Distance Education Nursing Students Satisfaction with e-Learning Resources

Published: 8 January 2019| Version 1 | DOI: 10.17632/5d9b7b7ckv.1
Contributors:
Gladys Dzansi,
Joseph Shahadu Issifu,
Yaw Oheneba-Sakyi,
Eric Tornu

Description

A questionnaire developed by Sun et al. (2008) on the dimensions and antecedents of perceived e-Learning satisfaction conceptual model was used to collect data. The questionnaire consisted of 13 variables including learner attitude towards computer, learner computer anxiety, learner internet self-efficacy, instructor response timeliness, instructor attitude towards e-Learning, e-Learning course flexibility, e-Learning course quality, technology quality, internet quality, perceived usefulness, perceived ease of use, diversity in assessment and learner perceived interaction (Jami Pour et al., 2017) with others and 73 items.

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An electronic questionnaire was designed using google forms. A week after the announcement, a link to the questionnaire was sent to 215 randomly selected respondents via email for a pre-test. Based on the pre-test results, the questionnaire was further refined. Data obtained were exported from the online Excel spreadsheet to Statistical Package of Social Sciences (SPSS) version 24. The data were carefully examined for errors. All statistical tests were non- directional (two- tail) at 0.05 level of significance (95% confidence level). Categorical variables (sex, religion, marital status, employment status, occupation, computer skills, e-Learning centre, level in e-Learning course, computer ownership and device used to access e-Learning) were analysed using Mann-Whitney U test and Kruskal-Wallis test to examine differences in the level of e-learning satisfaction between the groups. The variables (dependent and independent) under study are considered continuous variables by virtue of the 7 points Likert scale used. Thus, learner usage of Sakai LMS functionalities, instructor response timeliness, instructor attitude towards e-learning, e-learning course quality, e-learning course flexibility, technology quality, internet quality, perceived usefulness, perceived ease of use, diversity in assessment, learner perceived interaction with others as independent variable and e-learning satisfaction as the dependent variable. The distribution of data on the dependent variable was negatively skewed. Consequently Non -parametric tests were applied in the analysis of the data. Spearman rho was applied using Cohen (1988) criteria to examine the relationship between the independent variables and the dependent variable. Logistic regression analysis was applied to examine how well the variables predict learner satisfaction.