How Has Technology Changed Education?
Technology has impacted almost every aspect of life today, and education is no exception. Or is it? In some ways, education seems much the same as it has been for many years. A 14th century illustration by Laurentius de Voltolina depicts a university lecture in medieval Italy. The scene is easily recognizable because of its parallels to the modern day. The teacher lectures from a podium at the front of the room while the students sit in rows and listen. Some of the students have books open in front of them and appear to be following along. A few look bored. Some are talking to their neighbors. One appears to be sleeping. Classrooms today do not look much different, though you might find modern students looking at their laptops, tablets, or smart phones instead of books (though probably open to Facebook). A cynic would say that technology has done nothing to change education.
However, in many ways, technology has profoundly changed education. For one, technology has greatly expanded access to education. In medieval times, books were rare and only an elite few had access to educational opportunities. Individuals had to travel to centers of learning to get an education. Today, massive amounts of information (books, audio, images, videos) are available at one’s fingertips through the Internet, and opportunities for formal learning are available online worldwide through the Khan Academy, MOOCs, podcasts, traditional online degree programs, and more. Access to learning opportunities today is unprecedented in scope thanks to technology.
Opportunities for communication and collaboration have also been expanded by technology. Traditionally, classrooms have been relatively isolated, and collaboration has been limited to other students in the same classroom or building. Today, technology enables forms of communication and collaboration undreamt of in the past. Students in a classroom in the rural U.S., for example, can learn about the Arctic by following the expedition of a team of scientists in the region, read scientists’ blog posting, view photos, e-mail questions to the scientists, and even talk live with the scientists via a videoconference. Students can share what they are learning with students in other classrooms in other states who are tracking the same expedition. Students can collaborate on group projects using technology-based tools such as wikis and Google docs. The walls of the classrooms are no longer a barrier as technology enables new ways of learning, communicating, and working collaboratively.
Technology has also begun to change the roles of teachers and learners. In the traditional classroom, such as what we see depicted in de Voltolina’s illustration, the teacher is the primary source of information, and the learners passively receive it. This model of the teacher as the “sage on the stage” has been in education for a long time, and it is still very much in evidence today. However, because of the access to information and educational opportunity that technology has enabled, in many classrooms today we see the teacher’s role shifting to the “guide on the side” as students take more responsibility for their own learning using technology to gather relevant information. Schools and universities across the country are beginning to redesign learning spaces to enable this new model of education, foster more interaction and small group work, and use technology as an enabler.
Technology is a powerful tool that can support and transform education in many ways, from making it easier for teachers to create instructional materials to enabling new ways for people to learn and work together. With the worldwide reach of the Internet and the ubiquity of smart devices that can connect to it, a new age of anytime anywhere education is dawning. It will be up to instructional designers and educational technologies to make the most of the opportunities provided by technology to change education so that effective and efficient education is available to everyone everywhere.
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How Technology Is Changing the Future of Higher Education
Labs test artificial intelligence, virtual reality and other innovations that could improve learning and lower costs for Generation Z and beyond.
By Jon Marcus
This article is part of our latest Learning special report . We’re focusing on Generation Z, which is facing challenges from changing curriculums and new technology to financial aid gaps and homelessness.
MANCHESTER, N.H. — Cruising to class in her driverless car, a student crams from notes projected on the inside of the windshield while she gestures with her hands to shape a 3-D holographic model of her architecture project.
It looks like science fiction, an impression reinforced by the fact that it is being demonstrated in virtual reality in an ultramodern space with overstuffed pillows for seats. But this scenario is based on technology already in development.
The setting is the Sandbox ColLABorative, the innovation arm of Southern New Hampshire University, on the fifth floor of a downtown building with panoramic views of the sprawling red brick mills that date from this city’s 19th-century industrial heyday.
It is one of a small but growing number of places where experts are testing new ideas that will shape the future of a college education, using everything from blockchain networks to computer simulations to artificial intelligence, or A.I.
Theirs is not a future of falling enrollment, financial challenges and closing campuses. It’s a brighter world in which students subscribe to rather than enroll in college, learn languages in virtual reality foreign streetscapes with avatars for conversation partners, have their questions answered day or night by A.I. teaching assistants and control their own digital transcripts that record every life achievement.
The possibilities for advances such as these are vast. The structure of higher education as it is still largely practiced in America is as old as those Manchester mills, based on a calendar that dates from a time when students had to go home to help with the harvest, and divided into academic disciplines on physical campuses for 18- to 24-year-olds.
Universities may be at the cutting edge of research into almost every other field, said Gordon Jones, founding dean of the Boise State University College of Innovation and Design. But when it comes to reconsidering the structure of their own, he said, “they’ve been very risk-averse.”
Now, however, squeezed by the demands of employers and students — especially the up and coming Generation Z — and the need to attract new customers, some schools, such as Boise State and Southern New Hampshire University, are starting labs to come up with improvements to help people learn more effectively, match their skills with jobs and lower their costs.
More than 200 have added senior executives whose titles include the words “digital” or “innovation,” the consulting firm Entangled Solutions found; many were recruited from the corporate and tech sectors. M.I.T. has set up a multimillion-dollar fund to pay for faculty to experiment with teaching innovations .
Some colleges and universities are collaborating on such ideas in groups including the University Innovation Alliance and the Marvel Universe-worthy HAIL Storm — it stands for Harvesting Academic Innovation for Learners — a coalition of academic innovation labs.
If history is a guide, the flashiest notions being developed in workshops in these places won’t get far. University campuses are like archaeological digs of innovations that didn’t fulfill their promises. Even though the biggest leap forward of the last few decades, for example — delivering courses online — appears to have lowered costs , the graduation rates of online higher education remain much lower than those of programs taught in person .
“One of the most important things we do here is disprove and dismantle ideas,” said William Zemp, chief strategy and innovation officer at Southern New Hampshire University.
“There’s so much white noise out there, you have to be sort of a myth buster.”
But some ambitious concepts are already being tested.
College by Subscription
One of these would transform the way students pay for higher education. Instead of enrolling, for example, they might subscribe to college; for a monthly fee, they could take whatever courses they want, when they want, with long-term access to advising and career help.
The Georgia Institute of Technology is one of the places mulling a subscription model, said Richard DeMillo, director of its Center for 21st Century Universities. It would include access to a worldwide network of mentors and advisers and “whatever someone needs to do to improve their professional situation or acquire a new skill or get feedback on how things are going.”
Boise State is already piloting this concept. Its Passport to Education costs $425 a month for six credit hours or $525 for nine in either of two online bachelor’s degree programs. That’s 30 percent cheaper than the in-state, in-person tuition.
Paying by the month encourages students to move faster through their educations, and most are projected to graduate in 18 months, Mr. Jones said. The subscription model has attracted 47 students so far, he said, with another 94 in the application process.
However they pay for it, future students could find other drastic changes in the way their educations are delivered.
Your Teacher Is a Robot
Georgia Tech has been experimenting with a virtual teaching assistant named Jill Watson, built on the Jeopardy-winning IBM Watson supercomputer platform. This A.I. answers questions in a discussion forum alongside human teaching assistants; students often can’t distinguish among them, their professor says. More Jill Watsons could help students get over hurdles they encounter in large or online courses. The university is working next on developing virtual tutors, which it says could be viable in two to five years .
S.N.H.U., in a collaboration with the education company Pearson, is testing A.I. grading. Barnes & Noble Education already has an A.I. writing tool called bartleby write , named for the clerk in the Herman Melville short story, that corrects grammar, punctuation and spelling, searches for plagiarism and helps create citations.
At Arizona State University, A.I. is being used to watch for signs that A.S.U. Online students might be struggling, and to alert their academic advisers.
“If we could catch early signals, we could go to them much earlier and say, ‘Hey you’re still in the window’ ” to pass, said Donna Kidwell, chief technology officer of the university’s digital teaching and learning lab, EdPlus.
Another harbinger of things to come sits on a hillside near the Hudson River in upstate New York, where an immersion lab with 15-foot walls and a 360-degree projection system transports Rensselaer Polytechnic Institute language students to China , virtually.
The students learn Mandarin Chinese by conversing with A.I. avatars that can recognize not only what they say but their gestures and expressions, all against a computer-generated backdrop of Chinese street markets, restaurants and other scenes.
Julian Wong, a mechanical engineering major in the first group of students to go through the program, “thought it would be cheesy.” In fact, he said, “It’s definitely more engaging, because you’re actively involved with what’s going on.”
Students in the immersion lab mastered Mandarin about twice as fast as their counterparts in conventional classrooms, said Shirley Ann Jackson, the president of Rensselaer.
Dr. Jackson, a physicist, was not surprised. The students enrolling in college now “grew up in a digital environment,” she said. “Why not use that to actually engage them?”
Slightly less sophisticated simulations are being used in schools of education, where trainee teachers practice coping with simulated schoolchildren. Engineering students at the University of Michigan use an augmented-reality track to test autonomous vehicles in simulated traffic.
A Transcript for Life
The way these kinds of learning get documented is also about to change. A race is underway to create a lifelong transcript.
Most academic transcripts omit work or military histories, internships, apprenticeships and other relevant experience. And course names such as Biology 301 or Business 102 reveal little about what students have actually learned.
“The learner, the learning provider and the employer all are speaking different languages that don’t interconnect,” said Michelle Weise, chief innovation officer at the Strada Institute for the Future of Work.
A proposed solution: the “interoperable learning record,” or I.L.R. (proof that, even in the future, higher education will be rife with acronyms and jargon).
The I.L.R. would list the specific skills that people have learned — customer service, say, or project management — as opposed to which courses they passed and majors they declared. And it would include other life experiences they accumulated.
This “digital trail” would remain in the learner’s control to share with prospective employers and make it easier for a student to transfer academic credits earned at one institution to another.
American universities, colleges and work force training programs are now awarding at least 738,428 unique credentials , according to a September analysis by a nonprofit organization called Credential Engine, which has taken on the task of translating these into a standardized registry of skills.
Unlike transcripts, I.L.R.s could work in two directions. Not only could prospective employees use them to look for jobs requiring the skills they have; employers could comb through them to find prospective hires with the skills they need.
“We’re trying to live inside this whole preindustrial design and figure out how we interface with technology to take it further,” said Dr. Kidwell of Arizona State. “Everybody is wrangling with trying to figure out which of these experiments are really going to work.”
This story was produced in collaboration with The Hechinger Report , a nonprofit, independent news organization focused on inequality and innovation in education.
New global data reveal education technology’s impact on learning
The promise of technology in the classroom is great: enabling personalized, mastery-based learning; saving teacher time; and equipping students with the digital skills they will need for 21st-century careers. Indeed, controlled pilot studies have shown meaningful improvements in student outcomes through personalized blended learning. 1 John F. Pane et al., “How does personalized learning affect student achievement?,” RAND Corporation, 2017, rand.org. During this time of school shutdowns and remote learning , education technology has become a lifeline for the continuation of learning.
As school systems begin to prepare for a return to the classroom , many are asking whether education technology should play a greater role in student learning beyond the immediate crisis and what that might look like. To help inform the answer to that question, this article analyzes one important data set: the 2018 Programme for International Student Assessment (PISA), published in December 2019 by the Organisation for Economic Co-operation and Development (OECD).
Every three years, the OECD uses PISA to test 15-year-olds around the world on math, reading, and science. What makes these tests so powerful is that they go beyond the numbers, asking students, principals, teachers, and parents a series of questions about their attitudes, behaviors, and resources. An optional student survey on information and communications technology (ICT) asks specifically about technology use—in the classroom, for homework, and more broadly.
In 2018, more than 340,000 students in 51 countries took the ICT survey, providing a rich data set for analyzing key questions about technology use in schools. How much is technology being used in schools? Which technologies are having a positive impact on student outcomes? What is the optimal amount of time to spend using devices in the classroom and for homework? How does this vary across different countries and regions?
From other studies we know that how education technology is used, and how it is embedded in the learning experience, is critical to its effectiveness. This data is focused on extent and intensity of use, not the pedagogical context of each classroom. It cannot therefore answer questions on the eventual potential of education technology—but it can powerfully tell us the extent to which that potential is being realized today in classrooms around the world.
Five key findings from the latest results help answer these questions and suggest potential links between technology and student outcomes:
- The type of device matters—some are associated with worse student outcomes.
- Geography matters—technology is associated with higher student outcomes in the United States than in other regions.
- Who is using the technology matters—technology in the hands of teachers is associated with higher scores than technology in the hands of students.
- Intensity matters—students who use technology intensely or not at all perform better than those with moderate use.
- A school system’s current performance level matters—in lower-performing school systems, technology is associated with worse results.
This analysis covers only one source of data, and it should be interpreted with care alongside other relevant studies. Nonetheless, the 2018 PISA results suggest that systems aiming to improve student outcomes should take a more nuanced and cautious approach to deploying technology once students return to the classroom. It is not enough add devices to the classroom, check the box, and hope for the best.
What can we learn from the latest PISA results?
How will the use, and effectiveness, of technology change post-covid-19.
The PISA assessment was carried out in 2018 and published in December 2019. Since its publication, schools and students globally have been quite suddenly thrust into far greater reliance on technology. Use of online-learning websites and adaptive software has expanded dramatically. Khan Academy has experienced a 250 percent surge in traffic; smaller sites have seen traffic grow fivefold or more. Hundreds of thousands of teachers have been thrown into the deep end, learning to use new platforms, software, and systems. No one is arguing that the rapid cobbling together of remote learning under extreme time pressure represents best-practice use of education technology. Nonetheless, a vast experiment is underway, and innovations often emerge in times of crisis. At this point, it is unclear whether this represents the beginning of a new wave of more widespread and more effective technology use in the classroom or a temporary blip that will fade once students and teachers return to in-person instruction. It is possible that a combination of software improvements, teacher capability building, and student familiarity will fundamentally change the effectiveness of education technology in improving student outcomes. It is also possible that our findings will continue to hold true and technology in the classroom will continue to be a mixed blessing. It is therefore critical that ongoing research efforts track what is working and for whom and, just as important, what is not. These answers will inform the project of reimagining a better education for all students in the aftermath of COVID-19.
PISA data have their limitations. First, these data relate to high-school students, and findings may not be applicable in elementary schools or postsecondary institutions. Second, these are single-point observational data, not longitudinal experimental data, which means that any links between technology and results should be interpreted as correlation rather than causation. Third, the outcomes measured are math, science, and reading test results, so our analysis cannot assess important soft skills and nonacademic outcomes.
It is also worth noting that technology for learning has implications beyond direct student outcomes, both positive and negative. PISA cannot address these broader issues, and neither does this paper.
But PISA results, which we’ve broken down into five key findings, can still provide powerful insights. The assessment strives to measure the understanding and application of ideas, rather than the retention of facts derived from rote memorization, and the broad geographic coverage and sample size help elucidate the reality of what is happening on the ground.
Finding 1: The type of device matters
The evidence suggests that some devices have more impact than others on outcomes (Exhibit 1). Controlling for student socioeconomic status, school type, and location, 2 Specifically, we control for a composite indicator for economic, social, and cultural status (ESCS) derived from questions about general wealth, home possessions, parental education, and parental occupation; for school type “Is your school a public or a private school” (SC013); and for school location (SC001) where the options are a village, hamlet or rural area (fewer than 3,000 people), a small town (3,000 to about 15,000 people), a town (15,000 to about 100,000 people), a city (100,000 to about 1,000,000 people), and a large city (with more than 1,000,000 people). the use of data projectors 3 A projector is any device that projects computer output, slides, or other information onto a screen in the classroom. and internet-connected computers in the classroom is correlated with nearly a grade-level-better performance on the PISA assessment (assuming approximately 40 PISA points to every grade level). 4 Students were specifically asked (IC009), “Are any of these devices available for you to use at school?,” with the choices being “Yes, and I use it,” “Yes, but I don’t use it,” and “No.” We compared the results for students who have access to and use each device with those who do not have access. The full text for each device in our chart was as follows: Data projector, eg, for slide presentations; Internet-connected school computers; Desktop computer; Interactive whiteboard, eg, SmartBoard; Portable laptop or notebook; and Tablet computer, eg, iPad, BlackBerry PlayBook.
On the other hand, students who use laptops and tablets in the classroom have worse results than those who do not. For laptops, the impact of technology varies by subject; students who use laptops score five points lower on the PISA math assessment, but the impact on science and reading scores is not statistically significant. For tablets, the picture is clearer—in every subject, students who use tablets in the classroom perform a half-grade level worse than those who do not.
Some technologies are more neutral. At the global level, there is no statistically significant difference between students who use desktop computers and interactive whiteboards in the classroom and those who do not.
Finding 2: Geography matters
Looking more closely at the reading results, which were the focus of the 2018 assessment, 5 PISA rotates between focusing on reading, science, and math. The 2018 assessment focused on reading. This means that the total testing time was two hours for each student, of which one hour was reading focused. we can see that the relationship between technology and outcomes varies widely by country and region (Exhibit 2). For example, in all regions except the United States (representing North America), 6 The United States is the only country that took the ICT Familiarity Questionnaire survey in North America; thus, we are comparing it as a country with the other regions. students who use laptops in the classroom score between five and 12 PISA points lower than students who do not use laptops. In the United States, students who use laptops score 17 PISA points higher than those who do not. It seems that US students and teachers are doing something different with their laptops than those in other regions. Perhaps this difference is related to learning curves that develop as teachers and students learn how to get the most out of devices. A proxy to assess this learning curve could be penetration—71 percent of US students claim to be using laptops in the classroom, compared with an average of 37 percent globally. 7 The rate of use excludes nulls. The United States measures higher than any other region in laptop use by students in the classroom. US = 71 percent, Asia = 40 percent, EU = 35 percent, Latin America = 31 percent, MENA = 21 percent, Non-EU Europe = 41 percent. We observe a similar pattern with interactive whiteboards in non-EU Europe. In every other region, interactive whiteboards seem to be hurting results, but in non-EU Europe they are associated with a lift of 21 PISA points, a total that represents a half-year of learning. In this case, however, penetration is not significantly higher than in other developed regions.
Finding 3: It matters whether technology is in the hands of teachers or students
The survey asks students whether the teacher, student, or both were using technology. Globally, the best results in reading occur when only the teacher is using the device, with some benefit in science when both teacher and students use digital devices (Exhibit 3). Exclusive use of the device by students is associated with significantly lower outcomes everywhere. The pattern is similar for science and math.
Again, the regional differences are instructive. Looking again at reading, we note that US students are getting significant lift (three-quarters of a year of learning) from either just teachers or teachers and students using devices, while students alone using a device score significantly lower (half a year of learning) than students who do not use devices at all. Exclusive use of devices by the teacher is associated with better outcomes in Europe too, though the size of the effect is smaller.
Finding 4: Intensity of use matters
PISA also asked students about intensity of use—how much time they spend on devices, 8 PISA rotates between focusing on reading, science, and math. The 2018 assessment focused on reading. This means that the total testing time was two hours for each student, of which one hour was reading focused. both in the classroom and for homework. The results are stark: students who either shun technology altogether or use it intensely are doing better, with those in the middle flailing (Exhibit 4).
The regional data show a dramatic picture. In the classroom, the optimal amount of time to spend on devices is either “none at all” or “greater than 60 minutes” per subject per week in every region and every subject (this is the amount of time associated with the highest student outcomes, controlling for student socioeconomic status, school type, and location). In no region is a moderate amount of time (1–30 minutes or 31–60 minutes) associated with higher student outcomes. There are important differences across subjects and regions. In math, the optimal amount of time is “none at all” in every region. 9 The United States is the only country that took the ICT Familiarity Questionnaire survey in North America; thus, we are comparing it as a country with the other regions. In reading and science, however, the optimal amount of time is greater than 60 minutes for some regions: Asia and the United States for reading, and the United States and non-EU Europe for science.
The pattern for using devices for homework is slightly less clear cut. Students in Asia, the Middle East and North Africa (MENA), and non-EU Europe score highest when they spend “no time at all” on devices for their homework, while students spending a moderate amount of time (1–60 minutes) score best in Latin America and the European Union. Finally, students in the United States who spend greater than 60 minutes are getting the best outcomes.
One interpretation of these data is that students need to get a certain familiarity with technology before they can really start using it to learn. Think of typing an essay, for example. When students who mostly write by hand set out to type an essay, their attention will be focused on the typing rather than the essay content. A competent touch typist, however, will get significant productivity gains by typing rather than handwriting.
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Finding 5: the school systems’ overall performance level matters.
Diving deeper into the reading outcomes, which were the focus of the 2018 assessment, we can see the magnitude of the impact of device use in the classroom. In Asia, Latin America, and Europe, students who spend any time on devices in their literacy and language arts classrooms perform about a half-grade level below those who spend none at all. In MENA, they perform more than a full grade level lower. In the United States, by contrast, more than an hour of device use in the classroom is associated with a lift of 17 PISA points, almost a half-year of learning improvement (Exhibit 5).
At the country level, we see that those who are on what we would call the “poor-to-fair” stage of the school-system journey 10 Michael Barber, Chinezi Chijoke, and Mona Mourshed, “ How the world’s most improved school systems keep getting better ,” November 2010. have the worst relationships between technology use and outcomes. For every poor-to-fair system taking the survey, the amount of time on devices in the classroom associated with the highest student scores is zero minutes. Good and great systems are much more mixed. Students in some very highly performing systems (for example, Estonia and Chinese Taipei) perform highest with no device use, but students in other systems (for example, Japan, the United States, and Australia) are getting the best scores with over an hour of use per week in their literacy and language arts classrooms (Exhibit 6). These data suggest that multiple approaches are effective for good-to-great systems, but poor-to-fair systems—which are not well equipped to use devices in the classroom—may need to rethink whether technology is the best use of their resources.
What are the implications for students, teachers, and systems?
Looking across all these results, we can say that the relationship between technology and outcomes in classrooms today is mixed, with variation by device, how that device is used, and geography. Our data do not permit us to draw strong causal conclusions, but this section offers a few hypotheses, informed by existing literature and our own work with school systems, that could explain these results.
First, technology must be used correctly to be effective. Our experience in the field has taught us that it is not enough to “add technology” as if it were the missing, magic ingredient. The use of tech must start with learning goals, and software selection must be based on and integrated with the curriculum. Teachers need support to adapt lesson plans to optimize the use of technology, and teachers should be using the technology themselves or in partnership with students, rather than leaving students alone with devices. These lessons hold true regardless of geography. Another ICT survey question asked principals about schools’ capacity using digital devices. Globally, students performed better in schools where there were sufficient numbers of devices connected to fast internet service; where they had adequate software and online support platforms; and where teachers had the skills, professional development, and time to integrate digital devices in instruction. This was true even accounting for student socioeconomic status, school type, and location.
COVID-19 and student learning in the United States: The hurt could last a lifetime
Second, technology must be matched to the instructional environment and context. One of the most striking findings in the latest PISA assessment is the extent to which technology has had a different impact on student outcomes in different geographies. This corroborates the findings of our 2010 report, How the world’s most improved school systems keep getting better . Those findings demonstrated that different sets of interventions were needed at different stages of the school-system reform journey, from poor-to-fair to good-to-great to excellent. In poor-to-fair systems, limited resources and teacher capabilities as well as poor infrastructure and internet bandwidth are likely to limit the benefits of student-based technology. Our previous work suggests that more prescriptive, teacher-based approaches and technologies (notably data projectors) are more likely to be effective in this context. For example, social enterprise Bridge International Academies equips teachers across several African countries with scripted lesson plans using e-readers. In general, these systems would likely be better off investing in teacher coaching than in a laptop per child. For administrators in good-to-great systems, the decision is harder, as technology has quite different impacts across different high-performing systems.
Third, technology involves a learning curve at both the system and student levels. It is no accident that the systems in which the use of education technology is more mature are getting more positive impact from tech in the classroom. The United States stands out as the country with the most mature set of education-technology products, and its scale enables companies to create software that is integrated with curricula. 11 Common Core State Standards sought to establish consistent educational standards across the United States. While these have not been adopted in all states, they cover enough states to provide continuity and consistency for software and curriculum developers. A similar effect also appears to operate at the student level; those who dabble in tech may be spending their time learning the tech rather than using the tech to learn. This learning curve needs to be built into technology-reform programs.
Taken together, these results suggest that systems that take a comprehensive, data-informed approach may achieve learning gains from thoughtful use of technology in the classroom. The best results come when significant effort is put into ensuring that devices and infrastructure are fit for purpose (fast enough internet service, for example), that software is effective and integrated with curricula, that teachers are trained and given time to rethink lesson plans integrating technology, that students have enough interaction with tech to use it effectively, and that technology strategy is cognizant of the system’s position on the school-system reform journey. Online learning and education technology are currently providing an invaluable service by enabling continued learning over the course of the pandemic; this does not mean that they should be accepted uncritically as students return to the classroom.
Jake Bryant is an associate partner in McKinsey’s Washington, DC, office; Felipe Child is a partner in the Bogotá office; Emma Dorn is the global Education Practice manager in the Silicon Valley office; and Stephen Hall is an associate partner in the Dubai office.
The authors wish to thank Fernanda Alcala, Sujatha Duraikkannan, and Samuel Huang for their contributions to this article.
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