3 Reasons to Try Adaptive Learning Courseware [video]

Karen Vignare, executive director, Personalized Learning Consortium, Association of Public and Land Grant Universities

Dale Johnson, director of adaptive learning initiatives, Arizona State University

Patricia O'Sullivan, manager, Personalized Learning & Adaptive Teaching Opportunities Program, University of Mississippi

1. Retention

Karen Vignare: For most institutions, we're still struggling with how we improve first year retention, especially for students who are often are least well served that usually low income and students of color. And we're looking at ways that we can actually improve the teaching and learning process both for them. So those courses have been stubborn about seeing improvements and that's where we really think the power in adaptive courseware lies right now. We do see a future that will include and you already have organizations thinking about doing adaptive across the program. So that students might get through a program faster or get deeper into their learning. But we're really focused on that introductory course level so that we can see first year retention go up.

2. Continuous Feedback Through Data & Analytics

Dale Johnson: One of the frustrations we've had over the years is this idea that the course is a black box, and you don't really know whether the students are learning the material until after the first exam or after the end of the course. And what we're trying to do is accelerate the learning process. So the ability to get insight into what the students know and don't know early in the class is really valuable.

Patricia O'Sullivan: The data that universities can get from adaptive learning platforms can help them in so many ways. So at the institutional level, it can help them track student progress if they're in one platform, it's easier, but they can have multiple platforms speaking to each other. But they can get that data across the institution to check student progress and see how they're doing with these new learning initiatives. At the programmatic level, again, especially if students are on the same platform, departments can see programmatically where are the gaps, where are they losing students, where might they be retaining, what are they doing right, where are they retaining students. So that's really valuable information. Also for a accreditation purposes, that's very useful information. And then at the course level, it's really helpful for faculty. And I guess I'll segue into the third use of it is the tool to manage high enrollment classes. It's useful for faculty to see patterns in student learning behavior, but also use that data to do interventions with students who might be at risk. So rather than waiting for the first high stakes exam, which could be four, five weeks into the semester, they can check how students progressing in the course where one week, two weeks into the semester and do those interventions early when they really matter.

3. Section Variability

Karen Vignare: The other thing that's critical in our mind is section variability. A lot of community colleges, even smaller colleges will have multiple faculty teaching a course. And if a student walks into course that they've been assigned to, not getting the choice of just picking their professor, and one course has a pass rate of 80% and another one has a pass rate of 50%, how is that a good model for us? We've got to decrease section variability so what that means is the other support is really getting faculty to work together in these intro courses. And depending upon your institution, that may be actually be a easy lift, but too many of our institutions, people teach one section at a time and there's not a lot of collaboration. And that collaboration should extend, not just choosing a textbook or having learning outcomes that are similar. It should be about what are we gonna do in the classroom that is working for you so that we're sharing those best practices.