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Usability factors predicting continuance of intention to use cloud e-learning application

机译:预测使用云电子学习应用程序意图的持续性的可用性因素

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摘要

In this ever-progressive digital era, conventional e-learning methods have become inadequate to handle the requirements of upgraded learning processes especially in the higher education. E-learning adopting Cloud computing is able to transform e-learning into a flexible, shareable, content-reusable, and scalable learning methodology. Despite plentiful Cloud e-learning frameworks have been proposed across literature, limited researches have been conducted to study the usability factors predicting continuance intention to use Cloud e-learning applications. In this study, five usability factors namely Computer Self Efficacy (CSE), Enjoyment (E), Perceived Ease of Use (PEU), Perceived Usefulness (PU), and User Perception (UP) have been identified for factor analysis. All the five independent variables were hypothesized to be positively associated to a dependent variable namely Continuance Intention (CI). A survey was conducted on 170 IT students in one of the private universities in Malaysia. The students were given one trimester to experience the usability of Cloud e-Learning application. As an instrument to analyse the usability factors towards continuance intention of the application, a questionnaire consisting thirty questions was formulated and used. The collected data were analysed using SMARTPLS 3.0. The results obtained from this study observed that computer self-efficacy and enjoyment as intrinsic motivations significantly predict continuance intention, while perceived ease of use, perceived usefulness and user perception were insignificant. This outcome implies that computer self-efficacy and enjoyment significantly affect the willingness of students to continue using Cloud e-learning application in their studies. The discussions and implications of this study are vital for researchers and practitioners of educational technologies in higher education.
机译:在这个不断发展的数字时代,传统的电子学习方法已经不足以应对升级的学习过程的要求,尤其是在高等教育中。采用云计算的电子学习能够将电子学习转变为一种灵活的,可共享的,可重复使用的内容以及可扩展的学习方法。尽管跨文献提出了大量的Cloud e-learning框架,但进行了有限的研究来研究可预测使用Cloud e-learning应用程序的持续性的可用性因素。在这项研究中,已经确定了五个可用性因素,即计算机自我效能感(CSE),娱乐性(E),感知的易用性(PEU),感知的有用性(PU)和用户感知(UP)进行因素分析。假设所有五个自变量都与因变量即连续意图(CI)正相关。对马来西亚其中一所私立大学的170名IT学生进行了调查。给学生上三个月的时间来体验Cloud e-Learning应用程序的可用性。作为分析针对应用程序持续意图的可用性因素的工具,制定并使用了包含三十个问题的问卷。使用SMARTPLS 3.0分析收集的数据。从这项研究中获得的结果表明,计算机的自我效能感和享受作为内在动机可以显着预测持续性意图,而感知的易用性,感知的实用性和用户感知则微不足道。这一结果表明,计算机的自我效能感和娱乐性会极大地影响学生在学习中继续使用Cloud e-learning应用程序的意愿。这项研究的讨论和启示对高等教育的研究人员和教育技术从业者至关重要。

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