Hoping to bring its adaptive technology directly to students, teachers, and creators of 鈥渙pen鈥� educational content, ed-tech company Knewton has produced a new online platform that relies on 鈥渂ig data鈥� 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鈥攊ncreasingly popular among both assessment makers and educational publishers鈥攖o the burgeoning world of open educational resources, or OER.
In a statement, Knewton founder and CEO Jose Ferreira touted the new effort as a 鈥渇riendly robot tutor in the sky.鈥�
Leaders in the OER community expressed enthusiasm about the general possibility of making 鈥渙pen鈥� 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鈥檚 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.
Educators Skeptical
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 糖心动漫vlog, the public, or the OER content creators will embrace the specifics of either approach.
In Knewton鈥檚 case, many 糖心动漫vlog 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鈥檚 apparent 鈥減resumption that content alone can help students master skills and concepts,鈥� 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 鈥渙pen鈥� community values transparency across the board. That could mean that Knewton鈥檚 鈥渃losed鈥� algorithms and statistical techniques will be a significant turnoff for many OER providers.
鈥淭here鈥檚 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,鈥� 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鈥檚 analytics engine has 鈥減owered鈥� 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鈥檚 how the company鈥檚 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 鈥渟tart learning.鈥� 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鈥檚 millions of other users. Through a mind-boggling series of probability calculations, Knewton鈥檚 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鈥檚 algorithms quickly make determinations on the content鈥檚 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 鈥渇ree personal tutor鈥� that 鈥渃an practically read your mind.鈥�
Data-Privacy Challenges
A long list of potential concerns about Knewton鈥檚 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鈥攏ot just whether they get the correct answer鈥攚ill 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 its collection of millions of data points on individual students for creation of extensive 鈥渓earner profiles.鈥� And that was in the context of the company鈥檚 enterprise business with publishers, through which Knewton officials say they don鈥檛 collect or maintain any 鈥減ersonally identifiable information鈥� 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鈥檚 information to be used to improve Knewton鈥檚 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 helped lead a 12-state effort to procure high-quality OER for classroom use. As part of that initiative, more than two dozen state- and local academic content experts reviewed every unit submitted by approved bidders.
鈥淚鈥檓 not a data scientist,鈥� Wolfe said, 鈥渂ut that kind of vetting process by experts just gives me more comfort.鈥�
Green, of Creative Commons, also expressed concern over what he described as Knewton鈥檚 narrow focus on educational content alone. 鈥淚nteraction solely with content has a limited effect compared to interaction with content, teachers, peers, and the Web,鈥� Green said.
Addressing Criticism
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 鈥渆xpert judgment,鈥� which 鈥渉as an uninterrupted track record of failure.鈥�
And as for the role of teachers and peer interactions in student learning? 鈥淲e don鈥檛 claim to replace those things; we wouldn鈥檛 want to,鈥� chief research officer David Kuntz wrote in an email.
The company鈥檚 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鈥檚 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 鈥渆xciting鈥� and 鈥減ositive.鈥�
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. 鈥淲e think that long-term, people who build awesome things get rewarded for it,鈥� he said.
