User perceptions of the technology characteristics in a cloud-based collaborative learning environment: a qualitative study

The purpose of this study was to assess user perceptions of technology characteristics, which is a complicated construct in task technology fit model, in a cloud-based collaborative learning environment. For this purpose, cloud computing characteristics cited in the previous related research, were categorised into cost saving, ease of implementation, flexibility, mobility, scalability, sustainability, personalization, processing capabilities, agility, collaboration, usability, risk reduction, measured service, on demand self-service, and resource pooling. Interviews were then conducted with students who had some experience in using cloud-based applications for collaborative learning. Directed content analysis was performed using ATLAS.ti software to organise the coding process. The results of coding data showed that collaboration, mobility, and personalisation, which resulted from previous related literature, are also cited by a large number of participants in interviews as being significant characteristics of cloud-based collaborative learning applications. Organisational cost saving, ease of implementation, flexibility elasticity, scalability, sustainability, processing capabilities, agility, usability, risk reduction, measured service, on demand self-service, and resource pooling were not mentioned by any of the participants at all. However, easy monitoring and assessment, time control and saving, cost saving, accessibility, ease of use, and easy connection to other applications were new themes that emerged inductively during data analysis.

[1]  Mervat Adib Bamiah,et al.  Challenges and Benefits for Adopting the Paradigm of Cloud Computing , 2011 .

[2]  Jan Blom A theory of personalized recommendations , 2002, CHI Extended Abstracts.

[3]  Andrew F. Monk,et al.  Theory of Personalization of Appearance: Why Users Personalize Their PCs and Mobile Phones , 2003, Hum. Comput. Interact..

[4]  Omar F. El-Gayar,et al.  Evaluating the Impact of Electronic Health Records on Clinical Reasoning Performance , 2012, 2012 45th Hawaii International Conference on System Sciences.

[5]  M. T. Alam Cloud Computing in Education , 2013, IEEE Potentials.

[6]  Lionel Q. Mew,et al.  Online social networking: a task-person-technology fit perspective , 2009 .

[7]  Diana G. Oblinger Boomers, Gen-Xers, and Millennials: Understanding the "New Students.". , 2003 .

[8]  M. Monaco,et al.  The Millennial Student: A New Generation of Learners. , 2007 .

[9]  Hsiu-Fang Hsieh,et al.  Three Approaches to Qualitative Content Analysis , 2005, Qualitative health research.

[10]  P. Y. Thomas,et al.  Cloud computing: A potential paradigm for practising the scholarship of teaching and learning , 2011, Electron. Libr..

[11]  Dale Goodhue,et al.  Understanding user evaluations of information systems , 1995 .

[12]  Viswanath Venkatesh,et al.  Adoption of Collaboration Technologies: Integrating Technology Acceptance and Collaboration Technology Research , 2008 .

[13]  Shahriar Akter,et al.  An Assessment of M-Health in Developing Countries Using Task Technology Fit Model , 2011, AMCIS.

[14]  A. Dongre,et al.  Application of Qualitative Methods in Health Research: An Overview , 2010 .

[15]  Dale Goodhue,et al.  Task-Technology Fit and Individual Performance , 1995, MIS Q..

[16]  Bryce Allen,et al.  Content Analysis in Library and Information Science Research. , 1990 .

[17]  Yan Zhang,et al.  Qualitative Analysis of Content by , 2005 .

[18]  Siti Fatimah Abdul Razak,et al.  Cloud computing in Malaysia Universities , 2009, 2009 Innovative Technologies in Intelligent Systems and Industrial Applications.

[19]  David C. Yen,et al.  Determinants of users' intention to adopt wireless technology: An empirical study by integrating TTF with TAM , 2010, Comput. Hum. Behav..

[20]  Itzhak Harpaz,et al.  Advantages and disadvantages of telecommuting for the individual, organization and society , 2002 .

[21]  Marjan Laal,et al.  Collaborative learning: what is it? , 2012 .

[22]  Barbara Jo White,et al.  COLLABORATION USING CLOUD COMPUTING AND TRADITIONAL SYSTEMS , 2009 .

[23]  M. Sandelowski Qualitative analysis: what it is and how to begin. , 1995, Research in nursing & health.

[24]  Tung-Ching Lin,et al.  Understanding knowledge management system usage antecedents: An integration of social cognitive theory and task technology fit , 2008, Inf. Manag..

[25]  Maha Singh,et al.  Use of Cloud Computing in Academic Institutions , 2012 .

[26]  Alan R. Dennis,et al.  Understanding Fit and Appropriation Effects in Group Support Systems via Meta-Analysis , 2001, MIS Q..

[27]  Dongwon Lee,et al.  Assessing A New IT Service Model, Cloud Computing , 2011, PACIS.

[28]  N. Howe,et al.  Millennials Rising: The Next Great Generation , 2000 .

[29]  Rajkumar Buyya,et al.  Market-Oriented Cloud Computing: Vision, Hype, and Reality for Delivering IT Services as Computing Utilities , 2008, 2008 10th IEEE International Conference on High Performance Computing and Communications.

[30]  Tom Page,et al.  Using Virtual Reality for Developing Design Communication , 2010 .

[31]  David W. Chadwick,et al.  A privacy preserving authorisation system for the cloud , 2012, J. Comput. Syst. Sci..

[32]  Germanas Budnikas,et al.  Application of cloud computing at KTU: MS live@edu case , 2011, Informatics Educ..

[33]  W. Orlikowski Using Technology and Constituting Structures: A Practice Lens for Studying Technology in Organizations , 2000 .