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Identifying factors that predict student success in a community college online distance learning course.

Description: 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 ...
Date: December 2007
Creator: Welsh, Johnelle Bryson

Improving learner reaction, learning score, and knowledge retention through the chunking process in corporate training.

Description: The purpose of the study was to investigate the application of the chunking process to the design and delivery of workforce training. Students in a 1-hour course (N = 110) were measured on learner reaction, learning score achievement, and knowledge retention to see whether or not chunking training in a 1-hour session into three 20-minute sessions to match adult attention span resulted in a statistically significant difference from training for 1-hour without chunking. The study utilized a repeated measures design, in which the same individuals in both the control group and experimental group took a reaction survey instrument, a posttest after the training, and again 30 days later. Independent samples t tests were used to compare the mean performance scores of the treatment group versus the control group for both sessions. Cohen's d was also computed to determine effect size. All hypotheses found a statistically significant difference between the experimental and control group.
Date: December 2007
Creator: Murphy, Maureen

Influence of pre and post testing on return on investment calculations in training and development.

Description: When expenses become an issue, training is often one of the first budget items to be cut. There have been a number of evaluation studies about rates of return from training interventions. Most results are based on interviewing participants about the value of the intervention and its effect on their productivity. This often results in quadruple digit return on investment indications. Decision makers who control the budget often view these kinds of results with skepticism. This study proposes a methodology to evaluate training interventions without asking participants their opinions. The process involves measuring learning through a series of pre-tests and post-tests and determining if scores on pre-tests can be used as predictors of future return on investment results. The study evaluates a series of return on investment scores using analysis of variance to determine the relationship between pre-tests and final return on investment results for each participant. Data is also collected and evaluated to determine if the financial results of the organization during the period of the training intervention could be correlated to the results of the training intervention. The results of the study suggest that the proposed methodology can be used to predict future return on investment from training interventions based on the use of pre-tests. These rates of return can be used as a method of selecting between competing training intervention proposals. It is a process that is easily understood by the key decision makers who control the allocation of financial resources. More importantly, it is a process that can maximize the value of each dollar spent on training.
Date: May 2008
Creator: Hiraoka, Calvin H.