실시간 및 비실시간 온라인 학습 시스템의 품질 개선 연구: IPA와 토픽 모델링을 활용하여

Abstract

This study aims to propose quality improvement measures for online learning systems by comparing learning experiences in synchronous and asynchronous learning modes. Based on 1,551 learner reviews, topic modeling identifies key learning attributes and positive and negative importance-performance analysis (IPA) is performed. A t-test is also performed to quantitatively compare ‘instructor delivery skills’ and overall satisfaction. The results show that ‘instructor delivery skills’ is the most important key attribute in both learning modes, and ‘instructor delivery skills’ and overall satisfaction are rated significantly higher in the asynchronous learning mode than in the synchronous learning mode. In synchronous learning mode, ‘content quality’ and ‘learning autonomy’ are identified as key attributes with ambivalence. In the asynchronous learning mode, ‘content quality’ serves as the main attribute that leads to learner satisfaction, while ‘learning autonomy’ functions as a stable attribute that does not lead to dissatisfaction. In particular, this study is significant in that it systematically identifies the impact of key attributes of each learning mode on the learning experience using positive and negative IPA. The findings suggest the need to mitigate the negative impact of time constraints on the learning experience in synchronous learning mode and complement interactivity in asynchronous learning mode. It also provides practical suggestions for improving the quality of the learning experience through customized improvement strategies for each learning mode.