Knowledge Management & E-Learning: An International Journal (KM&EL), Vol 4, No 4 (2012)

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e-Learning quality: Scale development and validation in Indian context

Arun Kumar Agariya, Deepali Singh

Abstract


The aim of this paper is to develop a reliable and valid e-learning quality measurement scales from the learner as well as faculty perspectives in Indian context. Exploratory factor analysis followed by confirmatory factor analysis was done which is presented in two forms; covariance model and the structural model. The covariance model shows that the factors namely collaboration, industry acceptance and value addition are important from the learner’s point of view whereas the factors namely transparency in assessment, technical know-how and engagement (from students) are important from faculty point of view. Factors namely course content and design structures (technology/website design) are found equally important for learner’s as well as faculty’s perspective. The structural models validate the previously extracted factors along with their indicators. The findings of this study validate the long held belief that e-learning quality is a multidimensional construct and serves as a critical success factor. The proposed scale will help in identifying issues that contribute towards e-learning quality in Indian context and thereby formulating strategies accordingly, resulting in efficient (in terms of cost) and effective (outcomes) e-learning practices, which is the necessity of the hour for the economic development of the country. A fair amount of literature on e-learning dealt with identifying factors explaining the constructs of quality, perceived value and satisfaction. But there is paucity of research pertaining to e-learning quality scale development and validation from the learner as well as faculty perspective. This study is an attempt to bridge this gap in the existing literature.


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Knowledge Management & E-Learning: An International Journal (KM&EL)
ISSN 2073-7904

 

Maintained and Developed by:

Laboratory for Knowledge Management & E-Learning

Faculty of Education, The University of Hong Kong