Hoping to bring its adaptive technology directly to students, teachers, and creators of “open” educational content, ed-tech company Knewton has produced a new online platform that relies on “big data” to match individual learners to specific instructional materials that are ostensibly best-suited to their own learning needs and styles.
The creation of the platform marks the most aggressive attempt to date to merge such algorithm-based personalization—increasingly popular among both assessment makers and educational publishers—to the burgeoning world of open educational resources, or OER.
In a statement, Knewton founder and CEO Jose Ferreira touted the new effort as a “friendly robot tutor in the sky.”
Leaders in the OER community expressed enthusiasm about the general possibility of making “open” material (which is licensed in such a way as to be available for free use, revision, and sharing) adaptive. They believe the type of advanced learning analytics pioneered by companies such as Knewton might help solve one of their field’s central challenges: how to quickly surface the best content from among the millions of open educational resources now housed in numerous content repositories and countless individual websites.
A somewhat-related effort was also launched last month by Portland, Ore.-based Lumen Learning, which aims to provide schools with complete OER courseware that contains adaptive functionality that claims to give students some say in deciding what content they receive.
It remains to be seen if educators, the public, or the OER content creators will embrace the specifics of either approach.
In Knewton’s case, many educators and parents remain skeptical of big-data and algorithm-driven education, especially in an era of heightened concern around student-data privacy.
Educators may also be skeptical of Knewton’s apparent “presumption that content alone can help students master skills and concepts,” said Cable T. Green, the director of global learning for Creative Commons, a nonprofit that encourages the use and sharing of open tools and information.
And, Green added, the “open” community values transparency across the board. That could mean that Knewton’s “closed” algorithms and statistical techniques will be a significant turnoff for many OER providers.
“There’s a red flag raised by any company making claims about the value or effectiveness of learning resources without allowing the public to see what those claims are based on,” he said. Knewton was founded in 2008 by Ferreira, a former executive at test-prep giant Kaplan and derivatives trader at Wall Street powerhouse Goldman Sachs.
The company says it has since delivered billions of educational-content recommendations to almost 10 million students in 20 countries, across both K-12 and higher education.
But to date, Knewton’s analytics engine has “powered” only the proprietary content of the educational publishers with which it partners, including heavy-hitters such as Pearson and Houghton Mifflin Harcourt.
How the Algorithms Work
Here’s how the company’s new platform works: Students and other users can sign up for free directly at knewton.com. After a brief registration process, they can select the subject area, topic, and specific skills they are interested in, then click a button that says “start learning.” Immediately, the user will be introduced to content that is algorithmically selected to diagnose what he or she already knows.
As soon as the student begins interacting with that content, Knewton begins harvesting reams of data and comparing that information with the data already collected on the company’s millions of other users. Through a mind-boggling series of probability calculations, Knewton’s algorithms then begin determining which content is most likely to help the user learn what he or she has not yet mastered in the most efficient, engaging way possible.
At the same time, teachers and other creators of instructional materials can upload their lessons, YouTube videos, and the like to the site for free. Teachers might assign their own content to their own students, Ferreira said, or the Knewton platform might assign a new resource to a small initial group of carefully selected users. By comparing how well those users learn with that content to how well other users learn the same skills and concepts with different content, Knewton’s algorithms quickly make determinations on the content’s effectiveness, ability to engage students, and capacity to create valuable data for future use.
Knewton officials boast that their algorithms and statistical techniques are light years beyond those used by other companies in the adaptive-learning field.
The end result, Ferreira said, is that users get a “free personal tutor” that “can practically read your mind.”
A long list of potential concerns about Knewton’s new platform highlights the challenges of making OER truly adaptive, however.
For those skeptical of algorithms choosing all the content students see, the Lumen approach may be more appealing. In that courseware, students can rate their own level of confidence when answering specific questions, and that information—not just whether they get the correct answer—will be used to help select the next question they are asked. The idea is to give students some say in shaping their own learning pathways.
Knewton has also received intense scrutiny from privacy advocates over itsAnd that was in the context of the company’s enterprise business with publishers, through which Knewton officials say they don’t collect or maintain any “personally identifiable information” on individual students. The new consumer-oriented platform, on the other hand, will require students or their parents to create an account specific to their child and agree to allow their child’s information to be used to improve Knewton’s educational services.
And leaders in the OER field expressed hesitance about adaptive technology that relies almost entirely on statistical, rather than human, determinations about the quality of educational content.
Jennifer A. Wolfe, for example, is a partner with the Learning Accelerator, a nonprofit that has. As part of that initiative, more than two dozen state- and local academic content experts reviewed every unit submitted by approved bidders.
“I’m not a data scientist,” Wolfe said, “but that kind of vetting process by experts just gives me more comfort.”
Green, of Creative Commons, also expressed concern over what he described as Knewton’s narrow focus on educational content alone. “Interaction solely with content has a limited effect compared to interaction with content, teachers, peers, and the Web,” Green said.
Knewton believes that such concerns are either overblown or surmountable.
To begin with, the company insists it will not sell or share student data.
When it comes to vetting content, Ferreira said, statistical analysis is actually far more reliable than “expert judgment,” which “has an uninterrupted track record of failure.”
And as for the role of teachers and peer interactions in student learning? “We don’t claim to replace those things; we wouldn’t want to,” chief research officer David Kuntz wrote in an email.
The company’s new platform launched with nearly 100,000 pieces of content, the majority of which were curated by Knewton staff. Whether teachers, OER creators, and others volunteer to build on that foundation with their own lessons will go a long way to determining the product’s success.
Despite their concerns, both Wolfe and Green praised Knewton for taking a leading role in bringing adaptive technology to OER, a move they described as “exciting” and “positive.”
And for his part, the ever-brash Ferreira voiced no doubt that both the OER and consumer markets will learn to embrace what Knewton is offering, even if hesitation currently abounds. “We think that long-term, people who build awesome things get rewarded for it,” he said.
A version of this article appeared in the September 09, 2015 edition of Education Week as Blending Adaptive Technologies With Open Ed. Resources