Imagine classrooms outfitted with cameras that run constantly, capturing each child’s every facial expression, fidget, and social interaction, every day, all year long.
Then imagine on the ceilings of those rooms infrared cameras, documenting the objects that every student touches throughout the day, and microphones, recording every word that each person utters.
Picture now the children themselves wearing Fitbit-like devices that track everything from their heart rates to their time between meals. For about a quarter of the day, the students use Chromebooks and learning software that track their every click and keystroke.
What you’re seeing is the future of K-12 education through the eyes of Max Ventilla, the CEO of AltSchool, a Bay Area startup that represents the most aggressive, far-reaching foray into the world of big data and analytics that the K-12 education sector has seen to date.
Eventually, Ventilla envisions AltSchool technology facilitating an exponential increase in the amount of information collected on students in school, all in service of expanding the hands-on, project-based model of learning in place at the six private school campuses the company currently operates in Silicon Valley and New York City.
He sees all those torrents of data flowing from the classroom into the cloud, where AltSchool engineers will have built systems for merging the disparate streams into a single river of information. AltSchool software and algorithms created by Silicon Valley’s top developers and data scientists would then search the waters for patterns in each student’s engagement level, moods, use of classroom resources, social habits, language and vocabulary use, attention span, academic performance, and more.
The resulting insights—say, that 6th graders perform better in math after exercising, or that the girls in a particular science class are bored because boys use the lab equipment more frequently, or that Johnny is using new vocabulary words in conversations with his friends—would be fed to teachers, parents, and students via AltSchool’s digital learning platform and mobile app, which are currently being tested. The information would be accompanied by scheduling tips, recommendations for more gender-neutral science activities, and a playlist of assignments customized to each student.
How those suggestions are used, and whether they make a difference in how well each student learns, would also be tracked, creating a never-ending feedback loop of insights, experiments, recommendations, and product tweaks.
“We don’t want to improve some aspects of what schools do. We want a different kind of universe in which schools can exist 30 years from now,” said Ventilla, a 35-year-old Yale University graduate who previously worked as the head of personalization at online-services-giant Google.
For better or worse, it’s not just pie in the sky talk.
Over the past decade, big data and analytics have slowly crept into the world of public education. Versions of the unobtrusive, real-time, embedded-in-everyday-activities collection of student-learning data now being pioneered by AltSchool and others are touted in the federal government’s new National Education Technology Plan. Many observers hope the next step is the type of systemwide change that has already transformed the financial sector, health care, consumer technology, retail sales, and professional sports, among other industries.
And while Ventilla’s plans may seem grandiose, there are some good reasons to pay attention to what the company is doing.
For one, Ventilla has attracted top talent from his old employer, as well as leading companies in consumer technology and some of the top independent schools in the region. The AltSchool team has already prototyped and deployed some of the systems inside its own schools. And fueled by $133 million in venture capital from Facebook CEO Mark Zuckerberg and others, AltSchool’s 50-plus engineers, data scientists, and developers are designing tools that could be available to other schools by the 2018-19 school year.
Still, lots could go wrong. Among other barriers, AltSchool is almost certain to provoke a backlash from parents and privacy advocates who see in its plans the potential for an Orwellian surveillance nightmare, as well as potentially unethical experimentation on children.
But even if the company crashes and burns, some key observers hope its efforts will better illuminate the possibilities and pitfalls confronting a sector still wrestling with the questions of whether and how to embrace analytics.
“There are a multitude of entrepreneurs who are building learning experiences based on how Google thinks about the world, that you can leverage data in ways that produce beneficial outcomes,” said Robert J. Hutter, a managing partner at Learn Capital, a venture-capital firm that has invested in AltSchool and other companies. “The hope is that those experiments will be understood and appropriated by leaders in K-12.”
What Are Big Data and Analytics?
The term “big data” is generally used to describe data sets so large they must be analyzed by computers. Usually, the purpose is to find patterns and connections relating to human behavior and how complex systems function.
Analytics generally refers to the process of collecting such data, conducting those analyses, generating corresponding insights, and using that new information to make (what proponents hope will be) smarter decisions.
For years, public schools and ed-tech companies have experimented with both, usually with two goals in mind: to better personalize instruction, by customizing the learning experience to each student’s individual skills, abilities, and preferences; and to facilitate more data-driven operational decisions.
Inside school systems, advances have been made. It’s now common, for example, for classrooms to use learning software and digital games that generate extensive data that can be mined for evidence of student learning. At the macro level, districts routinely analyze large data sets containing information on students’ academic performance, attendance patterns, and even involvement with other public agencies. The results are used to predict which students are likely to become disengaged or drop out of school, then to intervene accordingly, among other purposes.
In the ed-tech industry, meanwhile, big data and analytics are everywhere. Companies ranging from Khan Academy to Pearson collect and analyze reams of information on how millions of students interact with digital content. Other companies promise to help district administrators use big data to predict everything from which candidates for teaching jobs are likely to have the biggest impact on student-test scores to where population growth will require that new school buildings be built in the future.
But experts say such initiatives have mostly resulted in small pockets of innovation or incremental shifts to existing practices, rather than systemic transformation.
One big reason: Big chunks of the data currently in use are either stored on paper or in teachers’ heads. And much of the digital information in use is generated via students’ on-screen and online activity, which even those in the ed-tech world acknowledge can capture only a limited slice of what constitutes real learning.
Other barriers exist, too. Even when new technologies have been introduced into classrooms, teachers have been slow to change the ways they teach. Districts have struggled for years to integrate data housed in separate silos. The education sector is embroiled in debates over how student information should be appropriately collected, shared, and used.
The net result is that school officials often settle for using technology to meet basic compliance requirements, said Jeff Wayman, a former educational researcher at Johns Hopkins University who now consults with districts on effective data systems.
“Technology got schools to a point where they can get done the things that have to get done,” Wayman said. “But in their heart of hearts, I think a lot of developers would say the technology is so much more powerful than how it’s being used.”
Analytics in Professional Sports, Other Industries
Other industries have found themselves in analogous positions.
Take, for example, professional sports, including the National Basketball Association.
Until recently, the types of data that even forward-thinking NBA teams collected were fairly limited, said Benjamin Alamar, a former executive with the Seattle SuperSonics (now the Oklahoma City Thunder) and the current director of sports analytics for the giant sports-entertainment company ESPN Inc.
Only a handful of franchises were doing any kind of complex statistical analysis of the information that was collected, Alamar said. Even those teams often stored their information in scattered spreadsheets and databases used by different people for different purposes. Information-related turf wars between departments were common. Many teams suffered from a lack of consensus around which metrics of success really mattered. Inconsistent ways of formatting and handling data exacerbated all those other problems.
The end result was that harried decisionmakers—in the NBA’s case, coaches and general managers—often struggled to access new forms of information, leading them to rely instead on established habits.
“The challenges are the same from industry to industry,” Alamar said.
In a short period of time, however, the NBA has been transformed.
To staff their new analytics departments, pro basketball teams now compete with tech giants and blue-chip management-consulting firms for data scientists with computer-programming skills and deep knowledge of advanced statistics.
NBA arenas are now outfitted with sophisticated camera systems that capture the location, movement, and actions of every player on the court 25 times per second. The system has produced a mountain of new data on such minutiae as the optimal number of times each player should dribble before shooting.
And teams are building new information-management systems that integrate such data with quantitative game-performance results, qualitative scouting notes, leaguewide salary information, biometric data on everything from players’ sleep habits to their exertion levels during practice, and multimedia files (such as video clips of an individual player’s tendencies.)
The game itself has changed as a result. One of the original insights of the basketball-analytics movement was that 3-point shots (taken from further out on the court) and layups (taken close to the basket) produce points far more efficiently than mid-range shots.
In response, teams have made a series of personnel, training, and tactical shifts, resulting in a league-wide trend of players taking inefficient, long 2-point shots far less frequently this year than they did just four years ago, as can be seen in the following charts.
Now, Alamar said, the challenge for NBA decisionmakers is how to stay ahead of the curve. In an analytics-driven culture, “you’re always growing, and you’re never there,” he said.
From Retail to Education Analytics
As vice president of research and development for retail-analytics firm RetailNext, George Shaw helped large stores usher in similar changes.
Mostly, that meant using video cameras to monitor shopping floors, then applying software and algorithms to the resulting footage to categorize people into shoppers versus employees, for example; track their locations and movements; document each item they touched; and connect all that information with what they ended up buying.
Now AltSchool’s head of technical research and development, Shaw is at the forefront of developing similar “passive observation” techniques for education.
“The idea is to lay down the path for understanding everything that happens in the classroom without the need for any sort of intrusive sensing at all,” he said.
The first big step toward that goal is the company’s AltVideo camera system, now installed in every classroom across all six AltSchool campuses. For now, the footage is mostly used by teachers and administrators on an ad hoc basis—if someone wants to review a particularly fruitful interaction with a student, for example.
But Shaw is helping lead the company’s efforts to begin what he calls “automated metadata production” on that footage. To begin that process, AltSchool is, now testing motion-tracking algorithms similar to those used in both the NBA and retail analytics. Eventually, that could expand to include applying advanced facial recognition, affect detection, and computer-vision algorithms to the footage to generate digital data on students’ engagement levels, emotional states, and more.
AltSchool leaders are still imagining the potential uses of such information, said Bharat Mediratta, the company’s co-founder and chief technology officer.
“First, we need to generate the big data,” he said. “Then, we start figuring out how to use it to transform education.”
Reasons for Skepticism
Before dismissing such a plan as hopelessly audacious, consider Mediratta’s pedigree.
For a decade, the 45-year-old Colgate University graduate was a top engineer at Google, where he was responsible for the technological and analytics infrastructure behind the company’s home page, through which users enter billions of Internet searches every day.
At AltSchool, Mediratta said, he’s trying to apply similar processes to another “humanity-sized challenge": replacing the top-down, slow-moving bureaucratic structures that currently shape public education with a “networked model” in which students, teachers, and schools are connected directly by information and thus capable of learning and adapting more quickly.
“We will get to the point where we have the same kind of big-data opportunities that Google has,” Mediratta said, “and we’ll be able to take advantage of them.”
Even so, it’s difficult to envision the country’s 100,000 or so public schools—in many places still struggling just to get adequate Internet and Wifi connections—adopting such radically new methods.
“It’s not difficult to find many others who have been very accomplished, and brought a lot of money to the table, and still fell short of their own lofty goals,” said Douglas A. Levin, the president of EdTech Strategies, a consulting group on school-technology issues.
For their part, AltSchool’s founders say that’s why they are playing the long game.
The company isn’t trying to create technology tools that have to be quickly sold and shoehorned into traditional public schools. It intentionally avoided the charter-management route taken by other presumptive innovators with big plans to change American public education.
Instead, AltSchool’s strategy is to invest heavily in research and product development, while also continuing to open more private “micro-schools” that serve as labs for those tools to be deployed, tested, and used to generate the data that is ultimately the company’s lifeblood.
The idea is to first establish a network of schools delivering high-quality education; then develop the technologies that can support the expansion of that network; and ultimately leverage the ever-growing amount of data the network produces to continually make the whole system, schools and technology alike, smarter and more effective.
And what does a “high-quality education” look like at AltSchool?
Ventilla describes it as ‘Montessori 2.0': a kind of supercharged version of the progressive, project-based learning often found in elite private schools and privileged enclaves within traditional school systems.
Play and hands-on learning are stressed—the less time students spend in front of screens, the better, Ventilla said. Standardized tests are viewed as an inadequate, outdated mode of measuring student learning. Involving parents in the details of their children’s education is core to the company’s mission.
That philosophy can be seen in action at AltSchool-Fort Mason, housed in a converted 24-hour fitness center a block from the San Francisco Bay, across the water from Alcatraz Island.
The theme for Christie Seyfert’s middle-grades class this year is exploring how systems function. Students are engaged in a months-long, classwide simulation of how different economic systems work. In English/language arts, the students investigated the forces contributing to the city’s problem with homelessness, conducting real-world interviews with experts as part of an assignment to rewrite an opinion piece on the issue that appeared in the San Francisco Examiner.
Each student received a customized version of the assignment, based in part on insights Seyfert gleaned from her students’ daily use of Newsela, a Web tool that customizes newspaper articles to each child’s reading level, then tracks their progress in developing specific skills.
“Here, we’re using data, but in ways that are so personalized to kids’ needs, learning styles, passions, and goals,” said Seyfert, who previously worked both as a Teach For America corps member in a tightly regimented public school environment and as an adult “collaborator” in an independent, project-based K-12 school.
“Now, I have an understanding of where [students] are with core skills, but there’s also that depth of engagement in what they’re learning,” she said.
The trade-off, though, is being subjected to AltSchool’s extensive monitoring. The company believes that scaling personalized, project-based learning is only possible with the new forms of data collection and analytics it is developing.
A great teacher might be able to gather and process and use information about the emotional states, social interactions, and classroom reactions of a handful of students at any given time, Ventilla said. But getting thousands of teachers to consistently do that for 20-plus students apiece requires a big technological boost, he believes.
So far, at least, it’s a deal that dozens of AltSchool-Fort Mason families have proved willing to pay $26,250 a year to make.
“They use the data they get to improve their own performance, for research, and for feedback to teachers and students,” said Mark Eisner, the vice president of a Silicon Valley biotech firm who has a 13-year-old daughter at the school. “I honestly have a hard time understanding the resistance to that.”
Despite the intense privacy-related concerns that others hold, AltSchool is betting that Eisner’s attitude will eventually carry the day. Three decades from now, the company hopes, schools won’t be able to imagine operating without the types of big-data-driven technologies that it is developing—just as most schools now couldn’t imagine functioning without light bulbs, personal computers, or Internet search engines.
Such a transformation is already well underway in other sectors of the economy. Even if AltSchool isn’t the one to usher such sweeping shifts into the world of public education, others are amassing on the horizon.
“Folks that are coming from the Internet and more digital domains, we tend to want to be able to constantly measure ourselves, because we need to be constantly improving,” Ventilla said. “The model for education right now is not very susceptible to change. But give us time.”
Coverage of the implementation of college- and career-ready standards and the use of personalized learning is supported in part by a grant from the Bill & Melinda Gates Foundation, at www.gatesfoundation.org. Education Week retains sole editorial control over the content of this coverage.
A version of this article appeared in the January 13, 2016 edition of Education Week as Unleashing Classroom Analytics