An Analysis of Factors that May Influence Student Satisfaction in Computer Programming Courses at an Online Midwestern University
Type of DegreePhD Dissertation
Education Foundation, Leadership, and Technology
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The rise in demand for computer programming jobs has created a significant need for computer programming training. Online learning can be an effective tool for meeting the needs of these job demands. The challenge for universities is that computer programming is perceived as a difficult course by many students (Askar & Davenport, 2009; Baser, 2013) and online course satisfaction is generally low (Maki et al., 2000). This study investigated the influence of instructor interaction, content interaction, interface interaction, and other factors to determine their effects on student satisfaction in online computer programming courses. A quantitative research design was used to address eight research questions. Participants were undergraduate students enrolled in an introductory Python computer programming essentials course at a small Midwestern university. An End of Course (EOC) student satisfaction survey was used to examine the relationship between student satisfaction and the predictor variables. Survey data was analyzed through Spearman’s correlation, Chi-Square Test of Independence, and binary logistic regression analysis. Results show that content interaction, interface interaction, and different instructor interactions are related to overall student satisfaction; however, no evidence was found to suggest that instructors responding to emails and/or phone calls within 48 hours is related to overall student satisfaction. Moreover, Chi-Square Tests revealed that there was a statistically significant difference between student satisfaction, interface interaction, and instructor interactions where instructors treated students with respect and professionalism based on gender. There were no statistically significant differences in student satisfaction, interface interaction, content interaction, or different instructor interactions based on race and age. Additionally, none of the interaction variables were significant predictors of student satisfaction. These findings suggest that more research is needed to determine the factors that may predict student satisfaction in online computer programming courses.