基于社交网络的个性化学习环境构建研究

Research on Construction of Personalized Learning Enviroments Based on Social Network

随着信息技术和学习理论的发展，教育研究的焦点逐渐从“以教为中心冶向“以学为中心冶转变，对 学习的研究也逐渐从对学习者本身的研究转向对学习环境的研究。社交网络模拟了人类社会生活与社会关系， 其理念契合了社会建构主义、关联主义、分布式认知等学习理论，更加符合网络时代学习的社会性、关联性、分布 性、碎片化、个性化等特征。本研究在分析现有网络学习环境的基础上，提出以社交网络模型为资源聚合与推荐 框架设计新型学习环境的思路，对个人学习空间、学习资源聚合模式和个性化推荐引擎构建等学习环境设计要 素进行了分析。社交网络可以实现“网络学习空间人人通冶，学习环境内外资源的个性化聚合，并记录学习过 程。通过对大量学习行为数据的分析，可以辅助教学决策，优化学习过程，推荐符合学习者个性的学习资源，实 现个性化学习。最后，本研究基于开源社会性软件Sakai OAE 构建了个性化学习环境并进行了实际应用，结果 表明该学习环境在用户易用性和技术接受度等方面取得了较好效果。

The development of information technology and learning theory presents several new features: 1) Knowl edge is constructed with social interaction and the meaning is generated in social and cultural settings and with other 's help. Using social learning framework to promote learning interaction is important. 2) There is a need for knowl edge share and learning tools and models. 3) Learning is about network creation as indicated by the connectivism the ory. Knowing where to find knowledge is more important than the knowledge itself. So we need to provide learners a personal learning space for knowledge to aggregate， manage and share. 4) Learning not only requires different learn ing strategies， but also personalized resources according to the learners' personality traits. Therefore， teaching and de sign of the learning environment need shifts from a ＂ teaching-centered＂ approach to ＂ learning-centered＂ one. We educators need to explore more intelligent and efficient personalized framework to promote the effective interaction and to foster learning community. Social network mirrored the interaction and social relationship of human society and its design ideas are aligned with the social constructivism， connectivisim， distributed cognition and other learning theo ries. Therefore， a social network framework can be used to build a learning environment which will fit well with the socialization， connection， distribution， fragmentation and personalization features of learning. This paper discussed the following aspects. First， the paper analyzed how to use social network to construct per sonal learning space. Personal space of social networking can be thought as ＂ network memory space. ＂ Learners can associate aggregate learning resources into their space and manage or share it easily. Second， this paper analyzed the learning resource aggregation patterns and principles. Learning resources aggre gation mainly has two ways: one is the outside learners of learning platform who can aggregate resources into the platform， and theother is the inner user of the learning platform allowing users to share their resources with other learners. Third， the paper analyzed the construction of personalized recommendation engine. Social network user interac tion can produce big behavioral data in the process of learning， via analysis of the big data， which could help teach ing decisions and optimize the learning process. Lastly， this study adopted the open source social software which named Sakai-OAE to build a personalized learn ing platform and applied it to practice. The results showed that the usability and user acceptance are great.