An Integrated LDA-QFD Approach for Improving Online Course Quality Based on Learners' Reviews

被引：0

作者：

Wang, Rui ^{[1
]}

Ling, Haili ^{[1
]}

Chen, Jie ^{[1
]}

Fu, Huijuan ^{[1
]}

机构：

[1] Jiangxi Univ Sci & Technol, Ganzhou, Peoples R China

来源：

INTERNATIONAL JOURNAL OF DISTANCE EDUCATION TECHNOLOGIES | 2025年 / 23卷 / 01期

基金：

中国国家自然科学基金;

关键词：

Course Quality; Learners' Need; MOOCs; Online Review; Quality Function Deployment; HIGHER-EDUCATION; DESIGN;

D O I：

10.4018/IJDET.371203

中图分类号：

G40 [教育学];

学科分类号：

040101 ; 120403 ;

摘要：

This study adopted the Latent Dirichlet Allocation (LDA) to extract learners' needs based on 70,145 reviews from online course designed for software design and development in China and then applied Quality Function Deployment (QFD) to map learners' differentiated needs into quality attributes. Taking national first-class courses as the benchmarking object to identify the key quality attributes expected from massive open online courses (MOOCs), the findings reveal that course video, exercise, teaching schedule, and presentation of course material are pivotal factors in the enhancement of online course quality. Among these, presentation of course material and teaching schedule are identified as priority factors of quality improvement, whereas course video and exercise are recognized as supplementary factors. The findings of this research provide effective guidance for MOOC educators to improve course quality.

引用

页数：24

共 48 条

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