An adoption model for cloud-based collaborative learning applications from top Malaysian universities' experience

• Main Author: Yadegaridehkordi, Elaheh
• Format: Thesis
• Language: English
• Published: 2015
• Subjects: QA76 Computer software
• Online Access: http://eprints.utm.my/id/eprint/61100/1/ElahehYadegaridehkordiPFC2015.pdf; http://eprints.utm.my/id/eprint/61100/; http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:94616

Cloud-based collaborative learning applications are new computing paradigms which facilitate collaborative activities in a centralized location. These applications offer various benefits to higher education. However, even though previous research have discussed cloud computing in general, there is still lack of studies considering students’ intention to adopt cloud-based collaborative learning applications in university settings especially in the context of Malaysian universities. Therefore, this research aims to develop and test an adoption model for cloud-based collaborative learning applications for Malaysian universities by integrating Unified Theory of Acceptance and Use of Technology (UTAUT) and Task Technology Fit (TTF). A preliminary investigation using face-to-face interviews with directors of Information Technology centers and administrators of students email in four selected top Malaysian universities was conducted to understand the current adoption status of cloud-based collaborative learning applications. Next, using purposive sampling, a survey which involved 209 students was conducted to collect data from students who have had experience in using cloud-based collaborative learning applications such as Google Apps and/or Office 365. Partial Least Squares (PLS) method based on Structural Equation Modelling (SEM) was used for analyzing the survey data. Smart PLS 2.0M3 was applied to validate the research model. The overall analysis results showed that characteristics of cloud computing and collaborative task significantly predict the fit between these constructs. Furthermore, Task Technology Fit together with, Performance Expectancy, Social Influence, and Facilitating Conditions significantly influenced intention to adopt cloud-based collaborative learning applications. Findings confirmed that individual and group characteristics were significant drivers of Performance Expectancy and Effort Expectancy. Finally, this research develops a Cloud-Based Collaborative Learning Applications Adoption Model that can serve as a tool to assist the Ministry of Education, university administrators, and cloud service providers to plan their strategies and provide supportive adoption environment for cloud-based collaborative learning applications in universities.