基于大数据的个性化自适应在线学习分析模型及实现

发布时间：2018-03-25 01:14

本文选题：大数据　切入点：个性化自适应学习　出处：《中国电化教育》2015年01期

【摘要】：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。
[Abstract]:Through big data's learning analysis model, we can deeply explore the learners' learning process and situation, and find out the learning rules. According to the needs and abilities of each student to provide individualized adaptive learning, this study summarizes the connotation and application of big data. This paper puts forward big data's "big" from a microscopic perspective, not in its "large capacity", but in analyzing the comprehensiveness and potential "great value" of the data. A personalized adaptive online learning analysis model is constructed from the four dimensions of data and environment (data and environment), who (method) and target (Why). Taking the "C language programming" course learning as an example, the learning process structure based on big data's individuation adaptive learning process is presented. The results show that the data analysis of students' learning behavior and knowledge mastery can recommend a reasonable learning path and appropriate learning resources. It can provide timely and accurate feedback on students' learning effect, provide individualized service intervention, and promote teaching and learning.
【作者单位】：东北师范大学计算机科学与信息技术学院;辽宁师范大学计算机与信息技术学院;吉林大学教育技术中心;
【基金】：教育部人文社会科学研究青年基金项目“自适应学习系统理论模型建构及其效果实证研究”(项目编号:12YJCZH086) 东北师范大学哲学社会科学校内青年基金团队项目“吉林农村中小学教师远程学习适应性研究”(项目编号:130021049) “中央高校基本科研业务费专项资金”阶段性成果
【分类号】：G434

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