学习分析视角下在线学习干预模型应用

发布时间：2018-05-26 14:54

本文选题：学习分析 + 在线学习　；参考：《现代远程教育研究》2017年04期

【摘要】：基于传统RTI模式构建的在线学习干预模型,是一个循环迭代的干预模型。该模型主要包括五个要素:筛选、监控、多层次干预、决策和分析。研究者利用学习分析技术将在线学习行为数据加以筛选和分析,及时预测可能出现学习风险的学习者从而提供适当的学习干预。该模型的特点:第一,突破现有的以传统课堂环境为背景的学习干预研究,将学习干预模型应用于在线学习的真实情境;第二,从学习分析的视角逐步明确和细化学习干预的方法、过程和策略并借助技术工具实施可操作且有效的干预措施;第三,通过问卷调查、SPSS和个别访谈的方法,从学习者的角度对在线学习干预模型的有效性进行了评估。模型实验结果表明,在线学习干预模型的应用效果较好,实验对象的学习结果与模型预测的结论较为一致,且被干预的学习者能够适应干预策略和措施,有效地规避了学习风险。
[Abstract]:The online learning intervention model based on traditional RTI model is a circular iterative intervention model. The model consists of five main elements: screening, monitoring, multi-level intervention, decision-making and analysis. The online learning behavior data are screened and analyzed by using the learning analysis technique, and the learners who may have learning risk can be predicted in time to provide appropriate learning intervention. The characteristics of the model are as follows: first, break through the existing study of learning intervention in the traditional classroom environment, and apply the learning intervention model to the real situation of online learning; second, From the perspective of learning analysis, we gradually define and refine the methods, processes and strategies of learning intervention and implement operational and effective intervention measures with the help of technical tools. The effectiveness of online learning intervention model was evaluated from the perspective of learners. The results of the model experiment show that the online learning intervention model has a good effect, and the learning results of the subjects are consistent with the predicted results of the model, and the affected learners can adapt to the intervention strategies and measures. Effectively avoid learning risks.
【作者单位】：浙江师范大学教育技术学系;华东师范大学;
【基金】：教育部人文社会科学一般项目“混合学习RTI适应性干预模型构建及其应用研究” 浙江师范大学第五期研究生课程教学改革项目
【分类号】：G434

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