Predicting adult students’ online learning persistence: a case study in South Korea using random forest analysis

IF 1.9 4区教育学 Q2 EDUCATION & EDUCATIONAL RESEARCH

Innovations in Education and Teaching International Pub Date : 2024-01-22 DOI:10.1080/14703297.2024.2305939

Na-Ra Nam, Sue-Yeon Song

引用次数: 0

Abstract

This empirical study uses a random forest algorithm to examine the factors that influence learners’ persistence in online learning at a prominent Korean institution. The data were collected from st...

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预测成人学生在线学习的持续性：利用随机森林分析法进行的韩国案例研究

本实证研究采用随机森林算法，考察了影响韩国一所著名院校在线学习者坚持学习的因素。数据收集自韩国著名大学的学生。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Innovations in Education and Teaching International EDUCATION & EDUCATIONAL RESEARCH-

CiteScore

4.80

自引率

5.60%

发文量

期刊介绍： Innovations in Education and Teaching International (IETI), is the journal of the Staff and Educational Development Association (SEDA) www.seda.ac.uk. As such, contributions to the Journal should reflect SEDA"s aim to promote innovation and good practice in higher education through staff and educational development and subject-related practices. Contributions are welcomed on any aspect of promoting and supporting educational change in higher and other post-school education, with an emphasis on research, experience, scholarship and evaluation, rather than mere description of practice.