平, 田晟瑶, 张义兵, 杨宾峰, 张卫东


【关 键 词 】:

知识建构社区; 观点种群; 进化认识论; 波普尔循环; 能量流动


【栏      目】:

网络教育


【中文摘要】:

观点进化是知识建构的核心,已有研究仍存在只分析观点个体、理论无法支持实践以及动态追踪欠缺等问题,亟须对多个观点所形成群体进行动态分析并揭示其进化机制。研究将“观点种群”作为分析单元,结合进化认识论和能量流动理论,探究知识建构社区中观点种群发展路径,揭示其能量流动机制。研究采用认知网络分析法和波普尔循环,分析某大学142名大二学生一学期知识建构教学中产生的538个观点种群。研究发现,观点种群呈现出从简单到复杂的认知结构跃升,体现出明显的阶段性进化路径。观点种群进化体现出从主观精神(世界2)向客观知识(世界3)转变的趋势,遵循波普尔循环逻辑。在能量流动过程中,研究提出了“观点聚合—选择—优化—组织化”的能级跃迁模型,揭示了观点种群在社区中的动态演化机制。研究为探究知识生态系统的动态演化提供实践依据,以期增强对开放学习社区中知识生成机制的整体认识。


【英文摘要】:

Idea evolution constitutes the core of knowledge building. However, problems still remain in existing research such as only analyzing individual ideas, insufficient theoretical support for practice, and the lack of dynamic tracking. Therefore, there is an urgent need to conduct dynamic analysis on idea clusters and and reveal their evolutionary mechanisms. In this study, "idea cluster" is taken as the analytical unit, and evolutionary epistemology and energy flow theory are combined to explore the development path of idea clusters in the knowledge building community, and to reveal the mechanism of its energy flow. Epistemic Network Analysis and Popper cycle are applied to analyze 538 idea clusters produced by 142 sophomores in a semester of knowledge building instruction. The results reveal that the idea clusters exhibit a leap in cognitive structure from simplicity to complexity,demonstrating a distinct stage-wise evolutionary trajectory. This evolution of idea clusters reflects the trend to shift from subjective experience(World 2) to objective knowledge(World 3), following the Popper cycle logic. Furthermore, in the process of energy flow, the study proposes an energy-level transition model of "idea aggregation-selection-optimization-organization", which reveals the dynamic evolution mechanism of idea clusters in the community. The study provides a practical basis for investigating the dynamic evolution of knowledge ecosystems, contributing to comprehensive understanding of knowledge generation mechanisms in open learning communities.

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