远程教育杂志Issue(1)：39-47,9.
基于数据挖掘的学生投入模型与学习分析
Student Engagement Modeling and Learning Analytics Based on Data Mining
摘要
Abstract
Student engagement is widely recognized as the important factor of higher education quality and college outcomes, which is beneficial to undertake higher education assessment and improvement, invoking the active research and practice in higher e-ducation. The study developed a model of student engagement, identified the related factors of student engagement by means of canonical correlation analysis, developed a student topology and mined the engagement behavior clusters based on the student survey data. The results indicated that student engagement was significantly related to student family background, student characteristics be-fore entering college, institution characteristics and coursework. Meanwhile, the student topology based on student engagement was helpful to deepen our understanding of the college student learning behaviors and college outcomes. The results of learning analytics could provide important reference for the institutions which focus on the student-centered and learning centered cultivation programs.关键词
学生投入/学习分析/教育数据挖掘/分类Key words
Students engagement/Learning analytics/Educational data mining/Classification分类
社会科学引用本文复制引用
舒忠梅,徐晓东,屈琼斐..基于数据挖掘的学生投入模型与学习分析[J].远程教育杂志,2015,(1):39-47,9.基金项目
本文系全国教育科学规划教育部重点课题“高等教育学生投入影响因素及作用路径模型与实证研究”（课题编号DIAI40298）的成果之一。 （）
