For hundreds of years, learning has been tied to a specific person (the instructor), at a certain place (the classroom), and at a certain time (class time); but media-based advances such as interactivity, mobility, and asynchronous delivery have finally broken through the teacher-centric barrier and given learners a little more flexibility.
While this is an incredible step forward, students are still restricted to a certain path and, more often than not, limited to specific content. But this is changing quickly and dramatically with a technology that is just now finding its way into the mainstream: adaptive learning.
The advent of adaptive learning makes the present day an exciting time to be involved in the learning profession. Here is how adaptive learning makes a difference: We know that we do not all learn at the same pace, and we know that the same content does not make the light bulb of understanding come on for each of us. It is also often true that two learners can have a completely different understanding of foundational knowledge. Forcing two different learners to go through the same material with the same time restrictions is not only inefficient but also contrary to what we know about the learning process.
Adaptive learning assesses a learner’s knowledge and then develops a path of learning that is tailored to meet that individual’s needs. But a good system does not stop there—it can continue to assess learners’ needs as they advance through the content, and it can adjust and modify the learning path in real time.
A simple example of this is a course that teaches someone how to use a yardstick. Using a yardstick requires an understanding of fractions. The adaptive learning system is able to tell that learner A already understands fractions and does not try to force that learner to sit through hours of unneeded content. In the case of learner B, the adaptive learning system supplies the content on fractions until it determines that the learner understands it. At that point, the learning path changes to accommodate what the student now knows.
In essence, adaptive learning might be more aptly called personalized adaptive instruction.
The other incredible advantage adaptive learning systems give us is the ability to accurately assess learning—both for the individual and across the spectrum of all learners engaged with it. For professionals working to produce the best learning experiences, that kind of data can tell us what works, what doesn’t work, where learners might struggle, and how to make the best improvements.
If Adaptive Learning Is So Great, Why Isn’t It Everywhere?
Actually, adaptive learning has been around for some time. Depending on which article you read, the origins of computerized adaptive learning may be traced to the 1970s or even as early as B.F. Skinner’s work in the 1950s. Although it has been around, and a great deal of positive words have been written about it, adaptive learning has not yet gained a tremendous amount of popularity. This is mostly due to that fact that up until recently, it has been expensive and surrounded by mystery, which has caused a bit of a public relations problem.
One of the larger challenges to wider adoption is cost. In the past, the systems and their development have been relatively expensive. To be truly adaptive, a computerized system needs an artificial intelligence (AI) that is capable of assessing the needs of the learner. This requires a healthy amount of processing power and sophisticated programming. What made earlier adaptive learning systems even more expensive was the systems themselves required trained technicians and developers to add content and assessments. There really were no “do-it-yourself” adaptive systems that didn’t require a small army of professionals just to produce a single course.
Another barrier is simply the mystique associated with artificial intelligence. Adaptive learning’s use of AI has caused it to be viewed as an incomprehensible “black box” that is more under the purview of technology gurus than the learning professionals and educators who are able to really put this phenomenal tool to good use. Many have assumed that adaptive systems require significant programming skills and a deep understanding of complex algorithms. Because of this, the people who could really do the most with adaptive learning technology looked elsewhere for learning innovation. This mystery has been only increased by developers who try to protect their hard work by keeping systems a trade secret, or by companies that attach the name of “adaptive learning” to technology that does not quite fit the bill.
Fortunately, both of these roadblocks are quickly disappearing. Processing power and inexpensive AI are becoming more readily available, and more adaptive learning platforms are coming with authoring systems that allow learning professionals themselves to construct the adaptive courses. This makes the best systems more affordable and puts the power in the hands of those who can use them with the greatest impact.
The next step is for educators and learning professionals to take the mystery out of adaptive learning so that we can all put it to good use. Enter ATD Essentials of Designing for Adaptive Learning. Participants will learn how to build learning paths that facilitate the best that learning technology has to offer.