Task-technology fit assessment of cloud-based collaborative learning technologies

• Main Authors: Yadegaridehkordi, E., Iahad, N. A., Ahmad, N.
• Format: Book Section
• Published: IGI Global 2017
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/74790/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021377582&doi=10.4018%2f978-1-5225-1918-8.ch020&partnerID=40&md5=0879f94971f0db7f9efcb8559c71d383

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.