随着网络和技术的不断发展，泛在学习逐渐成为一种普适的学习方式，它可以满足人们随时可学、随处可学的需求。但泛在学习的有效开展，需要海量的、个性化的、适应性的学习资源作支撑，这与当前静态的、单点存储的学习资源管理模式不相适应。在Web2.0时代，随着微博、微信、抖音、Facebook、Youtube等社交媒体激增以及众包模式的出现，用户逐渐从内容消费者转变为内容生产者，用户生成性内容逐渐成为人们关注的热点，其中百度百科、维基百科、知乎等知识平台为泛在学习资源的建设提供了参考。因此，充分发挥群体的智慧，利用“群建共享”的理念，挖掘用户生成性内容的价值，为满足泛在学习资源的需求提供了可能。

但是，基于“群建共享”的生成性学习资源共建模式仍然存在亟待解决的问题，主要表现在以下三个方面：贡献者群体复杂性高，生成性学习资源质量良莠不齐，缺乏一定的知识体系，碎片化现象严重；缺乏对用户反馈信息的有效、系统性利用；低质量学习资源囤积，削弱泛在学习的质量，导致用户贡献流失。

为解决生成性学习资源建设过程中的典型问题，以知识建构理论、信息生产的制用理论和生命周期理论为指导，本研究从生态学视角出发，将学习资源看作是泛在学习生态系统中的有机体，构建了生成性学习资源质量提升模型，设计和开发了生成性学习资源质量提升系统，并采用问卷调查法和案例研究法对系统的应用效果进行了评价和验证。本研究主要开展了以下三个方面的工作：

1. 围绕资源生命周期构建了集激励引导、共建共享、反馈改进、评估监测于一体的生成性学习资源质量提升模型，实现了以资源为中心，用户角色转变为保障的，针对全生命周期的质量控制和提升。该模型实现了从社会、个体和系统三个维度促进对用户贡献的激励和引导；实现了基于协同知识建构理念的群体资源共建共享；该模型对用户的过程性反馈内容进行了有效利用，实现了基于反馈的、面向用户的资源改进和完善；针对低质量学习资源囤积问题，实现了基于相应指标体系的资源质量的实时监测和评估。

2. 基于学习资源质量提升模型，本研究依托学习元平台设计和开发了生成性学习资源质量提升支撑系统，该系统综合运用了Spring MVC 架构、可视化技术等，核心模块包括基于树状视图的资源协同建构模块、基于社会化批注工具的资源质量改进模块、集普通用户、专家、系统评估于一体的资源质量监测模块和用户贡献激励模块，用以支撑资源全生命周期的质量改进和提升。

3. 以“在线学习的理论与实践”为主题开展学习资源的协同共建和改进，对生成性学习资源质量提升支撑系统进行深入应用，采取问卷调查法和案例分析法对系统的应用效果进行了评估。研究发现，参与者对系统整体的满意度和科技接受度较高，用户认知负荷较低，该系统能够帮助学习资源形成一定的结构体系，有利于学习者有序贡献资源；能够充分利用资源使用者的反馈建议，帮助资源创建者发现资源问题，并有针对性的进行改进和完善，与此同时，还能满足用户之间基于内容的研讨，促进用户积极参与。

通过开展上述工作，较好的解决了生成性学习资源建设和使用过程中的关键问题，并在以下两个方面取得了一定的创新：

1. 从生态学视角出发，基于学习资源的全生命周期，提出了生成性学习资源质量提升模型，弥补了以往资源质量控制的缺陷。本研究以生命周期为基础，充分考虑生成性学习资源在不同生命周期阶段的特征，设计了相应的资源质量提升手段，利用群建共享的理念，充分挖掘用户反馈信息的作用，综合运用多种控制机制，提供了学习资源全生命周期的质量提升保障。

2. 以资源为中心，将社会化批注工具引入到学习资源的质量改进活动中，为基于反馈的学习资源改进提供了新的途径和方法。本研究从资源的角度出发，以提升学习资源质量为目的，创新性的把社会化批注作为资源质量反馈的新途径，为用户提供基于内容的深度参与和积极互动的机会，实现用户知识掌握和资源质量提升的双赢，对于生成性学习资源建设具有比较好的实践意义。

With the continuous development of network and technology, ubiquitous learning has gradually become a general learning style, which can meet the needs of people to learn at anytime and anywhere. However, the effective implementation of ubiquitous learning needs massive, personalized and adaptive learning resources, which is not suitable for the current static and single-point storage learning resource. With micro-blog, WeChat, Tik Tok, Facebook, Youtube and other social media proliferated and crowdsourcing mode appearing in Web2.0 era, users gradually changed from content consumers to content producers. User generated content has gradually draw people’s attention. Baidu Encyclopedia, Wikipedia, Zhihu and other knowledge platforms provide a reference for the construction of ubiquitous learning resources. Therefore, giving full play to the wisdom of the group, using the concept of "group building and sharing", mining the value of user generated content, provides the possibility to meet the needs of ubiquitous learning resources.

However, there are still some problems to be solved in the construction mode of generative learning resources based on "group building and sharing", which are mainly manifested in the following three aspects: the high complexity of the contributors, makes the quality of generative learning resources uneven, lack of a certain knowledge system, fragmentation phenomenon is serious; the lack of effective and systematic use of user feedback information; and the hoarding of low-quality learning resources Product, weaken the quality of ubiquitous learning, lead to loss of user contribution.

In order to solve the typical problems in the process of the construction of generative learning resources, guided by the theory of knowledge building, the theory of information production and the theory of life cycle, this study, from the perspective of ecology, regards learning resources as the organism in the learning ecosystem, the research constructs the model of improving the quality of generative learning resources, designs and develops the quality of generative learning resources The application effect of the system is evaluated and verified by investigation and case study. This study mainly carried out the following three aspects of work:

1. Around the resource life cycle, a generative learning resource quality improvement model integrating incentive guidance, co-construction and sharing, feedback improvement, evaluation and monitoring is constructed, which realizes the quality control and improvement of the resource’s whole life cycle with resource as the center, where the exchange of user role as the guarantee. The model realizes the stimulation and guidance of user contribution from the three dimensions of society, individual and system; realizes the group resource co-construction and sharing based on the concept of collaborative knowledge building; The model makes effective use of the user's process feedback content and realizes the improvement and perfection of user oriented resources based on feedback; Aiming at the problem of low-quality learning resources hoarding, this study designed the corresponding index system to realize the real-time monitoring and evaluation of resource quality.

2. Based on the quality improvement model of learning resources, this study designs and develops a quality improvement support system of generative learning resources based on Learning Cell platform, which uses Spring MVC synthetically Architecture, visualization technology, etc. the core includes the resource collaborative building  module based on tree view, the resource quality improvement module based on social annotation tools, the resource quality monitoring module and the user contribution incentive module integrated with common users, experts and system evaluation to support the quality improvement and improvement of the whole life cycle of resources.

3. Based on the theme of "theory and practice of online learning", the collaborative construction and improvement of learning resources are carried out. The supporting system for improving the quality of generative learning resources is applied in-depth. The application effect of the system is evaluated by questionnaire survey and case analysis. It is found that the participants' satisfaction with the system as a whole, the acceptance of science and technology are high, and the cognitive load of users is low. The system can help the learning resources to form a certain structure system, which is conducive to the orderly contribution of resources by learners. It can make full use of the feedback and suggestions of resource users, help resource creators to discover resource problems, and make targeted improvements and improvements. At the same time, it can satisfy the content-based discussion among users and promote users' active participation.

Through the above work, the key problems in the construction and use of generative learning resources have been solved, and some innovations have been made in the following two aspects:

1. From the perspective of ecology, based on the whole life cycle of learning resources, a generative learning resource quality improvement model is proposed, which makes up for the defects of previous resource quality control. Based on the life cycle, this study fully considers the characteristics of generative learning resources in different life cycle stages, designs the corresponding means to improve the quality of resources, makes full use of the concept of group building and sharing, fully exploits the role of user feedback information, and comprehensively uses a variety of control mechanisms to provide the quality assurance of the whole life cycle of learning resources.

2. Taking resources as the center, social annotation tools are introduced into the quality improvement activities of learning resources, which provides a new way and method for learning resources improvement based on feedback. From the perspective of resources, aiming at improving the quality of learning resources, this study innovatively takes social annotation as a new way of resource quality feedback, provides users with the opportunity of deep participation and active interaction based on content, and realizes the win-win of user's knowledge mastery and resource quality improvement, which has good practical significance for the construction of generative learning resources.