利用学习分析技术预测学习者学业成绩

摘要

学习分析通过测量、收集和分析数据来提升学习者的学习体验.全球高等教育机构目前广泛使用学习管理系统(LMS), 除了基于学习管理系统的数据外,研究者还常利用学生的其他数据,如课堂出勤、作业分数、测验和期末考试成绩,来评估学生的学习经历.本文旨在找出哪些因素可以用来及时鉴别课程中表现不佳的学生,通过收集并分析香港城市大学一门非全日制文凭课程的学习管理系统数据和学生相关数据,运用多元线性回归分析法,探索这些数据对学生学业成绩的影响.研究发现,课程作业对学生的期末考试成绩有显著影响.%Learning analytics involves the measurement,collection and analysis of data for the purpose of enhancing learning experience of learners.The use of learning management systems (LMS) is very popular with many local and overseas higher education institutions.In addition to LMS-based data,other student-based data such as class attendance,assignment marks,test and final examination scores of courses offered in an academic programme are typical data that are used to assess the learning experience of students.This paper aims to identify factors that could be used to identify those students who are not performing well in the programme timely.Both LMS-based and student-based data relating to a local part-time diploma programme are collected and analysed to study the effect of them on students' academic performance using the multiple linear regression technique.It was found that coursework has significant effect on the final ex-amination performance of students.