Does quality matter? Measuring whether online course quality standards are predictive of student satisfaction in higher education

There is little formal research on the effectiveness and relevancy of quality standards in higher education. This dissertation study attempted to respond to the call for appropriate standards in higher education through formal research to examine the effect of quality in higher education online courses on student satisfaction. The research questions for the study were: (a) What instructional design standards are appropriate for measuring online course quality? and (b) To what extent are instructional design quality standards in online courses predictive of student satisfaction with the online learning experience?;The first step of the research process was a synthesis of existing models for course quality. An evaluation of the models in the literature revealed a gap between existing quality indicators and instructional design principles related to instructional strategies and assessment practices. To respond to this gap, the researcher developed a 109 criteria Taxonomy for Online Course Quality through an iterative Delphi process using national experts in online education. The taxonomy served as the assessment instrument for measuring the independent variable, course quality, using a dichotomous scale for 12 online courses, resulting in a score for each course in 18 quality constructs. End-of-course survey items were used to measure the dependent variable, student satisfaction, through a score for overall course quality and a composite score representing seven items addressing the course experience. The Mann-Whitney non-parametric test was used to test for differences in satisfaction for the two groups: courses that adhered to or failed to adhere to a quality standard. The Instructional Strategies standard for online course quality was the only one of 18 independent variables that was found to be statistically significant with a probability score of .033 in overall quality satisfaction using a baseline of .05 for probability (P).;The quality taxonomy introduced in this research extends existing models in the industry to include instructional design principles not addressed in the literature. In addition, the research also provides evidence that instructional strategies are predictive of student satisfaction in online courses. The results of the dissertation research may help convince institutions to prioritize the introduction and advancement of instructional strategies as an approach to creating better learning experiences. Further, the study offers a comprehensive taxonomy of validated standards for evaluating online course quality.