Framework for improving the effectiveness of e-learning content

Abstract

E-learning has become popular in the recent past because of its potential for providing more flexible access to content and instruction at any time, from any place. But at the same time, there are a lot of issues with its acceptance as a replacement for traditional methods of learning as well as course completion rates. This failure could be attributed to multiple reasons, but a major chunk would be related to differences in individual learning preferences. Literature review An elaborate literature review was done to understand the individual differences in terms of cognitive aspects and styles of learning. The Need for Cognition, which is a cognitive aspect typically associated with the global orientation of an individual s ability to process information was identified to be studied in detail. Objective The primary objective of the study was to identify the relationship between NFC and the cognitive styles of an individual, specifically on the Visualizer-Verbalizer and Who list-Analytic dimensions. A set of 10 hypotheses was established that proposed possible relationships between the NFC and cognitive styles, as well as the effect of other factors such as Prior Knowledge, Extrinsic reward, Perceived Utility and Source Credibility on NFC and learning preferences. Method A survey was designed to measure the various factors using questionnaires based on Need for Cognition Scale for NFC, Individual Learner style for Verbalizer-Visualizer and Who list-Analyst, and a custom set of questions for the effect of other identified factors on NFC and learning preferences. A total of 84 complete responses were chosen for further analysis. Regression Analysis was used to check the correlations between NFC and the cognitive styles / other factors to check the validity of the hypotheses .Results The regression analysis provided results that were corroborating 7 of the proposed hypotheses, showing a contradictory result for 2 hypotheses related to cognitive style orientations, and negating one hypothesis. Conclusion Specific relationship between NFC and cognitive styles was established. High NFC individuals showed an inclination towards Who list and Visual styles, while low NFC individuals showed an inclination towards Analytic and Verbal styles. Extrinsic rewards or Perceived Utility made the low NFC individuals more receptive to a course, while Source credibility and Quality of Information made both low as well as high NFC individuals equally receptive to the course. Lack of an immediate reward or utility for mandatory course brought down the course enjoyment levels of both low and high NFC individuals. Effects of Prior knowledge was also found to raise the receptivity levels of individuals when the information was congruent, while high NFC individuals were found to take more time to adapt to incongruent information. By understanding the NFC characteristic of an individual, and using the associations and effects of other factors in the proposed framework, individual differences could be addressed to make e-learning more effective.