This is pretty cool. I’m a firm believer that the “one size fits all” approach really doesn’t work when it comes to education. I remember when I was about 15 years old at high school; my arts teacher was a great believer in playing to each student’s strengths. So while the other kids were slapping paint on paper (or each other, as the case might be), I was happily roaming the woods behind the school gathering twigs with which to build models of prehistoric dwellings.
In fact, now I come to think about it, I even had my own key to the art block (which was separate from the main school building) so that I could come in at the weekends and fire my ceramics in the kiln. Now that’s individual teaching for you. (The teacher in question ended up selling his house, buying a North Sea fishing boat – on the basis that it could survive any type of weather – converting it into luxury accommodation, and sailing off into the sunset with his wife. I never heard from them again. They could still be wandering the world’s oceans for all I know.)
But we digress… I just heard that Arizona State University (ASU) has announced plans today to adopt Knewton’s Adaptive Learning Technology for developmental math courses and two of its largest college-level math courses. Knewton, an educational technology firm, will provide ASU with its Adaptive Learning Platform to help developmental and college-level learners in mathematics prepare for the rigors of college-level academics.
Knewton’s platform will integrate fully with MAT117 (College Algebra) and MAT142 (College Mathematics), creating a unique learning experience that is customized for each student. Knewton optimizes each student’s learning graph around which concepts s/he is weakest at and which are most important, delivering uniquely personalized study material each day to each student based on what s/he knows and how s/he learns best. Both courses will be offered online and in dedicated computer labs, and will be made available to approximately 6,800 students in the 2011-2012 academic year.
“Historically, student performance in entry-level math has been a strong predictor of academic success,” said Phil Regier, Executive Vice Provost and Dean of ASU Online. “The reality is that every student learns differently. Especially for many developmental and returning students, rigorous but personalized instruction may be the boost they need to succeed academically and move beyond what can be a major barrier to graduation.”
“We built this technology to allow schools to create a highly personalized and highly scalable learning experience for each student,” said Knewton founder Jose Ferreira. “Not everyone enters college on equal footing, and even the strongest students have conceptual weak spots. Now Knewton can diagnose each student’s proficiency on every concept, generate the perfect content in response, and give students and teachers powerful new analytical tools about student performance.”
Participating students will begin with a preliminary assessment, resulting in an Adaptive Remediation module with virtual and in-person tutoring. Once students demonstrate college readiness in mathematics, they will advance into ASU instructor-led math courses. Knewton technology will also support students in these entry-level math courses with continual learning assessments of their mastery of key course concepts.
ASU has successfully used adaptive learning techniques in experimental sections of MAT117 for the past two semesters. Knewton-powered courses will significantly enhance and expand adaptive learning at ASU, and are expected to launch in late spring 2011.
David Patterson, known for his pioneering research that led to RAID, clusters and more, is part of a team at UC Berkeley that recently made its RISC-V processor architecture an open source hardware offering. We talk with Patterson and one of his colleagues behind the effort about the opportunities they see, what new kinds of designs they hope to enable and what it means for today’s commercial processor giants such as Intel, ARM and Imagination Technologies.