Learning to Adapt: A Case for Accelerating Adaptive Learning in Higher Education, published by Education Growth Advisors, makes the case for learning software that automatically adjusts to student levels.
The paper opens with three scenarios that illustrate the potential:
- Lab simulations: When Cathy performed a procedure incorrectly, however, the virtual lab would not allow her to proceed until the error had been corrected. To that end, she received an onscreen message drawing her attention to the error and inviting her to repeat the earlier steps in the procedure to achieve a different result.
- Language app: The app, already knowing how far through the course material he has progressed, as well as his areas of strength and weakness in the material covered so far, draws on the data gathered during his previous sessions and the time parameters James has established to generate a new assignment that will focus his attention on those areas he has yet to master.
- Math lab: Each of three groups is assigned a different set of problems to tackle, based upon their current levels of competence. They get to work, talking with one another about the problems they had encountered in the online curriculum earlier in the week.
The paper concludes, “adaptive learning promises to make a significant contribution to improving retention, measuring student learning, aiding the achievement of better outcomes, and improving pedagogy.
With growing pressure to improve value, adaptive learning has the potential to break the higher education “Iron Triangle” of cost, access, and quality. Historically, institutions have been able to optimize only one or two variables–adaptive learning can drive improvement in all three.
Like the Knewton-ASU developmental math partnership, the paper suggests, “Adaptivity is different from personalization in that it takes a more sophisticated, data-driven, and, in some cases, non-linear approach to remediation.” The paper notes other platform providers include aNewSpring, Cerego, CogBooks, LoudCloud, and Smart Sparrow. (See the magic table on page 9 that summarizes the paper.)
“Adaptive learning brings with it great promise, but must be accompanied by significant culture and business process change.” It is typically introduced with small scale pilots today but will increasingly become mobile and untethered. However, “Big data and business analytics have the potential to improve the educational experience for students and faculty alike. However, this opportunity to “automate” components of the learning experience should converge with, rather than supplant, the human role in education.”
Combining adaptive and face-to-face instruction is gaining widespread adoption in elementary education where there are widely used products including Dreambox (K-5 math) and i-Ready from Curriculum Associates (K-12 assessment, K-8 reading and math) and Compass Odyssey (K-12 reading and math).
For more on adaptive learning in K-12, see:
- Premium Content is Dead, Long Live Premium Content
- DreamBox Learning: Intelligently Adaptive, Engaging & Motivating Math
- Top 10 Questions to Ask Common Core Vendors
- i-Ready is Ready for Prime Time
Compass Learning, Curriculum Associates, and Pearson are Getting Smart Advocacy Partners.