Does MOOC Quality Affect Users’ Continuance Intention? Based on an Integrated Model

Author:

Gu WeiORCID,Xu Ying,Sun Zeng-Jun

Abstract

Massive open online course (MOOC) is an innovative educational model that has attracted widespread attention in recent years. Despite a growing number of registered users, many have given up continuously using MOOC platforms after the first-time user experience; thus, a high dropout rate has severely hindered the sustainable development of MOOC platforms. To address the problem, this study started with the quality factors of MOOC platforms and the confirmation of user expectations by integrating the D&M ISS model and the expectation confirmation model into one, with the goal of identifying the factors that affect users’ continuance intention to use MOOC platforms. In this study, online questionnaires were distributed to Chinese users with experience in using MOOC platforms, and a total of 550 valid samples were recovered. In addition, the theoretical model was tested using structural equation modeling (SEM). The research results showed that there are three critical antecedents affecting the confirmation of user expectations for a MOOC platform, including information quality, system quality, and service quality, of which service quality has the greatest impact on users’ expectation confirmation. If user expectations for an MOOC platform are positively confirmed, the perceived usefulness of the platform as well as the satisfaction with it will effectively be improved. Moreover, perceived usefulness has been proven to be a critical factor affecting users’ continuance intention to use MOOC platforms, which is followed by user satisfaction. Compared to the original ECM, the integrated research model has delivered significantly improved explanatory power for users’ continuance intention. Hence, this study makes up for the insufficiency of ECM in explaining the factors affecting users’ expectation confirmation and provides theoretical support for MOOC platform developers.

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3