Investigating the usage of E-learning: An Integrated model of TAM and IS Success

Electronic learning (e-learning) is the new form of learning which is established with Internet and its services. Instructive institutes address the new and modern learning requirements by adopting new developments in the field. In this paper author has presented the integrated hypothesized model for e-learning success among undergraduate students in the contexts of Pakistan. The integrated model is based on Technology acceptance model (TAM) and Delone and Mclean information success (D&M IS) model to examine the effect of quality features, perceived ease of use and perceived usefulness on user’s intentions and satisfaction towards the usage of e-learning.

[1]  Fred D. Davis,et al.  A critical assessment of potential measurement biases in the technology acceptance model: three experiments , 1996, Int. J. Hum. Comput. Stud..

[2]  B. Bai,et al.  The impact of website quality on customer satisfaction and purchase intentions : evidence from Chinese online visitors , 2008 .

[3]  Duryana Mohamed.  Investigating cybercrimes under the Malaysian cyberlaws and the criminal procedure code: issues and challenges , 2012 .

[4]  Iuliana Dorobat.  Models for Measuring E-Learning Success in Universities: A Literature Review , 2014 .

[5]  Eric T. G. Wang,et al.  Understanding Web-based learning continuance intention: The role of subjective task value , 2008, Inf. Manag..

[6]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[7]  Khaled A. Alshare,et al.  IS Success Model in E-Learning Context Based on Students' Perceptions , 2010, J. Inf. Syst. Educ..

[8]  Clyde W. Holsapple,et al.  Defining, Assessing, and Promoting E‐Learning Success: An Information Systems Perspective* , 2006 .

[9]  Tiago Oliveira,et al.  Understanding the impact of m-banking on individual performance: DeLone & McLean and TTF perspective , 2016, Comput. Hum. Behav..

[10]  Ya-Ching Lee,et al.  An empirical investigation into factors influencing the adoption of an e-learning system , 2006, Online Inf. Rev..

[11]  L. Cronbach.  Coefficient alpha and the internal structure of tests , 1951 .

[12]  Hsiu-Li Liao,et al.  Impact of media richness and flow on e-learning technology acceptance , 2009, Comput. Educ..

[13]  Chorng-Shyong Ong,et al.  Factors affecting engineers' acceptance of asynchronous e-learning systems in high-tech companies , 2004, Inf. Manag..

[14]  Ming-Chi Lee,et al.  Explaining and predicting users' continuance intention toward e-learning: An extension of the expectation-confirmation model , 2010, Comput. Educ..

[15]  Konstantinos Theodoridis,et al.  Satisfaction determinants in the Greek online shopping context , 2010, Inf. Technol. People.

[16]  Maarten Gelderman,et al.  The relation between user satisfaction, usage of information systems and performance , 1998, Inf. Manag..

[17]  Kai Pata,et al.  Modeling Spaces for self-directed Learning at University Courses , 2009, J. Educ. Technol. Soc..

[18]  Yi-Ting Chen,et al.  Cooperative learning in E-learning: A peer assessment of student-centered using consistent fuzzy preference , 2009, Expert Syst. Appl..

[19]  Hangjung Zo,et al.  Critical success factors for e-learning in developing countries: A comparative analysis between ICT experts and faculty , 2012, Comput. Educ..

[20]  Jeffrey Soar,et al.  A model to measure e-learning systems success , 2012 .