The Electronic Journal of e-Learning provides perspectives on topics relevant to the study, implementation and management of e-Learning initiatives
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Journal Issue
Volume 15 Issue 1 / Apr 2017  pp1‑103

Editor: Robert Ramberg

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Editorial for EJEL Volume 15 Issue 1  pp1‑2

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Motivational Gaps and Perceptual Bias of Initial Motivation Additional Indicators of Quality for e‑Learning Courses  pp3‑16

Rosário Cação

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We describe a study on the motivation of trainees in e‑learning‑based professional training and on the effect of their motivation upon the perceptions they build about the quality of the courses. We propose the concepts of perceived motivational gap and real motivational gap as indicators of e‑learning quality, which reflect changes in both perceived and real students' motivation. These indicators help evaluate the changes in the trainees' motivation, as well as the bias that occurs in the perceptions about initial motivation. In the sample analyzed, the real motivational gap was more negative when the perceived motivational gap was negative and not so positive when the perceived motivational gap was positive. We found that there is a perceptual bias on initial motivation when the perceived motivational gap is not null. This means that, for the sample analyzed, the trainees may have “adjusted” their perception regarding the initial motivation as a function of their final motivation, bringing it closer to the latter and supporting their final status. We also show that these gaps help explain how the trainees' perception of quality is affected: the gaps were minimized at higher levels of perceptions of quality and when they were positive, the perception of quality was higher than average. The two proposed conceptual gaps are useful to measure quality in e‑learning and implement specific actions to improve it. The results of our study are useful as they create insights on perceptions of quality in an indirect way, i.e., without asking the trainees to think about what they believe quality is, so that they can quantify it. They also enable training companies to create additional and complementary indicators of quality of e‑learning courses that can help explain changes in perceptions of quality. 


Keywords: attitudes, courses, expectations, e-learning, gaps, motivational gap, motivation, motivation to learn, perception bias, quality, quality indicators, quality of e-learning, satisfaction, service, training management, training motivation


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