基于数据挖掘的互联网环境下大学生深度学习影响因素实证研究

Research on the Factors Affecting Students' Deep Learning in e-Learning Environment Based on Data Mining Methods

互联网时代为高校教学改革提供多元的教育模式丰富的学习资源,而网络的使用是否真地提升学习效果,很大程度上是直接取决于学习者在互联网学习情境下的深度学习水平。基于深度学习理论,通过采集C语言学习者学习风格、学习行为等特征数据,利用计算机数据分析的思路阐述网络环境下大学生深度学习的现状和个体特征的影响情况,并通过数据挖掘进一步分析得到:浏览并整合网络资源是最重要的影响因素。

Internet provides multiple education models and abundant resources for teaching reform of higher education. However, whether the using of Internet really promotes the learning outcome is largely dependent on learners＂ deep learning capability. Based on deep learning theories, collects features of C Programing course learners＂ learning styles, learning behaviors, etc., and then applies data mining methods to explore the curi＇ent status of learners＂ deep learning and how individual features influence learners＂ deep learning in e-learning environment. Fur- thermore, abstracts six key influence factors, among which browsing and integration of resources from Internet is the most influential factor.