Adaptive learning is an intriguing idea. It is easy to see how the idea of utilizing technology to create a personalized learning process for students that adapts to the needs of the learner is a compelling one for educational institutions and students alike. After all, finding a way to reach and engage more students in a sustainable way is game changing.
92% of chief academic officers agree that adaptive learning technology could potentially improve student learning outcomes, according to a recent survey conducted by the Association of Chief Academic Officers. In fact, 87% would like to see their faculty make greater use of this technology in entry-level courses. However, despite this faith in technology, IT resources and investments are an area of concern.
Another area of potential concern is in how the courseware works. Often the algorithms and methodology behind them isn’t shared with the school or faculty using the courseware. With the movement in education toward more data-driven methods of teaching and learning, it is important to understand not only how they work, but also what happens with the information gathered about the students who use the adaptive courseware.
Candace Thille, who recently made headlines when it was announced she was taking a leave of absence from Stanford to work with Amazon as the director of learning science and engineering, sat down with EdSurge last year to discuss the future of education and this issue was a topic of discussion.
As the founding director of Carnegie Mellon University’s Online Learning Initiative (OLI) and an assistant professor of education at Stanford University’s Graduate School of Education, she has become an influential voice in higher education. During the interview she was asked about colleges losing an aspect of control over the teaching process with adaptive learning. She explained what she sees as a potential concern.
“I think we have, in higher education, gotten into a pattern of outsourcing material development Like textbooks—that's a classic example. And people are perfectly fine developing their courses, buying large textbooks, or asking your students to buy large textbooks, and then just selecting stuff out of that that they're going to use as the foundational material to teach from.
So at that point, when you're using textbooks in that way, the pedagogical decision making is still being made by the institution or by the faculty member. The challenge with these new environments is that they are, in essence, making pedagogical decisions. So if you design an environment to support a learner to achieve some outcome, and then you're collecting the way the student is interacting with that asset, collecting that data, and then hopefully doing something more sophisticated than just, "Did they get it right or wrong?" but actually modeling it in an appropriate way to make a fairly accurate prediction about the learner's knowledge state, then you can do one of two things with that piece of information if you're the system developer.
You can take it and feed it back into the system so that the system can start making autonomous decisions about what's best for the learner next. Or, you can do what we were doing at OLI, which was take that information, model it, and then present it to the faculty member who's teaching the course so they can get insight into their learners or their class's knowledge state, and then use that to make a pedagogical decision.”
Ultimately, adaptive learning has amazing potential to strengthen teaching and learning outcomes, but schools also need transparency so they can continue to grow and adapt with the changing educational landscape.