摘要
Web3.0时代的学习处于“富工具”和“富资源”的数字化网络环境中，数字化学习资源日益丰富，获取渠道日益多元，学习理念不断变革，学习方式不断创新，知识更新的速度越来越快，因此，每个学习个体都不可能拥有所有的知识资源，当知识资源为学习个体所需，而又不为学习个体所知时，寻找知识资源的出处、获取知识间的关联比学习知识本身更重要。同时，丰富的开放学习资源为学习者提供了平等的学习条件，学习者在享受丰富的资源的同时，也易迷失在资源的海洋中，产生认知负荷，无法找到真正自己需要的资源。面对浩如烟海、杂乱无章的学习资源，如何快捷高效地聚合自己需要的知识资源，构建个人知识网络，满足学习者学习需求；并将聚合来的开放学习资源有效地分享出去，使学习资源得以高效利用，已成为目前国内外学者的研究热点。
本研究从联通主义学习观出发，将“学习即知识的连结”理念贯穿学习始终，强调学习者个人主动参与对资源聚合与分享的影响，运用“合作共建”、“协同编辑”、“共同评价”、“大众分类”等充分发挥“集体智慧”的方法，全面推进开放学习资源聚合与分享这一方向的研究。主要完成了基于集体智慧的开放学习资源聚合与分享框架的设计，并重点对该框架中的两大核心组件；两大核心内容；三大运行保障机制进行了深入的研究，并依据研究成果设计开发学习平台，进行实验，验证其效果。研究内容主要包括以下四部分：
（1）在学习者模型和领域知识模型两大核心组件研究中，主要依据学习者的网络学习行为构建学习者模型，学习者模型作为开放学习资源按需聚合与个性化分享的依据，在整个研究中占据极其重要的地位；从个体领域知识模型出发，发挥学习者创造的集体智慧，构建领域知识模型，领域知识模型是知识与开放学习资源关联的桥梁，在整个研究中起到关联媒介的作用。
（2）在开放学习资源聚合与开放学习资源分享两大核心内容研究中，主要依据学习者模型和学习者间交互创造的集体智慧，运用“合作共建”、“协同编辑”、“共同评价”、“大众分类”等充分发挥“集体智慧”的方法，以领域知识模型为桥梁，通过采用个体聚合与集体聚合、手动聚合与自动聚合相结合的方式聚合开放学习资源，并通过学习者主动分享和系统推荐两种方式分享聚合来的开放学习资源。
（3）在学习者参与激励机制、开放学习资源运行保障机制及可视化呈现机制三大运行保障机制研究中，主要依据马斯洛需求层次理论设计学习者参与激励机制；依据资源成长、进化及演化等生态学规律设计开放学习资源质量保障机制；采用标签云和知识地图，设计了可视化呈现机制，以保障基于集体智慧的开放学习资源聚合与分享的持续高效运行。
（4）依据上述研究成果，设计了平台的框架及相关对象模型、关系模型，完成了基于集体智慧的资源聚合与分享平台的开发，采用实验研究法，通过主观与客观，定性与定量的方法，从学习者和学习资源两个维度对本研究成果进行评价，研究结果表明，在学习者参与度、满意度、学习意愿及资源的聚合与分享效果等方面都取得了良好的效果。
本研究主要实现“自主学习理念”和“开放学习资源聚合与分享方法”两大创新。其一，将“学习即知识的连结”理念贯穿学习始终，将单纯的学习知识转变为关注知识获取的渠道，强调学习者主动参与的行为，充分发挥学习者交互创造的“集体智慧”，将学习的过程融入到个人社会化知识资源网络建构中来,实现了自主学习理念的创新。其二，突破了学习资源聚合与分享的研究框架，将研究的重点从学习资源聚合与分享的技术手段转变为学习资源聚合与分享的方式，将学习资源聚合与分享的主体由“系统”转变为“学习者”，依据学习者学习行为,尊重学习者主动参与,运用“合作共建”、“协同编辑”、“共同评价”、“大众分类”等充分发挥“集体智慧”的方法，依靠“人”本身强大的语义理解与处理能力，而不是通过计算机相关算法来处理判断语义，来干涉学习资源聚合与分享的结果，实现开放学习资源聚合与分享方法的创新性探索。
The study in Web3.0era is in the digital network environment of “rich tool” and“rich resource”. The digital learning resources are rich day by day, access channels areincreasingly diverse, the learning concept is changed continuously, learning method isinnovated constantly, knowledge is updated faster and faster, thus individual cannotmaster all the knowledge. It is important to seek the source of knowledge andinter-related relationship of knowledge than learning knowledge itself when eachindividual needs these resources. Meanwhile, the rich open learning resources provideequal opportunities for learners, while learners get lost in the resources when theyenjoy rich resources and they cannot really find the resources they need. How toaggregate the needed resources, build personal knowledge network, then share theopen learning resources to use them efficiently has become hot research topic amongscholars home and abroad.
Combining the concept of “learning—linking of knowledge”, this study startedfrom Connectivism and emphasized the individual active participation. Thatcomprehensively propelled the research on aggregation and sharing of open learningresources. The methods used in this study are the method of “co-build”,“collaborativeediting”,“co-evaluation” and “folksonomy”. This study designed the framework ofopen learning resource aggregation and sharing, which based on collectiveintelligence, the research focused on two core components of the framework, two corecontents and three running safeguard mechanisms. According to the research results，the learning platform is designed and conducted to verify its effectiveness. The studyincludes the following four parts:
(1) In the study of two core components of the “learner model” and “domainknowledge model”, learner model is built on the learner’s behavior. It is the basis ofaggregation and sharing of open learning resources and occupies a very importantposition in the research. Individual knowledge model form the basis of the domainknowledge model, which functions as a media, connecting knowledge with openlearning resources in the whole study.
(2) In the research of two core contents of the “aggregation open learningresources “and “sharing open learning resources”, domain knowledge model isconstructed on the basis of learner model, and is used the methods of “co-build”, “collaborative editing”,“co-evaluation”，and “folksonomy”. Open learning resourcesare aggregated through individual and collective way or through manual andautomatic approach. Then these open learning resources are shared through activelearners and system recommendation
(3) Maslow’s hierarchy of needs is used to design incentive mechanism oflearner participation in the research of three guarantee mechanisms, which are“incentive mechanism of learner participation”,“protection mechanism of openlearning resources” and “visualization mechanism”. The protection mechanism ofopen learning resource is designed on the growth, evolution of resources, as well asother ecological rules. Tag clouds and knowledge map are used to design visualizationmechanism, which protect the efficient operation of aggregation and sharing of openlearning resources based on collective intelligence.
(4) The framework of the platform and the related object model, and therelational model are designed. The platform of resources aggregation and sharingbased on collective intelligence is implemented. The study result is evaluated in theperspective of “subjective” and “objective”,“qualitative” and “quantitative”,“learner” and “resource”. The findings achieve good results in learner’s participation,satisfaction, aspiration，resources aggregation and sharing effect.
In this study, two innovations are realized, which are “self-learning concept” and“aggregation and sharing methods of open learning resource”. Firstly, with theconcept of “learning—linking of knowledge” running through the study, the processof learning is integrated into the construction of social knowledge network. The studyemphasized the active participation of learners, transforming pure knowledge learninginto knowledge acquisition experience, which gives full play to the “collectiveintelligence” through the interaction of learners. Secondly, the framework ofaggregation and sharing of open learning resources is broken. The research focuses onthe way of aggregation and sharing of open learning resources instead of meretechnical terms. The subject shifts from system to learners. Learners’ activeparticipations are respected with the application of different research methods, like“co-build”,“collaborative editing”,“co-evaluation” and “folksonomy”, which givefull play to “collective intelligence”. This study relies on the semantic comprehensionand processing ability of individuals instead of using computer algorithms to calculatethe semantic meaning of language, which will intervene on the results of theaggregation and sharing of open learning resources. The study tries to makeexploratory innovation to achieve the aggregation and sharing of open learningresources.
引文
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