Massive open online courses and completion rates: does academic readiness and its factors influence completion rates in MOOCs? - Newton, Rochelle (East Carolina University, 2016)
With the increase in the cost of an education and the flat employment rate, many institutions and students are looking to online learning to solve this academic dilemma. Online education is thought to be a low-cost academic alternative to brick and mortar courses. Massive Open Online Courses (MOOCs) goals include issues of equity in higher education, the rising costs of a college education, and funding concerns. MOOCs can be taken from anywhere as long as the participant has a computer and access to the Internet is available. Also, traditional MOOCs do not require any financial commitment and do not have academic prerequisites or an admissions process. Completion rates among learners taking MOOCs are low, begging the question of whether they actually address matters of escalating college costs and higher education equity. The purpose of this study is to explore whether academic readiness in the context of the likelihood the learner completing the course. This study focuses on one component of the many factors in MOOCs - the likelihood of course completion and academic readiness. Academic readiness in MOOCs is not a requirement, but a component that may determine whether a learner has the tools needed to complete a MOOC. Academic readiness suggests a level of knowledge and cognitive abilities necessary to understand the course content and to navigate the course technologically. Theories addressing structural elements within MOOCs include Clow's funnel of participation, behaviorism, and constructivism. Of these theories, constructivism provides the theoretical framework for understanding learners' abilities and willingness to learn in the study. This quantitative study attempts to evaluate the likelihood of course completion and the factors that may influence these outcomes using secondary data from Duke's MOOC pre- and post-course surveys. Logistic regression analysis with the dependent variable (a learner completes a Duke's MOOCs) and the independent variables (academic readiness and its factors -- college degree; age; race; gender; previous experience with course subject, course level -- beginner, intermediate; or advanced; and STEM or non-STEM) will be used to estimate the likelihood that these variables will encourage learners to complete MOOCs or understand why learners do not.
Keywords: academic factors; MOOCs (Web-based instruction); Students--Attitudes; Web-based instruction