Improving Student Persistence and Completion Rates in Online Degree Programs:

Leveraging Insights for Impact

At Pearson we believe that making our efficacy and research work relevant to customers is just as important as ensuring that work is rigorous.

That means that we aim for our research inquiries and outputs to be relevant to the people who matter most – our customers and learners. This is certainly the case in higher education university-based customers come to us for support in managing the delivery of their online courses or degree programs, a largely operational task. What they learn is that a partnership with Pearson means a focus on learner outcomes, which is great for their students.

In a partnership with one such set of university customers, our efficacy and research team, in collaboration with program leadership, are engaged in a study to understand the impact of a student's progression through the required courses affected their academic performance, their persistence from one course to the next, and the overall retention in the degree program.

Evaluating the ‘Carousel Model’ of Online Course Delivery

Our university customers leverage the “carousel model” of online course delivery. The carousel curriculum model is an innovative course delivery system that provides structured course offerings and allows for learner flexibility. A ‘carousel’ defines a rotation of courses required for a program (e.g. MBA, Graduate Diploma, etc.) and specifies which course is offered during a specific teaching period. Depending upon when a student enrolls in the degree program, he/she may enter the carousel during any of the teaching periods (e.g. six to eight week period) throughout the course of the year, and then continue through the carousel as courses are offered. Because a student can begin at any point, there are no defined course progressions. Our goal is to understand whether there are any specific learning progressions (i.e. one course after another) that are more predictive of student success and completion rates, after holding other related variables constant.

Using historical student data obtained from the university online degree program, our team identified discrete sets of course progression combinations, and used available student characteristics to match the groups across progressions so that all students who followed the same (or similar) course progressions would be analyzed together, and all students in the sample will “look” like each other in terms of student characteristics.

From there, statistical models were built to determine which progressions are most predictive of learner outcomes, after holding other information constant. For example, to learn more about how course progression impacts persistence in the degree program, we isolate the progression model that most relates to persistence. We then drill down on these data to extrapolate the characteristics unique to this progression that might explain the higher rate of persistence. For example, were these curriculum designed in such a way that these courses build on one another, suggesting that the earlier courses were helpful to remain motivated? Alternatively, we can identify a progression that saw a high stop-out, or intermission rate. For example, if a high proportion of students stopped-out at course “B”, perhaps the curriculum in courses “F” and “D” are too rigorous for that early in the programme.

Moving from Insight to Impact

So what do we do with these kind of insights? How do they translate into improved learner outcomes? Working collaboratively with our university-based customers, we can leverage what we learn directly into program improvements that best support student success, persistence and completion of an online degree program. Sometimes this may mean that a university will alter course progression requirements, in another instance they may simply provide more robust information to advisors and students to inform their course enrollment and progression decisions.

At Pearson our commitment to efficacy and research is a true differentiator: rather than simply delivering on operational support, this engagement is leading to programmatic enhancements and improved student outcomes - a win for students and our higher education customers.