何种因素影响网络学习资源进化?——基于德尔菲法和解释结构模型的研究

What Factors Influence the Evolution of E-Learning Resources?——A Study Based on the Delphi Method and Explanatory Structural Modeling

教育高质量发展的新阶段对资源大规模生成与持续改进的需求越来越高。准确识别网络学习资源进化的影响因素有助于掌握资源进化的规律与内在机制,从而助力学习资源高质量建设。该研究基于信息生态学理论,结合相关文献的梳理与分析,初步建立了网络学习资源进化影响因素指标体系。然后,通过德尔菲法对指标体系进行修订完善。最后,利用解释结构模型法分析因素之间的内在联系,并构建了网络学习资源进化影响因素解释结构模型。基于该模型,该研究认为,促进网络学习资源的进化需要以增加用户数量和激发用户创作积极性为目标。同时,在确保学习资源质量的前提下,注重学习平台和管理机制的建设,从而全面保障资源的有序进化。通过识别网络学习资源进化的影响因素,可以为高质量网络学习资源的建设提供有益的参考和指导,从而促进网络学习资源向更加优质和适用的方向不断发展。

The new stage of high-quality development of education has an increasing demand for large-scale generation and continuous improvement of E-learning resources.Accurately identifying the influencing factors of E-learning resource evolution helps to grasp the law and internal mechanism of resource evolution,thus helping the construction of high-quality resources.Based on the theory of information ecology,this study initially establishes an index system of influencing factors on the evolution of E-learning resources by combing and analyzing relevant literature.Subsequently,the index system is revised and improved through the Delphi method.Finally,the intrinsic connection between the factors is analyzed by using the explanatory structural model method,and the explanatory structural model of the factors influencing the evolution of E-learning resources is constructed.Based on the model,this study argues that promoting the evolution of E-learning resources needs to be aimed at increasing the number of users and stimulating their creativity.At the same time,under the premise of ensuring the quality of learning resources,it focuses on the construction of learning platforms and management mechanisms,and thus can comprehensively guarantee the orderly evolution of resources.By identifying the influencing factors of the evolution of E-learning resources,it can provide useful reference and guidance for the construction of high-quality E-learning resources,so as to promote the continuous development of E-learning resources in the direction of better quality and applicability.