Machine learning is key to scaling personalized learning, presenters from Rice and Duke argue at SXSWEdu.
Educational 'Technology' Across the Ages
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Can personalized learning technology save university students from their own bad study habits?
One of the great promises of applying technology to education is that it will allow every student to have a personalized learning plan, with a closed-loop link between learning assessments and further instruction on areas of weakness.
At SXSWEdu, the educational innovation and learning technologies spin-off of the South by Southwest conference, Richard G. Baraniuk of Rice University and Andrew C. Butler of Duke University spoke about some of the barriers to achieving that goal and presented one possible solution, OpenStax Tutor, an open-source resource aimed at improving college study skills.
"This is not the first time technology has promised to revolutionize education," Baraniuk said. In their day, the movie projector and the television were new technologies promoted for their revolutionary educational potential, he noted.
"The difference is, for the first time we have technologies that are not just broadcast technologies. We have technologies that can acquire massive amounts of personalized data about students as they work through problems," said Baraniuk. That data can drive feedback to the students, as well as feedback for the improvement of curricula and research into better educational methods, he said.
This is the latest in a series of projects Baraniuk has championed through the Rice Center for Digital Learning and Scholarship. Back in 1999, his team introduced Connexions, a site that encourages educators to create modular learning resources and share them freely. OpenStax College was introduduced in February 2012 to promote the creation and promotion of open-source college textbooks. OpenStax Tutor also is aimed primarily at college-level education, although components of the software also are being used as part of Rice's STEMScopes program supporting science, technology, engineering and math education for the K-12 grades.
For the OpenStax Tutor project, Baraniuk, a professor of electrical and computer engineering, has teamed up with experts in cognitive science including Butler.
One of the problems with current approaches to learning is they tend to be "cognitively uninformed," meaning they fail to take advantage of the latest research on how we really learn and remember what we have learned, Baraniuk said.
Left to their own devices, students also tend to choose ineffective study strategies, Butler said. "They're very focused on the short term, so there's a lot of cramming going on," he said. That's a problem because information learned in a rush tends not to be retained very well, he said. What works much better is to space out learning, with testing and refreshing doses of learning spread out over time.
What's most productive isn't necessarily what's easiest. "We want to present students with desirable difficulties," Butler said. "So we have this tension between what people like and what's good for them."
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