Here are some early attempts at adaptive learning. These are a starting point—each reflects the potential of this model. Although we are just getting started, adaptive learning may well be one of the defining movements of education technology for the next several years. From what I can tell, it seems that adaptive learning usually refers to a platform or learning environment. A recent article in The Journal concluded that we aren’t quite to the level of completely adaptive learning—but some platforms are moving closer.
There are two other models related to adaptive learning. They are differentiated and personalized learning, which also include student-centered content, but do not necessarily require data or technology. Both have been practiced for decades. However, it is worth noting that the difference between the three can often be non-existent or a matter of semantics. The models do share a certain amount of overlap.
Adaptive learning seems to still be in its early stages of development. Ultimately, the hope seems to be the use technology to make more efficient use of time and resources in education contexts. Tools are just now starting to move beyond a simple two-way system. Some tools already provide instant feedback to students. This is an early form of adaptive learning.
However, such feedback could be far more personalized. As time goes on, adaptive learning will begin to consider factors and patterns other than just right and wrong answers. Tools will identify not just the topics a student struggled with, but also which particular step confounds the student. A new understanding will emerge, representing student learning as a more continuous and gradual process. Progress will become less “yes-or-no” and less “black-and-white.”
The promise of adaptive learning is exciting, but it can’t—and won’t—be realized immediately. This process has only just begun. The value of adaptive learning might be in the discovery of new pathways and combinations for students. These new discoveries emerge from data which instructors cannot process in the way technology can. However, data cannot be collected for every student attribute. Any success with adaptive learning will require an instructor who understands the limitations of such tools and that a learner is more than just a data profile.
These are just a few observations—I want to know what others have learned about the state of adaptive learning. Add your experiences (or predictions!) in the comments or connect with me @cantrell_cj!
Catelyn Cantrell is a soon-to-be graduate from the University of Florida and a member of the Omninox Publishing team in Gainesville, Florida, a developer of interactive guides for Advanced Placement® Courses. She is starting a master’s degree in English Education and taking steps towards a teaching career.