Task-Technology Fit Assessment of Cloud-Based Collaborative Learning Technologies

Abstract

Universities require basic changes in knowledge and communication-based society in order to achieve higher order learning experience and to satisfy expectations of new generation of students. This study aims to understand the likelihood of the cloud-based collaborative learning technology adoption within educational environments. Reviewing cloud computing research, technology characteristic construct was divided into collaboration, mobility, and personalization. Based on the Task-Technology Fit (TTF) model, this study tested a theoretical model encompassing seven variables: collaboration, mobility, personalization, task non-routineness, task interdependence, task-technology fit, user adoption. Purposive sampling was used and data were collected from 86 undergraduate and postgraduate students who had experiences in using cloud-based applications for collaborative activities. The results indicated that task non-routineness, collaboration, mobility, and personalization have positive significant effects on TTF. However, distinct from past studies, task interdependence positively influences TTF. In addition, results indicated that the significant effect of TTF on users' intention to adopt cloud-based collaborative learning technologies was considerable.