The more students using the technology, the more data it can pull from.

The more data it can pull from, the more knowledgeable and accurate the recommendations become. Knewton’s Chief Operating Officer, David Liu, said that’s exactly what’s happening with the recommendations in My Lab’s and Mastering’s foundational courses.

By targeting accurate areas of weakness, the suggestions are starting to become trusted by both students and faculty, he said. So why branch out from the kinds of courses that seem the best suited for adaptive learning technology?

Liu said part of the reason is to show that the technology can be used just as well in more advanced courses, and with more advanced students.

“We’ve always believed and known that if you have a rubric around what is right and what is wrong, then we can make it adaptive,” he said. “All students can be positively affected by adaptive learning, not just those in remedial courses. Kids doing really well are often bored in class, and so how do we keep those kids engaged? Adaptive learning is helping students at both ends of the spectrum, and certainly kids in the middle.”

When deciding which advanced courses to test out with adaptive learning, Pearson and Knewton chose to focus on STEM courses specifically. By 2018, more than 8.65 million people are expected to be working in STEM fields in the United States.

Corey said this area was an obvious, and important, place to take adaptive learning technology next.

“Like those college readiness courses, it’s clear that too many students are being left behind in STEM courses,” he said.

 

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