One of the promises of digital learning and teaching is that it offers a personalized and individualized learning environment. It’s common these says to hear praise for ‘child-centered’ or ‘student-centered’ approaches to learning in contrast to the ‘adult-centered’, ‘teacher-centered’ practices now associated with chalk boards, No. 2 pencils, and classrooms of distracted, disengaged students.
How would classrooms change if technology could adapt to each student’s learning needs in real-time?
Adaptive learning technology has been around for a while now, but with major funding from Pearson — the largest education company in the world — small New York City startup Knewton plans to make big waves. Originally a test prep company, Knewton has now turned their focus to adaptive coursework.
With $54 million raised in investment capital, Knewton’s coursework software tracks which questions students answer right or wrong, how long they take to answer, whether they skip or revisit a question, and where their mouse travels on the screen — such as if movement follows the words as the student reads the question or hovers over a particular answer. The program guides students through the coursework in a manner tailored by their personal learning data.
“Different students can also be taught the same material in different ways, depending on their previous reactions.”
For example, a student who has demonstrated a preference for visual learning might be presented with a graph rather than an equation when being introduced to a new concept.
Internet companies have been using analytics to track consumer behavior for years — and with much success. The idea is to apply this type of thinking to digital learning and teaching.
Still, some have raised concerns. Richard Clark, a professor of educational psychology and technology at the University of Southern California, is concerned that Knewton has not disclosed the data they use to ground the individual adaptations.
“If they are doing solid work, why not publish or at least point to the peer-reviewed studies that are the basis for their approach?” he said.
“For Knewton,” says Ken Koedinger, a professor at Carnegie Mellon University and director of the Pittsburgh Science of Learning Center, “there’s a real danger of optimizing for the wrong thing.” For instance, if students’ lessons are optimized for quicker progress through the course, that might end up just yielding easier courses, not more learning.”
There remains a significant amount to discover for educators, researchers, and software engineers eager to unlock the details of what optimizes student learning and performance outcomes. Knewton’s project then is both to collect real-time data about the unique individual learning process of thousands of users, and then apply those findings to create an adaptive, personalized learning environment for those in the greatest need.