Which students succeed at online learning

Johnelle Bryson Welsh's dissertation "Identifying Factors That Predict Student Success in a Community College Online Distance Learning Course" (2007) while researching US colleges, provides useful insights into students of e-learning courses generally. Demographic variables (such as age and gender) do not effect course results. The online students tend to older, married, worked full-time, and supported others. Successful students had better computer skills. Literacy was an issue for many students. One odd result was that students enrolled in only one course did worse than those undertaking two or more courses.

The study's purpose was to identify demographics, educational background, finances, formal and informal education and experiences, reading habits, external environmental factors, psychological factors, and computer efficacy factors that predict a student's ability to successful complete an online (Web-based) distance learning community college course. Major student retention theories and student attrition and persistence research guided the study. Distance learners (N = 926) completed four surveys, which collected data for 26 predictor variables that included age, gender, marital status, ethnicity, support others, course load, first-time student, last semester attended, student type and location, financial stability, tuition payment, prior learning experiences, reading habits, family support, enrollment encouragement, study encouragement, time management, study environment, employment, extrinsic and intrinsic motivation, locus of control, self-efficacy, computer confidence and skills, and number of prior online courses. Successful or unsuccessful course completion was the dependent variable. Statistical analyses included Cronbach's alpha, Pearson chi-square, two-sample t test, Pearson correlation, phi coefficient, and binary logistic regression. Variables in each factor were entered sequentially in a block using separate binary logistic regression models. Statistically significant variables were course load, financial stability, prior learning experiences, time management and study environment, extrinsic motivation, self-efficacy, and computer skills. Selected predictor variables (N = 20) were entered hierarchically in a logistic regression model of which course load, financial stability, and self-efficacy were statistically significant in the final block. Correlation coefficients were computed for statistically significant predictor variables to determine whether the significance was confined to the control group or an overall level of significance. Findings were supported through cross-validation and forward stepwise entry of variables in logistic regression. Despite having two or more at-risk factors, distance learners who had high levels of self-efficacy, good computer and time management skills, financial stability, a favorable study environment, were enrolled in more than one course, and believed their prior learning experiences helped prepared them for their course were more likely to be successful.