电子书包中基于大数据的学生个性化分析模型构建与实现路径

The Model Construction and Implementation Path of Students’ Personality Analyzing Based on Big Data

该文在对大数据特征分析的基础上，对电子书包各学习系统生成大数据的缘由进行了分析，并以学生电子书包中电子学档系统所记录的结构化、半结构化以及非结构化的大数据信息为分析对象，以学生个性化学习、个性心理学和学习分析为理论依据，构建了基于电子书包大数据的学生个性化分析模型。该模型以学习内容个性化、学习活动个性化、学习方式个性化和学习评价个性化为分析维度，以相关的系统数据库支持为出发点，对系统中的学生个性化信息进行分类汇聚。在此基础上，通过对各系统要素间的语义关系进行分析，建立了学生个性化分析模型要素的关系框架，并从个性化学习资源推送、个性化学习过程监控与指导以及个性化学习社区推荐等三个方向分析了学生个性化分析模型的实现路径，以期为今后开展基于大数据的学生个性化学习分析研究提供理论指导。

This paper analyzes the reason for the big data generated by the system of electronic schoolbag on the basis of analyzing the feature of big data. And it regards the information of big data which includes structured data， semi-structured data and unstructured data as analyzing object and the theories which include personalized learning， personality psychology and learning analytics are considered as theoretical basis. Then an analyzing model of students’ personality is constructed based on the big data generated by electronic schoolbag. The model consists of four analysis dimensions which are personalized learning content， personalized learning activities， personalized learning styles and personalized learning evaluation. The personalized information is classified and gathered based on the support of relative system database. Furthermore， relational framework of the element for personalized model is established by analyzing the semantic relationships among the various elements of the systems. Implementation paths are showed from three directions which include pushing personalized learning resources， personalized learning process monitoring and guidance and pushing personalized learning community so that it can provide theoretical guidance for the analysis of personalized learning based on big data in the future.