基于大数据的个性化自适应在线学习分析模型及实现

Realization of Individual Adaptive Online Learning Analysis Model Based Big Data

通过大数据学习分析模型,能够深入探究学习者的学习过程与情境,发现学习规律,根据每一个学生的需求和能力为其提供个性化自适应学习。本研究综述了大数据的内涵及应用,从微观视角提出了大数据之"大",不在于其表象的"大容量",而在于分析数据的全面性和潜在的"大价值"。基于大数据分析,从数据与环境(What)、关益者(Who)、方法(How)和目标(Why)等4个维度构建个性化自适应在线学习分析模型。以《C语言程序设计》课程学习为例,从基于大数据个性化自适应的学习过程结构、学习过程可视化及学习效果实证等方面进行分析,研究结果表明对学生学习行为与知识掌握的数据分析,能够推荐合理的学习路径与恰当难度的学习资源,可对学生的学习效果做及时准确的反馈,提供个性化服务干预,有利于促进教与学。

Learning analysis model based big data helps to explore learning process, learning situation, learning principles and provide individual adaptive learning based on learner requirements and ability. Firstly, this paper summarizes the intension and application of big data and especially emphasizes that big data is not higher volume but high value. Secondly, individual adaptive online learning analysis model is built based on four dimensions, namely data and environments（what）, stakeholders（who）, methods（how） and objectives（why）.Finally, Taking C language program design for example, this paper analyzes learning process structure, visualization and learning effect. The results show that individual learning which analyzing learning behavior, recommending reasonable learning path and learning resource can promote the teaching and learning, especially for underachievers.