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

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Бібліографічні деталі
Опубліковано в::International Journal of Distance Education Technologies vol. 23, no. 1 (2025), p. 1-25
Автор: Wang, Rui
Інші автори: Ling, Haili, Chen, Jie, Fu, Huijuan
Опубліковано:
IGI Global
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Короткий огляд: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.
ISSN:1539-3100
1539-3119
DOI:10.4018/IJDET.371203
Джерело:ABI/INFORM Global