Congrats to the new Dr. Kashif Asdi, LT PhD grad!

Congrats to the new Dr. Kashif Asdi! Kashif’s dissertation title is “Learner Characteristics as Early Predictor of Persistence in Online Courses.” A description of his dissertation is below. Dr. Asdi has more than 20 years of experience in academic innovation, training and development, and performance-improvement. Previously, Kashif led teams of curriculum specialists and instructional designers to create competency-based, learning-centered curricula for fully online and hybrid programs for higher education institutions.
Kashif answering questions from the crowd after his presentation.
The purpose of this study was to examine how learner characteristics could be used to predict whether or not a college learner would persist in the first online course and, more importantly, enroll in the next two terms. The four learner characteristics examined were learners’ pre-course basic verbal score, college application score, degree level, and start date. The data were collected from 2,674 graduate learners who were enrolled in one of the online public service and health graduate programs at a large Midwestern university. A quantitative study was conducted to investigate the research questions. The chi-square test of association, a nonparametric statistical test, was used to determine if there were any significant differences between variables of the data. The following descriptive statistics were used to describe the data: frequency distributions, means, standard deviations, and percentages. Stepwise logistic regression was used to understand whether learner persistence can be predicted based on a learner’s pre-course basic verbal score, application score, degree level, and start date.
The tests results revealed a statistically significant difference between learners who completed their first course and learners who dropped out of their first course with respect to pre-course basic verbal, application score, and degree level. There was no statistically significant difference between the two groups with respect to start date. The logistic regression model was found to be statistically significant (p < .0005); however, the model explained only 1.7% of the variance in learner persistence; hence, this model needs to be used with caution. Of the four independent variables, only application score (p < .0005) added significantly to the model. This study supports the idea that learners who have higher application scores are more likely to complete the first course and enroll in the next two terms.
The findings of this study can contribute to the scholarly work in the field and potentially provide the base for future interventions to improve learner persistence in the first online course and enrollment in the next two terms.