One challenge for those who are considering bringing adaptive learning into their higher education programs is knowing what, exactly, other professionals and companies using the same terminology are referring to.
This spring, the personalized learning “terminology wars” have been addressed extensively by both Michael Feldstein and Phil Hill, publishers of the influential e-Literate blog. They are attempting to provide their own definition of personalized learning as a practice.
The crux of the problem is this: the terms “personalized learning” and “adaptive learning” are often used interchangeably, but no common definitions exist for either, and both terms mean different things to different people.
This is an issue instructional designer and teacher Niki Bray has been giving a lot of thought to in her role as the adaptive learning fellow for WCET (the Western Interstate Commission for Higher Education’s Cooperative for Educational Technologies), a non-profit advocacy group for technology-enhanced higher education. Her work has involved both researching adaptive learning and educating the WCET community about its benefits, current research, implementation, and adaptive learning technologies. And, as she says in the interview below(which has been condensed and edited for clarity), “there’s still no consensus in the field.”
Bray is also an instructor and instructional designer with the University of Memphis School of Health Sciences, where she is working on her doctorate in Instructional Design & Technology. Bray has coached and taught at every education level and says her work as a secondary teacher made her passionate about personalizing learning in the classroom. As an instructional designer and scholar, she has seen how technology allows instructors to take that personalization to the next level.
What have you learned about adaptive learning during your fellowship?
Some people have a belief that adaptive learning has been taking place forever. I don’t believe adaptive learning has taken place forever. You have to have the algorithms for a system to truly be adaptive — to personalize at any moment in time, continuously learning about the learner and making changes to any of the content, the sequence, or the assessment that best suits that learner at that particular time, which can be different at another time.
I don’t think that can be done without the use of big data and learning machines. You must have the ability to know exactly what each learner knows at any given moment in time.
That’s probably the biggest thing I’ve learned about adaptive learning. You can personalize learning and differentiate learning. Adaptive does all of that, but to be truly adaptive, you have to have a system that helps you to collect all these hundreds of points of data on each and every learner.
How close are we to standardizing that terminology?
Some of the most respected people I know still call adaptive learning “personalized.” It makes our current state of knowledge very difficult, because two people can call the same thing something totally different, but it means the same thing. That’s really confusing to anybody who is new to adaptive learning and wants to know more.
At the Santa Fe Adaptive Learning Conference that WCET hosted last June, some of the most brilliant minds in our field were on a panel together. Literally every single one of them was asked what they would call it, and there was no consensus. They still do not agree on that terminology. I think as we continue to work to standardize that will help the terminology to become clearer.
What do you believe the difference is?
My personal opinion is that you cannot do adaptive learning without technology. You can do personalized learning without technology, if that makes sense.
If I have a class of students sitting in front of me today, I can personalize that experience by using what I know about my students. For example, I teach a sports psychology class. Let’s say that I know these six students played high school soccer and these three students were on the high school football team. As I go through my class and I’m able to determine what their experience has been, I can personalize one particular assignment by putting it in the context of the sport in which they have experience. I can then differentiate that based upon their needs. What if I have a student in a group who has poor writing skills? Then maybe I offer that student the opportunity to demonstrate their learning in a way other than writing.
I spent 18 years in the secondary classroom. There is no way that I was able to totally adapt what I was doing every single day for any single student in the classroom the way adaptive learning with the use of algorithms is capable of. I could differentiate the experience. I could personalize that experience, but I couldn’t adapt it. Adaptive is real time. It’s the media. It’s highly personalized based upon your needs and your interests.
Do you think the lack of clarity in the terminology is hampering work in the adaptive learning field?
I wouldn’t say so. Those professors who are interested in student learning — who are student-centered, who care about students, who want to see students grow and learn and be prepared for life after college — are actively seeking ways in which they can improve their courses. They don’t care what it’s called. They just want to help.
A.J. O’Connell is a freelance journalist specializing in education reporting and a former college journalism teacher.