By Jason Gaulden
We have entered the Age of Agility, an exciting, unsettling time in our nation’s history. Going forward, workers and businesses will have to adapt continuously to rapidly changing circumstances caused by the accelerating adoption of workplace automation and artificial intelligence.
This new age might offer great benefits to individuals and businesses, or it could displace hundreds of thousands, even millions, of workers over the next couple of decades. PricewaterhouseCoopers estimates 38 percent of U.S. jobs will be automated by 2030. To put that in context, kids in sixth grade today will be entering the prime of their working lives then.
And despite popular misconceptions, it’s not just jobs on factory floors that are imperiled. Truck drivers, medical technicians, and even lawyers could find their jobs disappearing. White- and blue-collar jobs alike are vulnerable, though lower-paying jobs are likely to vanish first and in greater numbers.
More than at any time in recent history, it’s impossible to know what future employment will look like, in terms of the structure of work, the tasks involved, and the specific expertise required. This would seem to offer great opportunity, if we can prepare ourselves to seize it. How do we address upheaval of such astounding proportions? As Alan Gottlieb and I argue in our new report, Age of Agility: Education Pathways for the Future of Work, it must begin with our education system.
Students exiting the pre-K–12 system will need to be ready for radical societal and workplace changes if they are to have any shot at thriving personally or professionally. This requires an education system that models the virtues of agility—one that is responsive to and prepares students for rapid changes. By and large, however, our schools are failing to prepare them for this emerging reality.
An evolving school of thought promotes scrapping our existing systems and starting over. The basic argument here is that the status quo is so rife with perverse incentives, entrenched special interests, and ideological polarization that even the incremental changes achieved to date have occurred only after protracted political battles. In many other sectors of our high-tech society, change is often transformative and quick. But there is a deeply embedded resistance to agility in American education today, which demonstrates the need for an overhaul, yet simultaneously makes that difficult. This has to change.
To be sure, today’s elementary education, with more experiential learning added to the mix, needs to remain in place because young children need to be fluent readers and writers and acquire at least basic computational skills at an early age. None of the exciting opportunities that need to be available to middle- and high-school-aged students will be possible if they lack those foundational skills. But education of young children needs to be far more effective and engaging if we hope to achieve better than the middling results we’ve settled for over the decades.
One preliminary step school systems could take to prepare students for the future would be to create networks of truly diverse schools. Recent evidence demonstrates that racially and economically integrated, inclusive schools are ideally positioned to help young people develop the capacities they will need to thrive in increasingly diverse workplaces.
Another solution is to create learning opportunities more customized to individual students’ strengths, passions, and progress. Indeed, in isolated pockets throughout the country, practitioners are beginning to provide real-life models of highly personalized learning. Many of these places also break down barriers between seat-time and real-life experience, encouraging and enabling students to work in a variety of environments, with ever-shifting sets of people. This helps prepare children for a world characterized by rapid and perpetual change.
But these are just two of many possible strategies. If we’re willing to stretch our thinking, to step outside obsolete paradigms, then we can enact policies that create conditions that allow substantive change to occur.
So let’s start the serious work required to retool our education system. Every city and state needs to act urgently to convene business leaders, policymakers, and educators who can work together to develop entirely new education and training systems.
To some people, the idea of a highly automated workforce seems like an abstract concept, a time off in the distant future that won’t possibly affect them. They’re wrong. The race against robots has begun, and the Age of Agility is already upon us. There’s no time to waste if we are to provide the real-world preparation our students desire and deserve.
Jason Gaulden is Communications Director at America Succeeds, a national network of business leaders working to improve education policy and practice. He also leads the organization’s Agility Agenda, a campaign to improve the nation’s education-to-employment system.
The views expressed herein represent the opinions of the author and not necessarily the Thomas B. Fordham Institute.
Editor’s note: This essay is a response to Jason Gaulden’s Flypaper article, “America’s anachronistic education system,” as well as Education Week’s recent Special Report, “Schools and the Future of Work.”
Within the last week, Apple co-founder Steve Wozniak announced the founding of “Woz U,” a digital institute designed to inspire the next generation of innovators. The CEO of Google, Sundar Pichai, also proclaimed that the tech giant will invest $1 billion over the next five years to remediate what he sees as an alarming disconnect between how college graduates are prepared and what the job market actually requires. "The nature of work is fundamentally changing,” Pichai said, “and that is shifting the link between education, training, and opportunity. One-third of jobs in 2020 will require skills that aren't common today. It's a big problem."
The tech gods have spoken and are aligned: Our country faces a crisis in educating our children to meet an increasingly complex world. Where does this disconnect leave us educators? We need to develop our graduates’ skills and talents for an evolving twenty-first-century economy, but the goalposts have shifted away from the aim of our current schools, and it is hard to know where to start. What hope do we educators have to design a curriculum, program, and school culture that will actually matter for our students?
We can best do this by returning to a timeless and always applicable approach: a classical liberal arts education.
Before you dismiss this idea as nostalgic blowback, consider that the best hedge against the vicissitudes of fortune will always be the permanent: clear thinking, wisdom, and character, which a classical education is ideally structured to inculcate as a foundation for life-long learning. Indeed, we can’t know what and where jobs will be a few years from now, but history and human nature tell us that thoughtful leadership will be required. In every age of uncertainty, we should double down on the enduring ends of a classical education—the ability to deliberate carefully, see multiple sides of an issue, and exercise sound and decisive judgment. We sometimes call this critical thinking, but the ancients called it wisdom.
At Great Hearts, the classical charter school network I co-founded, we seek to develop wisdom in pursuit of truth, goodness, and beauty. The medium of this pursuit is earnest conversation regarding, as Matthew Arnold said, “the best that has been thought and said.” All of our high school students have at the center of their day a two-hour Socratic conversation on works of great literature, philosophy, art, and history. Socratic pedagogy is deployed in all subjects, from music to physics.
In these spaces, students use the ideas of great authors, artists, and scientists of the past to understand classmates’ perceptions and premises by asking respectful, relevant questions. They learn to acknowledge ambiguity, respect disagreement, accept doubt, and allow for multiple interpretations to coexist. They escape the tyranny of the present, as well as their own emotions and concerns. And they imagine the permanent aspects of the human condition, both good and bad, and ponder what has been, what is, and what might be possible.
Every generation faces essential questions—and they skip them at their own peril. What does it mean to be a human being? How does a specific idea, pursuit, or product relate to human happiness? What is justice? What is my duty to myself and others? How does one balance freedom with responsibility? These are not coffee shop queries, but first order questions that are more important than ever in the twenty-first century. And a mind and soul well trained to pursue and answer them—and use this training practically in the workplace—will be ready to innovate and effect change for the greater good.
Unfortunately, too much of education today is focused on standardized tests, getting kids into college, and careerism before one’s career. Some of this is understandable; we want students to think ahead and strive to big goals. But many students are tracked without any consideration of their work’s purpose and inherent nobility, and with little concern for the professions in which their unique talents can be useful. A classical liberal arts education, however, instills in young people the joy of learning for learning’s sake, and helps them discover what makes them happy: the link between their character and unique talents, their calling. And when we are happy and grounded, we are more useful to ourselves and others, no matter what life brings our way.
It’s true, of course, that not every graduate is destined for Silicon Valley or an executive suite. We need craftsmen, tradeswomen, and soldiers. But they too deserve a classical liberal arts education. And they ought to be just as well educated as those in boardrooms and ivory towers. Indeed, American democracy, freedom, and ingenuity depend on poet-warriors and philosopher-technicians. This is why we believe at Great Hearts that all of our public school students should receive a classical liberal arts education before they go on to a profession or pick a major in college.
These, moreover, aren’t just my sentiments. There’s a growing body of research that a classical liberal arts education is not some ivy-covered relic and detour to a useless past, but an increasingly important part of the present and future. George Anders and Randall Stross, for example, both argued in recent books that the emotional intelligence, interpretive capacity, and problem-solving skills enabled by a liberal arts education set graduates of these programs apart from their non-program peers. And in The Age of Agility: Education Pathways for the Future of Work, Jason Gaulden and Alan Gottlieb argue that four capacities will emerge as more and more vital in the decades ahead: the ability to abstract deeper meaning; the self-awareness and empathy to have probing conversations with those from different backgrounds; the ability to intuit novel thinking in fluid environments; and the ability to write and codify processes under a desired outcome. While Gaulden and Gottlieb don’t expressly make the connection, these capacities sound like the cumulative outcomes of any classical liberal arts education worth its salt.
Tim Cook, CEO of Apple, said in his commencement address at the Massachusetts Institute of Technology this past spring: “I’m more concerned about people thinking like computers without values or compassion or concern for the consequences…That is what we need you to help us guard against. Because if science is a search in the darkness, then the humanities are a candle that shows us where we have been and the danger that lies ahead.”
I hope that in the age of expediency we don’t forget the great value of slowing down, of deep reflection and conversation, and of living in community in the shared search for truth and meaning. Abraham Lincoln said “the best thing about the future is that it comes one day at a time.” When it comes to schooling, trying to predict the future and rush towards it only diminishes the present. The one thing we do know about the future of work is that a well-stocked mind and well-nurtured soul will be the best provisions for the uncertain journey ahead.
Dan Scoggin is the co-founder and chief advancement officer of Great Hearts, serving 15,000 K–12 scholars in Arizona and Texas and growing nationally.
The views expressed herein represent the opinions of the author and not necessarily the Thomas B. Fordham Institute.
For decades, education technophiles have envisioned a future wherein gee-whiz devices and engaging digital applications whisk students away from the doldrums of traditional classroom instruction and into a fun world of beeping computers, self-paced lessons, and cloud-based collaboration.
That may yet come to pass—and at some outlier schools, is already here—but don’t be surprised if the true transformative power of education technology is most evident when it comes to something old-fashioned: basic education research. The declining cost and easy availability of substantial computing power may enable us finally to unlock the black box of the classroom, giving scholars and teachers much more insight into what is and isn’t working. Technology can do more than just keep students engaged; it can equip teachers, school and district leaders, and policymakers with the sort of insights and analytics that can help them make better decisions for students.
A Challenging Research Subject
Studying the actual behavior of teachers and students has always been a difficult and expensive proposition. The most respected approach involves putting lots of trained observers—often graduate students—in the back of classrooms. There, they typically watch closely and code various aspects of teaching and learning, or collect video, take it back to the lab, and spend innumerable hours coding it by hand.
This kind of methodology has helped the field gain significant insights, such as the importance of teachers asking open-ended questions, and how better to evaluate teachers’ practice, à la the Gates-funded Measures of Effective Teaching initiative. But it’s incredibly labor-intensive, costs gobs of money, and thus may not be practical.
Alternatives to observational studies are much less satisfying. The most common is to survey teachers about their classroom practices or curricula, as is done with the background questionnaires given to teachers as part of the National Assessment of Educational Progress (NAEP). Though useful, these types of surveys have big limitations, as they rely on teachers to be honest and accurate reporters of their own practice—which is tough even with positive intentions. It’s not easy to remember what you taught months ago, and teachers might also try to tell researchers what they think they want to hear or choose responses that cast themselves in a positive light. Another approach, asking teachers to keep logs detailing their work, such as how they spend time, is somewhat more reliable, but still far from perfect. It is also time-consuming, thus stealing precious minutes and hours from teachers’ most important work: helping students learn.
Not surprisingly, the research base on the real stuff of education—instructional practices, homework assignments, the curriculum as it is actually taught—is remarkably thin. Scholars have found easier, cheaper, and more fruitful yields from mining administrative data sets, usually stemming from compliance reports at the school or district level, than from collecting detailed information about what’s happening in real classrooms in real time. This has left the field, and policymakers, with a huge blind spot about what teachers and kids are doing, and what might or might not be working.
“Machine Learning” to Track Student Learning
Enter the machines. What if we didn’t need to have graduate students crouching in the back of classrooms in order to catalog the play-by-play of classroom instruction? What if, instead, we could capture the action with a video camera or, better yet from a privacy perspective, a microphone? And what if we could gather that information not just for an hour or two, but all day, 180 days a year, in a big national sample of schools? And what if we could then use the magic of machine learning to have a computer figure out what the reams of data all mean?
This possibility is much closer than you might imagine, thanks to a group of professors who are teaching computers to capture and code classroom activities. Martin Nystrand (University of Wisconsin-Madison), Sidney D’Mello (University of Notre Dame), Sean Kelly (University of Pittsburgh), and Andrew Olney (University of Memphis) are interested in helping teachers learn how to ask better questions, as research has long demonstrated that high-quality questioning can lead to better engagement and higher student achievement. They also want to show teachers examples of good and bad questions. But putting live humans in hundreds of classrooms, watching lessons unfold while coding teachers’ questions and students’ responses, would be prohibitively costly in both time and money.
So with funding from the Institute of Educational Sciences, this team of researchers decided to teach a computer how to do the coding itself. They start by capturing high-quality audio with a noise-canceling wireless headset microphone worn by the teacher. Another mike is propped on the teacher’s desk or blackboard, where it records students’ speech, plus ambient noise of the classroom. They take the audio files and run them through several speech-recognition programs, producing a transcript. Then their algorithm goes to work, looking at both the transcript and the audio files (which have markers for intonation, tempo, and more) to match codes provided by human observers.
The computer program has gotten quite good at detecting different types of activities—lectures vs. group discussion vs. seatwork, for example—and is starting to be able to also differentiate between good questions and bad. To be sure, D’Mello told me, humans are still more reliable coders, especially for ambiguous cases. But the computers are getting better and better, and good enough that, with sufficient data, they can already produce some very reliable findings at a fraction of the cost of a people-powered study.
It’s even easier, of course, if the underlying instructional data are digital to begin with. That’s the specialty of Ryan Baker, associate professor of teaching, learning, and leadership at the University of Pennsylvania. He and his team examine the “digital traces” of students’ interactions with digital applications—their key strokes, pauses, and answers when working on online math programs, for example. They then build algorithms to make sense of them. Their research starts by asking humans to watch students at work; their insights are fed into their computer models, which learn to replicate the human coding with enough time and data.
Such research has already borne fruit. Baker’s team and its computer have shown that more students become bored, then disengaged, when the material is too hard than when it is too easy. Short periods of confusion and frustration are good; long periods indicate that the student has given up. And some “off task” time—as long as a minute or two—is OK, as students tend to come back refreshed and ready to tackle whatever they are working on. Thus, teachers should allow kids some breathing room rather than cracking the whip the second they see students get distracted.
Putting Data to Work
This is incredibly useful information, the kind that can help teachers improve their practice and boost the efficiency and effectiveness of students’ time in class. Imagine if such studies—both of traditional classroom practices and the digital variety—became much more common. Large national studies like NAEP could complement teacher surveys with the collection of audio, every day, all day, in a big sample of schools. Plus, they could capture the digital activity of students, and ask teachers to scan student assignments and tests so those could be analyzed as well.
We would finally have an accurate picture of what’s actually being taught in U.S. schools. And if we combine that with state administrative and achievement data, and put it in the hands of competent analysts, we’d have a better way to examine which teacher practices, curricula, use of time, and on and on, are related to improved student learning. We could see whether teachers whose students make the largest gains really do make greater use of the concrete practices that Doug Lemov describes in Teach Like a Champion, for example. for example. And we could determine whether and where there are equity gaps in effective teaching, the level of challenge of student assignments, and much else that might be addressed in order to narrow the achievement gap.
Big hurdles remain, to be sure. The biggest aren’t technological, but political: Chronicling classrooms in minute detail will not go over well with all teachers, even if researchers promise that the data will be used for research purposes only. Nor will privacy-minded parents be thrilled; security protocols will need to be established that give everyone involved confidence that the audio recordings won’t fall into the wrong hands. And scholars will need to be careful not to make causal claims based on data sets that aren’t subject to experimental designs; the sheer quantity of data can’t make up for the lack of controls and random assignment. Big data alone can be a boon to “hypothesis generation,” but we’ll still need traditional studies in which teachers are asked to adopt new practices to learn whether the practices work.
Still, the power duo of big data and machine learning will enable us to build a research enterprise that actually improves classroom instruction, regardless of how traditional or technology-infused the instruction might be. That’s enough to make a computer smile.
Editor’s note: This essay was first published by Education Next.
On this week's podcast, special guest Sara Mead, a partner at Bellwether Education, joins Alyssa Schwenk and Brandon Wright to discuss the past, present, and future of early childhood education. During the Research Minute, Amber Northern examines the positive effects of education reform in Newark, New Jersey.
Amber’s Research Minute
Mark J. Chin et al., “School District Reform in Newark: Within- and Between-School Changes in Achievement Growth,” The National Bureau of Educational Research (October 2017).
A new study by RAND examines teachers’ support of their state standards and tests. It’s a nationally representative sample of K–12 teachers, and though educators from all subjects were surveyed, the report focuses only on the responses of math and English language arts (ELA) teachers. It also compares responses from educators who were surveyed in 2015 and 2016 on a subset of repeated questions and looks into how certain teacher and school characteristics are related to teacher support or lack thereof. The survey has a response rate of 45 percent.
There are key five findings. First, nearly 90 percent of both ELA and math teachers support the use of state standards for instruction. Slightly higher percentages believe that math and ELA standards provide a foundation for postsecondary preparation for students and that they support alignment of the curriculum from grade to grade. However, among those same teachers, only about a third say they support the use of current statewide tests to measure mastery of the state standards in their respective subject area.
Second, though standards enjoy wide support from teachers overall, teachers in schools with more lower-income students are even more likely to support the use of state standards in both math and ELA and the use of tests to measure mastery of ELA standards.
Third, a couple subgroup differences are worth mentioning, namely that educators who reported teaching in Common Core states were less likely to support their state tests in math and ELA than those who reported not being in CCSS states. Also, teachers who taught higher numbers of students with special needs were less likely to support the use of tests to measure mastery in math.
Fourth, in looking into the black box, analysts found that those who did not support the standards were less likely than supporters to think that the standards had a manageable number of topics to teach in a year. Non-supporters also felt that the state tests were too difficult for their students and that they would not provide accurate data for students with special needs. Surprisingly, low percentages of supporters and non-supporters (less than a quarter) voiced concerns that the test was not aligned to their standards or that their school lacked the technological capacity to administer the state test.
Fifth and finally, there were no significant changes in teachers’ overall concerns about standards and tests from 2015 to 2016, except for a couple, including that teachers in states that administered the PARCC ELA test in both 2015 and 2016 showed a measurable decrease in various concerns about that test (meaning they were less likely to say that the test would be too difficult for their students, take time away from other important classwork, or not provide accurate scores).
So, at the risk of oversimplification: Most teachers like state standards (though there’s still aversion to Common Core in some cases) and dislike state tests—but also believe that standards alignment and the technology for administering assessments have both improved. And, despite the initial outcry about Common Core tests like PARCC, once you get used to them, they’re not so bad after all. Which seems like something the testing critics (educators and non-educators alike) should keep in mind.
SOURCE: Kaufman, Julia H., Elaine Lin Wang, Laura S. Hamilton, Lindsey E. Thompson and Gerald Hunter, “U.S. Teachers' Support of Their State Standards and Assessments: Findings from the American Teacher Panel,” RAND Corporation (2017).
Rates of college completion for Hispanic students have lagged over the past decade even while the number of Hispanic high school graduates has grown. This—combined with issues of disproportionate poverty in Hispanic communities, their growing share of the college-age population, and concerns about racial and economic inequities—has led to an Education Next study examining what might be done to help more Hispanic students enroll in and graduate from college.
The authors examine the effects of the National Hispanic Recognition Program (NHRP), an intervention undertaken by the College Board to recognize outstanding Hispanic high-school students and encourage them to enroll in college. The initiative identifies the highest performing 2.5 percent of Hispanic students across six geographic regions in the United States. Student eligibility for the award is determined by their eleventh grade Preliminary SAT/National Merit Scholarship Qualifying Test scores, holding a GPA of at least 3.5, and having an ethnicity that is at least one-quarter Hispanic. The NHRP is an intervention that changes two key features of a Hispanic student’s high-school experience: one, the College Board notifies students and school staff about the existence of the NHRP; and, two, with the student’s permission, they share a list of NRHP honorees with postsecondary institutions who are looking to enroll academically exceptional Hispanic students.
The authors construct a national sample of all Hispanic PSAT/NMSQT takers in the U.S. from the graduating classes of 2004 through 2010. They then link individual records to College Board and National Student Clearinghouse datasets, including demographic information, information about eventual college enrollment, high school attended, history of SAT attempts, institutions which received their SAT scores, and AP participation. Also included is information from the Common Core of Data, the Private School Universe Survey, and the Integrated Postsecondary Education Data System, which all include further information on certain high school and postsecondary characteristics. The NHRP’s potential impact is measured using a regression discontinuity design, comparing students on either side of the cut-off point for eligibility according to their PSAT/NMSQT scores.
Findings indicate that NHRP eligibility has a significant effect on the college attendance patterns of Hispanic students, inducing more to apply to and attend more institutions where Hispanic enrollment has traditionally been behind their peers. Eligible students are 5 percentage points more likely to attend colleges that recruit Hispanic students through NHRP; 5 percentage points more likely to attend out-of-state institutions; 3 percentage point more likely to attend public flagship universities; and 1.5 percentage points more likely to enroll in a four-year college, with about two-thirds of this effect driven by a movement away from two-year institutions, which the program presumably inspires.
Researchers also look at the program’s impact on college completion and find positive but statistically imprecise results indicating an increase of 1.5 percentage points in the numbers of students who complete their bachelor's degree. The program’s effects on six-year graduation rates appear to yield similar results. And effects are largest for those at the highest risk of dropping out of college, coming from schools with the largest populations of Hispanic students, located in more rural environments, and with students whose parents are likely to have less education. These students are also more likely to enroll at more competitive universities.
Ultimately, there is no financial reward for students who are eligible for the NHRP, and colleges continue to make their own decisions about college applications. But this study shows how a relatively straightforward but targeted intervention from College Board—in its role as facilitator for promoting mutually beneficial communication between schools, students, and colleges—may positively influence the college enrollment decisions and completion outcomes of Hispanic students, especially those at most risk.
SOURCE: Odel Gurantz et al., “Boosting Hispanic College Completion: Does High-School Recruiting Help More Students Graduate?” Education Next (Summer 2017).