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.

Examining Student Participation in Three Learning Activities Supported by Social Annotation Tools

“…Motivation is certainly one major contributing factor to learners' participation (Xie & Ke, 2011). Apart from this, research on collaborative learning suggests some other factors attributable to the differences in learners' degree of participation such as learners' learning styles and their personalities (Durán, 2011;Yadegaridehkordi et al, 2013). It is largely unclear why the levels of participation are so different among students in this particular study, and there is a need for future research investigating how to optimize student participation in SA-supported collaborative learning activities.…”

“…In fact, the majority of extant studies pertaining to collaborative learning were conducted in online environments such as discussion forums, wikis, and blogs (Yadegaridehkordi, Iahad, & Ahmad, 2013). Contrastingly, SA tools were rarely examined.…”

Analyzing Continuance of Cloud Computing in Higher Education Institutions: Should We Stay, or Should We Go?

“…According to [11], the decision to discontinue an adopted system might also be influenced by environmental or institutional pressures and further investigation will have to take additional perspectives to understand organizational level continuance. Consequently, COL was added as an organisational factor [82][83][84][85]. At the same time, CP [15,86] and RP [86][87][88] were identified as environmental factors.…”

“…At the same time, CP [15,86] and RP [86][87][88] were identified as environmental factors. COL is an essential aspect of HEIs, and CC services facilitate effective communication among the stakeholders [82,83], especially in the digital natives [89,90]. Table 2 shows a mapping analysis matrix that depicts the theories and constructs derived from the literature [91,92].…”

“…Currently, COL is a significant determinant of HEI success. CC facilitates and offers new methods of collaboration between stakeholders in HEIs [82,83]. Current generation of learners in HEIs being described as digital natives needs the Internet to perform routine tasks [89,90] and engage in collective online activities (e.g., studying in groups, socialising, and so on) [106].…”