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.