Adaptive learning is in many regards the polar opposite of the MOOC because adaptive learning curriculum designers or platforms individualize the learning experience to reflect the learning gaps of the person taking an online course.
Where MOOCs make were developed to bring the standardized or one-size-fits-all course to the masses (millions of users can enroll in the same course), adaptive learning is built the promise of the opposite: One user can have a tailored, personalized learning experience that adapts to your ongoing needs based on data inputs and machine learning algorithms. In theory, one million learners could take the same course on Blockchain and one million different learning experiences would be generated.
In many of our conversations with teachers about the promise of adaptive learning we see that they fall within three camps:
1) You will get a skeptical look back, often combined with a warning about the magnitude of the manual work it takes to build an adaptive learning experience.
2) They point out that adaptive learning I just a fancy term of differentiation
3) They question the overemphasis on knowledge over skills in the construction of digital learning experiences.
All of the above are relevant reflections and all are true.
The trust is that, in its current form, adaptive learning is complicated, and requires a lot of extra work on the teacher or HR/learning professional who is implementing it.
In this unit we discuss adaptive learning, what it is, why it is (arguably) important, but also the still limited body of literature on adaptive learning. We’ve always known that people learn in different ways and to create successful learning experiences online we have to allow people to follow their passions for different content. But even more important than that, we also have to enable learners to complete different exercises so everyone can practice the skills and competencies that are important for their career path. But how does one enable that? Is it all about quizzes, baseline tests, and different learning paths, and what does each of these expressions mean?