软件导刊2025，Vol.24Issue(2)：198-203,6.DOI:10.11907/rjdk.241709
基于MOOC学习平台的学习行为数据分析与预测
Data Analysis and Prediction of Learning Behavior Based on MOOC Learning Platforms
谢晓宇 1范深 2宋金玉 1张所娟 1于坤1
作者信息
- 1. 陆军工程大学 指挥控制工程学院,江苏 南京 210006
- 2. 陆军海防332旅,辽宁 大连 116000
- 折叠
摘要
Abstract
In order to promptly grasp the learning situation of students on MOOC platforms and provide targeted tutoring and intervention,this study utilized data mining techniques to analyze the learning behavior data of students in the"principles and applications of databases"MOOC course at the Army Engineering University.By collecting six behavioral characteristics,including test scores,chapter scores,and video watch-ing duration,it was found that these characteristics are significantly correlated with academic performance.Using the K-means clustering algo-rithm,students were categorized into four learning types:ideal,diligent,top student,and at-risk,and an academic early warning model was constructed.Targeted early warning intervention measures were proposed to improve learning outcomes and avoid academic risks.This study provides a basis for educators to improve teaching methods and enhance teaching quality.关键词
MOOC学习平台/在线学习/学习行为分析/学业预警Key words
MOOC learning platform/online learning/learning behavior analysis/academic warning分类
社会科学引用本文复制引用
谢晓宇,范深,宋金玉,张所娟,于坤..基于MOOC学习平台的学习行为数据分析与预测[J].软件导刊,2025,24(2):198-203,6.
