Web-based training has become a billion dollar industry in the United States. Electronically aided learning is viewed by many companies as a cost-effective way to deliver the up-to-date, up-gradable job-related training that the industry is demanding. This study sought to examine the relationship between learners’ satisfaction with online training as it relates to learner readiness, online features, and course relevance. The population for this study was adults seeking non-credit workforce training, specifically library professionals who were involved in web-based training through the Lifelong Education @ Desktop (LE@D) program at the University of North Texas, Denton. Online methods of training are used most extensively in the area of mandatory or compliance training, in which 35 % of training is conducted mostly or completely online. The total potential library population using LE@D product to date is approximately 4,000 unique enrollments nationwide. Participants were selected from a complete list of unique LE@D users over a 90-day period. A survey instrument was sent via e-mail to 514 enrollees who had completed a recent LE@D online training course. In total, 254 participants responded to the survey. Bivariate analysis of the variables using the Pearson product-moment correlation was used to determine the occurrence and strength of …

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) …