教育虚拟社区:教育大数据的必然回归

Big Data and Learning Analytics for Educational Virtual Community

当前，基于教育大数据的实时决策、数据可视化和个性化学习服务受到人们的热捧，但很少有人从伦理规范和质量保证等视角对基于教育大数据的研究和应用进行反思。本文首先厘定了教育大数据的内涵、特征，然后分析了教育大数据与教育虚拟社区的契合以及教育大数据当前研究和应用中在技术器物、运维机制、使用主体三个层面所凸显出的问题，认为以学习者为中心、具有生态交往文化特性和一定伦理规范的教育虚拟社区可以规避教育大数据当前所面临的问题。基于上述论述，文章提出教育大数据回归教育虚拟社区将是必然，并阐述了实现教育大数据向教育虚拟社区回归的思路或方法。

In recent years， the education real-time decisions， data visualization and personalized learning services based on the educational big data have received scholars' interest， but few people have reflected on the researches and applications of the educational big data on the perspectives of ethical standards and quality assurance. In order to demonstrate the necessity that the development of the educational big data should be combined with the educational virtual community， this article consists of three parts. Firstly， the paper defines educational big data and describes its features and meaning. It also analyzes the commonalities between the educational big data and the educational virtual community on the perspectives of cultural characters， humanism and the contributions to the connection between online learning and traditional education. Secondly， the article reviews the internal and external development of the educational big data and sums up its existing problems in the current. According to Emst Cassirer， we divide the problems into three aspects—technology， operation mechanism， and the users. In the aspect of technology， the digitally deconstructs and reconstructs for the learner， the collection and storage of the data do not take the students in center and form little constructive feedback for the learners. In the aspect of operation mechanism， the interest game between the educational institutions leads to the “data island” and hampers the data interchange. At the same time， the algorithms based on the educational big data could not perceive the circumstances around the learner and could not understand what the learner is really thinking. In the aspect of the users， it lacks of ethics， the quality assurance system and the educational big data analysts. All three aspects restrict the development of the educational big data. On the basis of existing researches， we believe that the characters and the development of the educational virtual community could overcome the drawbacks of the educational big data. Thirdly， this paper states how to realize the educational big data regresses to the educational virtual community. We believe that the characteristics of learner centered of the educational virtual community could avoid meaningless growth of the big data; the ecological interaction between teachers and students could overcome the mechanical reduction for the learner; the community-based educational big data could connect the learners and form the constructive feedback for the learners. So the educational big data should be combined with the educational virtual community. Integrating the educational big data and the virtual community can help highlight the learner' s self-awareness， self-value and self-seeking， and value the learners' rights during the education process.