Roots of the Failure of School Reform to Resolve Social Problems — David Labaree on What Schools Can’t Do (Part 2)

In the concluding section of this week’s blog post, David Labaree succinctly sums up some of the key factors that explain why school reform efforts in the US often fail to achieve their ambitious goals. In part one, Labaree discussed why US schools are so often asked to pursue goals — like support economic productivity, foster social mobility, and reduce inequality — that they have never been equipped to achieve. Labaree is an Emeritus Professor at the Stanford University Graduate School of Education and one of the foremost experts on the history of education and educational reform in the US. As Labaree explains, this post was originally published in the Swiss journal Zeitschrift für Pädagogische Historiographie and his book, Someone Has to Fail.  Labaree added an introduction (and cartoons) and posted this on his blog on July 9, 2026.

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Roots of the Failure of School Reform to Resolve Social Problems

In closing, let me summarize the reasons for the continuing failure of school reform in the U.S.

The Tensions Among School Goals:  One reason for the failure of reform to realize the social goals expressed in it is that these goals reflect the core tensions within a liberal democracy, which push both school and society in conflicting directions.  One of those tensions is between the demands of democratic politics and the demands of capitalist markets.  A related issue is the requirement that society be able to meet its collective needs while simultaneously guaranteeing the liberty of individuals to pursue their own interests.  As we have seen, these tensions cannot be resolved one way or the other if we are going to remain a liberal democracy, so schools will inevitably fail at maximizing any of these goals.  The result is going to be a muddled compromise rather than a clear cut victory in meeting particular expectations.  The apparently dysfunctional outcomes of the educational system, therefore, are not necessarily the result of bad planning, deception, or political cynicism; they are an institutional expression of the contradictions in the liberal democratic mind.

The Tendency Toward Organizational Conservatism:  There is also another layer of impediment that lies between social goals and their fulfillment via education, and that is the tension between education’s social goals and its organizational practices.  Schools gain their origins from social goals, which they dutifully express in an institutional form, as happened with the construction of the common school system.  This results in the development of school organization, curriculums, pedagogies, professional roles, and a complex set of occupational and organizational interests.  At this more advanced stage, schools and educators are no longer simply the media for realizing social aspirations; they become major actors in the story.  As such, they shape what happens in education in light of their own needs and interests, organizational patterns,  and professional norms and practices.  And this then becomes a major issue in educational reform.  Such reforms are what happens after schooling is already in motion organizationally, when society seeks to assign new ideals to education or revive old ones that have fallen into disuse, thus initiating an effort to transform the institution toward the pursuit of different ends.  But at that point society is no longer able simply to project its values onto the institution it created to express these values; instead it must negotiate an interaction with an ongoing enterprise.  As a result, reform has to change both the values embedded in education and the formal structure itself, which may well resist.  As I have shown elsewhere, three characteristics of the American school system – loose coupling, weak instructional control, and teacher autonomy – have made this system remarkably effective at blocking reforms from reaching the classroom.

Reformer Arrogance:  Another problem that leads to the failure of school reform is simple arrogance.  School reformers spin out an abstract vision of what school and society should be, and then they try to bring reality in line with the vision.  But this abstract reformist grid doesn’t map comfortably onto the parochial and idiosyncratic ecology of the individual classroom.  Trying to push too hard to make the classroom fit the grid may destroy the ecology of learning there; and adapting the grid enough to make it workable in the classroom may change the reform to the point that its original aims are lost.  Reformers are loath to give up their aims in the service of making the reform acceptable to teachers, so they tend to plow ahead in search of ways to get around the obstacles.  If they can’t make change in cooperation with teachers, then they will have to so in spite of them.  They see a crying need to fix a problem through school reform, and they have developed a theory for how to do this, which looks just great on paper.  Standing in the state capital or the university, they are far from the practical realities of the classroom, and they tend to be impatient with demands that they should respect the complexity of the settings in which they are trying to intervene.

The Marginality of School Reform to School Change:  Finally, we need to remind ourselves that school reform has always been only a small part of the broader process of school change.  Reform movements are deliberate efforts by groups of people to change schools in a direction they value and to resolve a social problem that concerns them.  We measure the success of these movements by the degree to which the outcomes match the intentions of the reformers.  But there’s another player in the school change game, and that’s the market.  By this I mean the accumulated actions of educational consumers who are pursuing their own interests through the schooling of their children.  From the colonial days, when the expressed purpose of schooling was to support the one true faith, consumers were pursuing literacy and numeracy for reasons that had nothing to do with religion and a lot to do with enhancing their ability to function in a market society.

That very personal and practical dimension of education was there from the beginning, even though no one wanted to talk about it, much less launch a reform movement in its name.  And this individual dimension of schooling has only expanded its scope over the years, becoming larger in the late 19th century and then dominant in the 20th century, as increasingly educational credentials became the ticket of admission for the better jobs.  The fact that public schools have long been creatures of politics – established, funded, and governed through the medium of a democratic process – means that they have been under unrelenting pressure to meet consumer demand for the kind of schooling that will help individuals move up, stay up, or at least not drop down in their position in the social order.  This pressure is exerted through individual consumer actions, such as by attending school or not, going to this school not that one, enrolling in this program not some other program.  It is also exerted by political actions, such as by supporting expansion of educational opportunity and preserving educational advantage in the midst of wide access.

These actions by consumers and voters have brought about significant changes in the school system, even though these changes have not been the aim of any of the consumers themselves.  They have not been acting as reformers with a social cause but as individuals pursuing their own interests through education, so the changes they have produced in schooling by and large have been inadvertent.  Yet these unintended effects of consumer action have often derailed or redirected the intended effects of school reformers.  They created the comprehensive high school, dethroned social efficiency, pushed vocational education to the margins, and blocked the attack on de facto segregation.  Educational consumers may well keep the current school standards movement from meeting its goals if they feel that standards, testing, and accountability are threatening educational access and educational advantage.  They may also pose an impediment to the school choice movement, even though it is being carried out explicitly in their name.  For consumers may feel more comfortable tinkering with the system they know than in taking the chance that blowing up this system might produce something that is less suited to serving their needs.  In the American system of education, it seems, the consumer – not the reformer – has long been king.

What Schools Can’t Do — David Labaree (Part 1) 

In this week’s post, David Labaree explores why schools are so often asked to pursue goals — like support economic productivity, foster social mobility, and reduce inequality — that they have never been equipped to achieve. Labaree is an Emeritus Professor at the Stanford University Graduate School of Education and one of the foremost experts on the history of education and educational reform in the US. As Labaree explains, this post was originally published in the Swiss journal Zeitschrift für Pädagogische Historiographie and his book, Someone Has to Fail.  Labaree added an introduction (and cartoons) and posted this on his blog on July 9, 2026. Labaree’s conclusion to the post will be published next week. 

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This post is the text of a lecture I gave in 2009 at the University of Berne.  It was originally published in the Swiss journal Zeitschrift für Pädagogische Historiographie and then found its way into my 2010 book, Someone Has to Fail.  Here is the link to the first published version.

It’s about a longstanding problem in American educational policy:  We ask schools to pursue goals that are beyond their capabilities.  Schools are simply not very good at a lot of things we ask them to do.  They can’t promote equality, they can’t end poverty, they can’t create good jobs, they can’t drive economic growth, they can’t promote public health.  Yet we expect them to do all this heavy lifting for us.

Part of the story is about why schools aren’t good at these things.  Another is why we keep giving them such assignments anyway.  The answer to the second, I suggest, is that we pass off on schools social problems that we are unwilling to accomplish through the political process, where the capability for success actually resides.  Instead of addressing these problems directly through political action, we foist them off on schools and then blame them for continually falling short of the desired goal.  Herein lies the reason why school reform has been such steady work.  Read and weep.

Even if you’ve read this before, don’t miss the cartoons that I tucked into the text this time.  They’re worth a post all by themselves.

Americans have a long history of pinning their hopes on education as the way to realize compelling social ideals and solve challenging social problems.  We want schools to promote civic virtue, economic productivity, and social mobility; to alleviate inequalities in race, class, and gender; to improve health, reduce crime, and protect the environment.  So we assign these social missions to schools, and educators gamely accept responsibility for carrying them out.  When the school system inevitably falls far short of these goals, we initiate a wave of school reform to realign the institution with its social goals and ramp up its effectiveness in attaining them.  The result, as one pair of scholars has put it, is that educational reform in the U.S. is “steady work.”  In this lecture, I want to tell a story:  What history tells us about what schools cannot do.

At its heart, this is a story grounded in paradox.  On the one hand, American schooling has been an extraordinary success.  It started as a small and peripheral enterprise in the 18th century and grew into a massive institution at the center of American society in the 21st, where it draws the lion’s share of the state budget and a quarter of the lives of citizens.  Central to its institutional success has been its ability to embrace and embody the social goals that have been imposed upon it.  Yet, in spite of continually recurring waves of school reform, education in the U.S. has been remarkably unsuccessful at implementing these goals in the classroom practices of education and at realizing these goals in the social outcomes of education.

America, I suggest, suffers from a school syndrome.  We have set our school system up for failure by asking it to fix all of our most pressing social problems, which we are unwilling to address more directly through political action rather than educational gesture.  Then we blame the system when it fails.  Both as a society and as individuals, we vest our greatest hopes in an institution that is manifestly unsuited to realizing them.  In part the system’s failure is the result of a tension between our shifting social aims for education and the system’s own organizational momentum.  We created the system to solve a critical social problem in the early days of the American republic, and its success in dealing with this problem fooled us into thinking that we could redirect the system toward new problems as time passed.  But the school system has a mind of its own, and trying to change its direction is like trying to do a U-turn with a battleship.

Today I will explore the failure of school reform to realize the central social goals that have driven it over the years.  And at the end I explore the roots of schooling’s failure in its role as an agent of social reform.

The social missions of schooling in liberal democracies arise from the tensions that are inherent in such societies.  One of these tensions is between the demands of democratic politics and the demands of capitalist markets.  A related issue is the requirement that society be able to meet its collective needs while simultaneously guaranteeing the liberty of individuals to pursue their own interests.  In the American setting, these tensions have played out through the politics of education in the form of a struggle among three major social goals for the educational system.  One goal is democratic equality, which sees education as a mechanism for producing capable citizens.  Another is social efficiency, which sees education as a mechanism for developing productive workers.  A third is social mobility, which sees education as a mechanism for individuals to reinforce or enhance their social position.

Democratic equality represents the political side of our liberal democratic values, focusing on the role of education in building a nation, forming a republican community, and providing citizens with the wide range of capabilities required to take part in democratic decision-making.  The other two goals represent the market side of liberal democracy.  Social efficiency captures the perspective of employers and taxpayers, who are concerned about the role of education in producing the job skills (human capital) that are required by the modern economy and that are seen as essential for economic growth and social prosperity.  From this angle the issue is for education to provide for the full range of productive skills and forms of knowledge required in the complex job structure of modern capitalism.  Social mobility captures the perspective of educational consumers and prospective employees, who are concerned about the role of educational credentials in signaling to the market which individuals should get the jobs with the most power, money, and prestige.

The collectivist side of liberal democracy is expressed by a combination of democratic equality and social efficiency.  Both aim at having education provide broad social benefits, with both conceiving of education as a public good.  Investing in the political capital of the citizenry and the human capital of the workforce benefits everyone in society, including those families who do not have children in school.  In contrast, the social mobility goal represents the individualist side of liberal democracy.  From this perspective, education is a private good, which benefits only the student who receives educational services and owns the resulting diplomas.  Its primary function is to provide educational consumers with privileged access to higher level jobs in the competition with other prospective employees.

So let me look at how well – or rather, how poorly – American schools have done at accomplishing these three social missions.

Democratic Equality

School systems around the world have been more effective at accomplishing their political mission than either their efficiency or mobility missions.  At the formative stage in the construction of a nation state, virtually anywhere in the world, education seems to have an important role to play.  The key contribution in this regard is that schooling helps form a national citizenry out of a collection of local identities.  One country after another developed a system of universal education at the point when it was trying to transform itself into a modern state, populated by citizens rather than subjects, with a common culture and a shared national identity.  For the U.S. in the early 19th century, the key problem during this transitional period was how to establish a modern social order based on exchange relations and democratic authority out of the remnants of a traditional social order based on patriarchal relations and feudal authority.  A system of public education helps to make this transition possible primarily by bringing a disparate group of youths in the community together under one roof and exposing them to a common curriculum and a common set of social experiences.  The result was to instill in students social norms that allowed them to emerge as self-regulating actors in the free market while still remaining good citizens and good Christians.  Creating such cultural communities is one of the few things that schools can consistently do well.

So the evidence shows that at the formative stage, school systems in the U.S. and elsewhere have been remarkably effective in promoting citizenship and forming a new social order.  This is quite an accomplishment, which more than justifies the huge investment in constructing these systems.  And building on this capacity for forming community, schools have continued to play an important role as the agent for incorporating newcomers.  This has been particularly important in an immigrant society like the United States, where – from the Irish and Germans in the mid-19th century to the Mexicans and South Asians in the early 21st century – schools have been the central mechanism for integrating foreigners into the American experience.

But the ability of schooling to promote democratic equality in the U.S. has had little to do with learning, it has faded over time, and it has been increasingly undermined by counter tendencies toward inequality.  First, note that when schools have been effective at community building, this had little to with the content of the curriculum or the nature of classroom teaching.  What was important was that schools provided a common experience for all students.  What they actually learned in school was irrelevant as long as they all were exposed to the same material.  It could have been anything.  It was the form of schooling more than its content that helped establish and preserve the American republic.

Second, the importance of schooling in forming community has declined over time.  The common school system was critically important in the formative days of the American republic; but once the country’s continued existence was no longer in doubt, the role of the system grew less critical.  As a result, the more recent ways in which schools have come to promote citizenship have been more formalistic than substantive.  This is now embedded in classes on American history, speeches at school assemblies, pilgrim pageants around Thanksgiving, presidential portraits on classroom walls, and playing the national anthem before football games.  What had been the system’s foremost rationale for existence has now retreated into the background of a system more concerned with other issues.

Third, and most important, however, the role of schools in promoting democratic equality has declined because schools have simultaneously been aggressively promoting social inequality.  One of the recurring themes of my book is that every move by American schools in the direction of equality has been countered by a strong move in the opposite direction.  When we created a common school system in the early 19th century, we also created a high school system to distinguish middle class students from the rest.  When we expanded access to the high school at the start of the 20th century, we also created a system for tracking students within the school and opened the gates for middle class enrollment in college.  When we expanded access to college in the mid-20th century, we funneled new students into the lower tiers of the system and encouraged middle class students to pursue graduate study.  The American school system is at least as much about social difference as about social equality.  In fact, as the system has developed, the idea of equality has become more formalistic, focused primarily on the notion of broad access to education at a certain level, while the idea of inequality has become more substantive, embodied in starkly different educational and social trajectories.

Social Efficiency

In the current politics of education, the goal of social efficiency plays a prominent role.  One of the central beliefs of contemporary economics, international development, and educational policy is that education is the key to economic development as a valuable investment in human capital.  Today it is hard to find a political speech, reform document, or opinion piece about education that does not include a paean to the critical role that education plays in developing human capital and spurring economic growth – and the need to reform schools in order to fix what’s wrong with the economy.

Economists Claudia Goldin and Lawrence Katz have made a strong argument for the human capital vision of education in their recent book, The Race Between Education and Technology.  They argue that the extraordinary expansion of the American economy in the 20th century was to a large degree the result of an equally extraordinary expansion in educational enrollments during this period.  It is no coincidence, they say, that what turned out to be the American Century economically was also the Human Capital Century for the U.S.

The numbers are indeed staggering.  In the United States education levels rose dramatically for most of the 20th century.  For those born between 1876 and 1951, the average number of years of schooling rose a total of 6 years, which is an increase of 0.8 years per decade.  This means that the average education level of the entire U.S. population rose from less than 8 years of grade school to two years of college in only 75 years.  The authors estimate that the growth in education in the U.S. accounted for between 12 and 17 percent of the growth in economic productivity across the 20th century, with the average educational contribution at 13.5 percent.  Put another way, they argue that increased education alone accounted for economic growth of about one-third of one percent per year from 1915-2005.

One problem with this claim, however, is that the size of the human capital effect they show is relatively small.  On average they estimate that the growth in educational attainment accounted for less that 14 percent of the growth in economic productivity over the course of the 20th century.  That’s not negligible but it’s also not overwhelming.  This wouldn’t be a concern if education were a modest investment drawing a modest return, because every little bit helps when it comes to economic growth.  But that’s clearly not the case.  Education has long been the largest single expenditure of American state and local governments, which over the course of the 20th century devoured about 30 percent of their total budgets.  In 1995 this came to almost $400 billion in direct payments for elementary, secondary, and higher education.  In short, as costly as education is, it would seem that its economic benefits would need to be more substantial than they are in order to justify these expenses as a solid investment in the nation’s wealth instead of a large drain on this wealth.

Another problem is that it is hard to establish that in fact education was the cause and economy the effect in this story.  The authors make clear that the growth in high school and college enrollments both exceeded and preceded demand for such workers from the economy.  Employers were not begging high schools to produce more graduates in order to meet the needs for greater skill in the workplace; instead they were taking advantage of a situation in which large numbers of educated workers were available, and could be hired without a large wage premium, for positions that in the past had not required this level of education.  So why not hire them?  And once these high school graduates were on the job, the employers may have found them useful to have around (maybe they required less training), so employers began to express a preference for high school graduates in future hiring.  But just because the workforce was becoming more educated didn’t mean that the presence of educated workers was the source of increases in economic productivity.  It could just as easily have been the other way around.

Producing a large increase in high school graduates was enormously expensive, especially considering that the supply of these graduates was much greater than the economic demand for them.  But strong economic growth provided enough of a fiscal surplus that state and local governments were able afford to do so.  In short, it makes sense to think that it was economic growth that made educational growth possible.  We expanded high school because we could afford to.  And we wanted to do so not because we thought it would provide social benefits by improving the economy but instead because we hoped it would provide us with personal benefits.  The authors point out that the growth of high school enrollments was not the result of a reform movement.  Instead, the demand for high school came from educational consumers.  Middle class families saw high school and college as a way to gain an edge – or keep their already existing edge – in the competition for good jobs.  And working class families saw high school as a way to provide their children with the possibility of a better life than their own.  The demand came from the bottom up not the top down.  Administrative progressives later capitalized on the growth of the high school by trying to harness it for their own social efficiency agenda, as expressed in the 1918 Cardinal Principles report.  But by then the process of high school expansion was already well under way, with little help from them.

The major accomplishment of the American school system was not necessarily that it provided education but that it provided access.  The system may or may not have been effective at teaching students the kinds of skills and knowledge that would economically useful, but it was quite effective at inviting students into the schools and keeping them there for an extended period of time.  Early in their book, Goldin and Katz identify what they consider to be the primary “virtues” of the American educational system as it developed before the civil war and continued into the 20th century.  In effect, these virtues of the system all revolve around its broad accessibility.  They include:  “public provision by small, fiscally independent districts; public funding; secular control; gender neutrality; open access; and a forgiving system.”

Note that none of these virtues of the American school system speaks to learning the curriculum.  Instead all have to do with the form of the system, in particular its accessibility and flexibility.  I thoroughly agree.  But for the human capital argument that Goldin and Katz are trying to make, these virtues of the system pose a problem.  How was the system able to provide graduates with the skills needed to spur economic growth when the system’s primary claim to fame was that it invited everyone in and then was reluctant to penalize anyone for failing to learn?  In effect, the system’s greatest strength was its low academic standards.  If it had screened students more carefully on the way in and graded them more scrupulously on their academic achievement, high school and college enrollments and graduation rates never would have expanded so rapidly and we would all be worse off.  This brings us to the third goal of education, social mobility.

Social Mobility

In liberal democracies in general, and in the United States in particular, hope springs eternal that expanding educational opportunity will increase social mobility and social equality.  This has been a prime factor in the rhetoric of the American educational reform movements for desegregation, standards, and choice.  But the evidence to support that hope simply doesn’t exist.  The problem is this:  In the way that education interacts with social mobility and social equality, both of these measures of social position are purely relative.  Both are cases of what social scientists call a zero sum game:  A + B = 0.  If A goes up then B must go down in order to keep the sum at zero.  If one person gets ahead of someone else on the social ladder, then that other person has fallen behind.  And if the social differences between two people become more equal, then the increase in social advantage for one person means the decrease in social advantage for the other.  Symmetry is built into both measures.

Although social equality is inherently relative, it is possible to think of social mobility in terms of absolute rather than relative position.  During the 20th century in the U.S., the proportion of agricultural, manufacturing, and other blue collar workers declined while the proportion of clerical, managerial, professional, and other white collar workers rose.  At the same time the proportion of  people with a grade school education declined while the proportion with more advanced education rose.  So large numbers of families had the experience in which parents were blue collar and their children white collar, parents had modest education and their children had more education.  In absolute terms, therefore, social mobility from blue collar to white collar work during this period was substantial, as children not only moved up in job classification compared to their parents but also gained higher pay and a higher standard of living.  And this social mobility was closely related to a substantial rise in education levels.  This was a great success story, and it is understandable why those involved would attribute these social gains to education.  For large numbers of Americans, it seemed to confirm the adage: to get a good job, get a good education.  Schooling seemed to help people move up the ladder.

At the individual level, this perception was quite correct.  In the 20th century, it became the norm for employers to set minimum educational qualifications for jobs, and in general the amount of education required rose as one moved up the occupational ladder.  Youths overall had a strong incentive to pursue more education in order to reap social and economic rewards.  Economic studies regularly demonstrate a varying but substantial return on a family’s investment in education for their children.  For example, one estimate shows that males between 1914 and 2005 earned a premium in lifetime earnings for every year of college that ranged from 8 to 14 percent.  That makes education a great investment for families – better than the stock market, which had an average annual return of about 8 percent during the same period.

What is true for some individuals, however, is not necessarily true for society as a whole.  As I explained about social efficiency, it is not clear that increasing the number of college graduates leads to an increase in the number of higher-level jobs for these graduates to fill.  To me it seems more plausible to look at the connection between education and jobs this way:  The economy creates jobs, and education is the way we allocate people to those jobs.  Candidates with more education qualify for better jobs.  What this means is that social mobility becomes a relative thing, which depends on the number of individuals with a particular level of education at a given time and the number of positions requiring this level of education that are available at that same time.  If there are more positions than candidates at that level, all of the qualified candidates get the jobs along with some who have lower qualifications; but if there are more candidates than positions, then some qualified applicants will end up in lower level positions.  So the economic value of education varies according to the job market.  An increase in education without a corresponding increase in higher level jobs in the economy will reduce the value of a degree in the market for educational credentials.

This poses a problem for the chances of social mobility between parents and children.  After all, children are not competing with their parents for jobs; they’re competing with peers.  And like themselves, their peers have a higher level of education than their parents do.  In relative terms, they only have an advantage in the competition for jobs if they have gained even more education than their peers have.  Educational gains relative to peers are what matter not gains relative to parents.  As a result, rates of social mobility have not increased over time as educational opportunity has increased, and societies with more expansive educational systems do not have higher mobility rates.

Raymond Boudon and others have shown that the problem is that increases in access to education affect everyone, both those who are trying to get ahead and those who are already ahead.  Early in the 20th century, working class parents had a grade school education and their children poured into high schools in order to get ahead; but at the same time, middle class parents had a high school education and their children were pouring into colleges.  So both groups increased education and their relative position remained the same.  The new high school graduates didn’t get ahead by getting more education; they were running just to stay in place.  The new college graduates didn’t necessarily get ahead either, but they did manage to stay ahead.

So school reform in the U.S. has failed to increase social mobility or reduce social inequality.  In fact, without abandoning our identity as a liberal democracy, there was simply no way that educational growth could have brought about these changes.  School reform can only have a chance to equalize social differences if it can reduce the gap in educational attainment between middle class students and working class students.  This is politically impossible in a liberal democracy, since it would mean restricting the ability of the middle class to pursue more and better education for their children.  As long as both groups gain more education in parallel, then the advantages of the one over the other will not decline.  And that is exactly the situation in the American school system.  It’s the compromise that has emerged from the interaction between reform and market, between social planning and consumer action: we expand opportunity and preserve advantage, both at the same time.  From this perspective, the defining moment in the history of American education was the construction of the tracked comprehensive high school, which was a joint creation of consumers and reformers in the progressive era.  That set the pattern for everything that followed.  It’s a system that is remarkably effective at allowing both access and advantage, but it’s not one that reformers tried to create.  In fact, it works against the realization of central aims of reform, since it undermines social efficiency, blocks social mobility, and limits democratic equality.

These three goals, however, have gained expression in the American educational system in at least two significant ways.  First, they have maintained a highly visible presence in educational rhetoric, as the politics of education continuously pushes these goals onto the schools and the schools themselves actively express their allegiance to these same goals.  Second, schools have adopted the form of these goals into their structure and process.  Democratic equality has persisted in the formalism of social studies classes, school assemblies, and the display of political symbols.  Social efficiency has persisted in the formalism of vocational classes, career days, and standards-based testing.  Social mobility has persisted in the formalism of grades, credits, and degrees, which students accumulate as they move through the school system.

Next Week: Roots of the Failure of School Reform to Resolve Social Problems: David Labaree on What Schools Can’t Do (Part 2)

Lessons I Have Learned from Researching School Reform — Larry Cuban

This week, IEN reposts a blog from Larry Cuban that captures the challenges of clearly articulating the difficulty of reforming schools on a large scale while still fostering hope for the future. Cuban is a Professor Emeritus of Education at Stanford University, a former high school social studies teacher and district superintendent, and one of the foremost authorities on educational reform in the US. Previous IEN posts from Cuban or focused on Cuban’s work include Schooling around the World; The arc of Progressivism and “Grammar of Schooling”; and (Not) Reforming again and again and again The original post appeared on Larry Cuban’s Blog on July 9th.

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Many years ago, I had met with a group of Stanford University graduate students then working on their joint Masters in Business Administration (MBA) and education. Some had taught for a few years through Teach for America and were eager to graduate and then apply their knowledge and skills learned in their MBA program to largely minority, low-performing schools.

Here is the post I wrote about that discussion I had with these wannabe reformers eager to engage in changing schools.

Many of the 18 MBA students sitting around a seminar table had taught a few years in urban schools through Teach for America (TFA). Those who had no direct experience in schools had worked for consulting firms with contracts in major urban districts. Smart, savvy about organizations and passionate about reforming schools, the students wanted to hear my thoughts about reform that I had extracted from nearly a half-century of experience as teacher, superintendent, and researcher.

I offered four lessons. Since I have written about each of these lessons in earlier posts I will compress the lessons and cite the earlier posts for those readers who want more information.

I learned that:

*It is essential to distinguish between reform talk, adoption of reform-driven policies, and putting reforms into classroom practice. (See https://larrycuban.wordpress.com/2011/01/18/the-inexorable-cycles-of-school-reform/)

* Reform talk and policy action in the purposes of tax-supported schooling, curriculum, instruction and organization of schools often occur in cycles but putting reforms into practice is slow, requires steady work, incremental, and often zig-zag. (See https://larrycuban.wordpress.com/2011/01/18/the-inexorable-cycles-of-school-reform/)

* Turning to public schools as a solution for larger economic, social, and political problems has become a national tic, a peculiar habit, that U.S. reformers have had for decades (See https://larrycuban.wordpress.com/2011/01/15/does- reforming-u-s-schools-soften-or-harden-inequalities-in-wealth-and-health/

* Both stability and change mark the path of public schools over the past two centuries (See https://larrycuban.wordpress.com/2009/08/16/how-do-teachers-teach-2/ )

I spent about 30 minutes going over these lessons and then I opened the floor to students’ questions.

After a few questions asking me to clarify the lessons I had learned, a visibly agitated young woman recounted her experience as a TFAer in an urban district and her journey to Stanford for conceptual and organizational skills (and credentials). She wanted to return to a similar system to make organizational and instructional changes.

Then she asked her question: “Larry, look around this room. It is filled with people who want to reform failing schools. We will have the knowledge and skills and we will work hard. But your message to us is that reform talk occurs in cycles, adopted reforms come back again and again, reformers stumble a lot and when changes do occur they are small ones. Well, how can I put it: you don’t give me and my colleagues here too much hope. I am depressed from the lessons you have learned over so many decades. What advice would you give to all of us?”

I was neither surprised nor put off by the question. David Tyack and I had taught a course on the history of school reform for over a decade from which we wrote our book, Tinkering toward Utopia. Moreover, I had heard variations of this question often as a conference keynoter and in many prior discussions with students, colleagues, and conferees.

The upside of the student’s comment is recognizing that emotions and passions buried in heart-felt values of equity and helping urban low-income and minority students drive much school reform. That is a plus often overlooked by policymakers who too often prize values of effectiveness and efficiency and cite cost-benefit trade-offs and return on investment (ROI) rather than openly acknowledging the emotions involved in reform.

Emotions fuel practitioners, policymakers, and parents to move past the inevitable potholes on the road to reform success. Whether a reform is scientifically proven, logical, or even efficient surely matters but high-octane self-confidence and righteous belief in doing something worthwhile count also.

Unfortunately, emotions too often skip over inspection of assumptions. And there is one quiet assumption hidden in that student’s question.

Wanting to do good for urban youth, willing to put in hard work, and having a Stanford degree were somehow enough to turn around a failing classroom and an under-performing school. And here in this seminar I was claiming that any wannabe reformer needed knowledge of previous well-intentioned designs and prior reformers who had also worked hard but experienced a few small victories while often tasted the salt of many failures. That I may have triggered the blues in some of these wannabe reformers seemed both unfair and unrealistic to my questioner.

Even though nearly all these students accepted the accuracy of what I said-–many had read similar accounts of previous reforms–- I sensed that the questioner wanted reassurance that her time, energy, and commitment would pay off later in successful reforms.

Since I could neither reassure her nor give her unvarnished hope, what advice did I give this room filled with Reformers-R-Us?

What I did was talk about the importance of knowing realistically what faces anyone undertaking an adventure that contains the possibility, nay, probability of failure. I compared the launching of a reform in a school or district to climbing a difficult mountain. Responsible people want a guide. Someone who can tell the adventurers where the crevices are, what false turns to avoid, where the icy spots are and to be honest about the possibility that they may have to turn back before reaching the summit.

Accurate knowledge of forthcoming difficulties, honesty, and humility are crucial to reaching the summit of a mountain or implementing a school reform. Hope for success rests in expertise, problem solving, and courage but–and this is an especially important “but”–climbing that mountain (implementing that reform in an actual classroom or school) is still worth the effort even if success (however defined) is not achieved.

That is what I told those MBA students.

_____________________________

An Endless Summer for AI and Education?

Although most schools take a break for the summer, there has been no letup in articles discussing AI and K-12 education. To take stock of the latest developments, this week’s IEN post shares headlines and links to over 20 articles on AI and education published in major sources of US education news since the middle of June. Among other issues, the articles highlight the rapidity of AI-related developments, the need for guidelines, the challenges for productive learning that created by AI, and AI’s potential to support teachers, teaching and learning in different subjects and domains. (Note: Although we attempted to use AI to help augment and format this list, it generated incorrect links, links to articles from previous years, and misidentified sources and authors.)

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AI embraced by more students and educators, new report finds, Anna Merod, K-12 Dive (July 22, 2026)

Can AI Help Students Learn Social-Emotional Skills? Arianna Prothero, Education Week, (July 19, 2026)

A Step-by-Step Guide to AI in Schools — How Much to Use and When, Jennifer Weber, The74 (July 16, 2022)

Should kids use Google AI search? These experts say no, Rebecca Ruiz, Mashhable (July 15, 2026)

The End of Homework? Teachers Grapple With Cheating in the Age of AI, Greg Toppo, The 74 Million, (July 14, 2026)

Despite the growth of some AI schools like Alpha, research doesn’t show that AI tutors are better than human teachers, Gerald K. LeTendre, The Conversation (July 13, 2026)

Scathing Analysis Concludes Google Search’s AI Tools Are Bad for Kids, Alyson Klein, Education Week (July 15, 2026)

Anthropic Unveils Claude for Teachers, Joining OpenAI and Google in Race to Dominate Classroom AI, Lily Altavena, Chalkbeat (July 14, 2026)

The National AI Policy Landscape in K–12 Education, Jody Britton, EdSurge, (July 13, 2026)

4 More States Require Districts to Adopt AI Policies, Anna Merod, K-12 Dive, (July 9, 2026)

Lessons on AI for Elementary Students: ‘Teach Them Good Habits Now’, Arianna Prothero, Education Week (July 8, 2026)

Faster Solutions, Lower Test Scores: How AI Is Eroding Math Skills, Jill Barshay, The Hechinger Report (July 6, 2026)

AI Gets a Body as Humanoid Robot Enters New York Classroom, Emma Thompson, EdTech Innovation Hub, (July 6, 2026)

High-Earner Families Are Ditching Traditional Schools for Life Skills and AI Tutors’ Katherine Bindley, The Wall Street Journal (July 3, 2026)

Where Chatbots Fit in the Curriculum Conversation: Use of the AI-powered tools to boost students’ writing and studying skills comes with advantages and disadvantages, Ed Finkel, K-12 Dive (July 1, 2026)

More Than Half of Georgia Teachers Now Use Artificial Intelligence to Prepare for Class, Ross Williams, The74 (June 30, 2026)

‘Building AI Apps Is Not Easy’: Stretch, ISTE’s Chatbot, Is Finally Ready to Go, Alyson Klein, Education Week (June 30, 2026)

‘Can AI Save Teachers Time and Reduce Burnout? Anna Merod, K-12 Dive (June 29, 2026)

NYC Delays School AI Rules After Criticism of Draft Guidance, Alex Zimmerman, Chalkbeat, (June 24, 2026)

Reed Hastings on What It Will Take for AI to Be Different From Other Ed Tech: Former Netflix CEO on the ‘urgency for harnessing AI for accelerated, mastery-based learning. Michael Horn and Diane Tavenner, Class Disrupted /The74 (June 24, 2026)

Norway Imposes Near Ban on AI in Elementary School, Reuters, (June 19, 2026)

AI in Schools: 3 Ways Congress Can Help Anna Merod, K-12 Dive, Original Source (June 18, 2026)

Student Cheating Is Becoming Impossible to Detect in an A.I. Era: Big tech companies and small start-ups are using social media to hype new tools that allow students to trick teachers and A.I. detectors, Dana Goldstein, New York Times (June 18, 2026)

Students Are Experiencing AI in Very Different Ways. Is That a Problem? Jennifer Vilcarino, Education Week, (June 18, 2026)

Survey: Young People Turn to AI to Be ‘Their Real, Unfiltered Selves’: New research shows 1 in 3 young people use AI for personal, relational support or engaging intimately with characters and personas, Greg Toppo, The 74 Million, (June 15, 2026)

“Micro-Innovations” in Assessment for Specific Subjects, Levels, and Contexts: AI, New Technologies and the Future of Assessment (Part 4) 

With so much changing so fast, what new developments in assessment at the classroom and school level bear watching? In the final post in this four-part series, Adelaida Kim and Thomas Hatch provide examples of “micro-innovations” in assessment that leverage AI and new technologies to support the development of specific skills and abilities in different subjects and levels. Part one provided an overview of some uses of AI in both large-scale standardized tests and classroom-based assessments. Part two described some of the new platforms, apps, and tools that teachers can use to create, analyze, and score assessments, particularly those that support more student-centered learning. Part three took a deeper look at and compared the strengths and weaknesses of the assessment capabilities of selected teacher-directed AI platforms, EdTech tools, and AI “assistants” with multimodal capabilities. For related stories on AI and education, see: Can AI “ignite the mind and heart”? Stability & change in the education system in China (Part 3); Scanning the global headlines for recent news on AI, schools, and education; AI, Cellphones, Literacy, Students’ Mental Health, Political Turmoil and More: Scanning the Headlines for the Top Education Stories for 2025.

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Fueled by AI and new technologies, innovations in assessment are emerging and quickly finding their way into classrooms, educational platforms, and large-scale tests. These include a wide range of digital tools that purport to help educators improve assessments across subjects and levels (see, for example, NWEA’s 75 digital learning tools and apps that teachers can use to support formative assessment and instruction in the classroom). Beyond these generic tools, however,  a number of “micro-innovations” are demonstrating how new assessments can support the development of specific skills and knowledge in different subjects and at different levels. The effectiveness of most of these new assessment tools and approaches has not yet been established, but a review of recent articles from major education news outlets provides a sense of what’s already out there. The book Artificial Intelligence and Education in the Global South also provides a glimpse of AI’s role in assessments across different subjects and contexts in developing countries. 

A game-based approach for assessing linguistic skills among students with dyslexia

Dysolve is an AI-based educational platform developed to support learners with dyslexia and related language-processing differences through adaptive, game-based activities rather than traditional static assessments or interventions. The platform provides users with customized interactive verbal games; as students play, the program analyzes responses in real time and generates new games that focus on specific cognitive and linguistic skills that need further development. To increase novelty, games are only used once and then disappear. Preliminary findings indicate potential improvements in reading outcomes for some elementary-aged learners, 

Read-alouds and speech recognition for assessing reading abilities 

Conventional early-grade reading assessments have relied on training educators to administer one-on-one tests, but this individualized approach makes large-scale testing expensive and demanding. Newer AI-based approaches, combined with developments in speech recognition technologies, however, can be administered to many students at once while still gathering detailed information about phonemic awareness, decoding ability, and reading fluency. For example, SoapBox Labs has developed speech-recognition technology designed to interpret children’s voices and convert oral reading or spoken responses into data that can inform assessment. This approach seeks to embed assessment within routine classroom activities, such as having early elementary students read aloud while automated systems transcribe speech, analyze fluency or comprehension indicators, and generate information that may guide instructional decisions. Following its acquisition by Curriculum Associates, this technology has been incorporated into existing educational programs, including i-Ready, reflecting broader efforts to integrate voice-based analytics into literacy instruction. 

Among a slew of related platforms and tools, Amira fuses voice-based AI into reading activities with a chatbot or “reading assistant.” Amira’s reading assistant begins by observing a student read for six to ten minutes and gauges the child’s ability to name letters, sound out words and combine them into phrases and sentences. From that initial screening, Amira can gather information to spot signs of dyslexia, assess phonics mastery, estimate a student’s vocabulary size, and get a handle on decoding skills and comprehension levels. Then, the program reports findings to a teacher to support differentiated instruction, estimating the literacy levels and needs of individual students.

Amira’s “reading assistant” “observes” a student read to gauge key elements of reading ability, The74

Along with the Rapid Online Assessment of Reading (ROAR) and several other edtech-enabled approaches, Amira has been approved by states such as California and New Jersey to facilitate early screening of students for difficulties in learning to read. Some initial evidence suggests these digital tools can improve reading outcomes for some students, but with some limits.  According to Ran Liu, chief AI scientist at Amira, “We’ve learned that around 25-30-minute sessions are where we see a ceiling effect.” Although Amira can also be used with Spanish-speaking students, all of these tools need to be adapted for other languages, and critical concerns include how well they will work for students with accents or speech-related challenges. 

Automated Early Literacy Assessment in Low-Resource Languages

Although many of the most well-known AI tools focus almost exclusively on English, training AI models on locally collected speech data also enables assessments in a wide range of languages, including those that are often underrepresented in educational technology systems. To that end, the EGRA-AI project in South Africa explores whether speech-recognition models can automatically assess children’s early reading abilities in African languages such as Sepedi and isiXhosa. The system records children reading letters or words aloud and uses machine learning models to determine whether their pronunciation is correct.

AI-Supported Feedback on Student Writing in contexts with limited internet access

In addition to AI-enabled platforms like Classtime and Brisk that provide automated feedback on student performance across many subjects and levels, some tools are being designed specifically to meet the needs of educators working in areas with limited digital infrastructure and large class sizes. For example, in the AIED Unplugged initiative in Brazil, teachers photograph students’ handwritten essays and upload the images to an AI system that evaluates them using a predefined rubric. The system converts handwriting using optical character recognition and provides rubric-aligned feedback on organization, grammar, and argumentation. The system is designed for teachers to review the feedback before returning it to students. 

A game-based approach to assessment in physics

Although many digital tools focus on foundational skills like reading, NWEA (Northwest Evaluation Association) has been working with the game maker Filament Games to develop a digital assessment that examines middle school students’ understanding of Newton’s Second Law of Motion. The assessment uses a collaborative 3D simulation in which pairs of students adjust variables, such as mass and force, to synchronize virtual vehicles, enabling the system to capture evidence of scientific reasoning during problem-solving. The assessment – Distance Dash – is a game-based, digital assessment delivered through the Roblox platform. In the game, “students pick a skateboard, a bike, a grocery cart, or an automobile, load each with different items, then collaboratively fine-tune the forces placed on them. The whole time, the game covertly measures several objectives, including whether students understand the principles of acceleration and how to apply optimal force.” The project is part of broader efforts to explore game-based environments as potential spaces for classroom assessment, while also raising questions about how such platforms shape collaboration, engagement, and the measurement of student learning.

A still image from Distance Dash on Roblox. (NWEA), The74

AI-Supported Preparation for High-Stakes Examinations

In Liberia, AI-driven chatbots are being piloted to help secondary school students prepare specifically for the West African Examinations Council (WAEC) exams. These chatbots simulate exam-style questions, provide explanations of correct answers, and offer targeted practice in areas where students struggle. Although they are primarily designed as learning tools, such systems implicitly rely on continuous formative assessment: the chatbot must infer a student’s level of understanding in order to generate appropriate questions and feedback.  

AI-Based Measurement of Collaborative Problem-Solving

AI is also being used to measure competencies that are difficult to assess through traditional tests. In the ACTNext “Crisis in Space” pilot, students work together in a multiplayer game environment to solve a simulated emergency scenario. AI systems analyze students’ dialogue and interactions—such as turn-taking, information sharing, and problem-solving strategies—to assess collaborative skills. Rather than evaluating a single correct answer, the system analyzes patterns in communication and teamwork. This approach reflects broader efforts in educational measurement to assess 21st-century competencies, including collaboration and collective problem-solving, using AI-driven analysis of behavioral data

Oral assessments in higher education.

With students’ use of AI tools raising concerns about cheating, many educators are looking for alternatives to essays, research reports, and other written assessments. Those concerns, in turn, have fueled a renewed interest in oral assessments. For instance, Panos Ipeirotis, a professor at New York University’s business school, noticed that many students in his data science class were unable to discuss or defend their own written work when called upon. As Ipeirotis put it, “If you cannot defend your own work live, then the written artifact is not measuring what you think it is measuring.” 

“If you cannot defend your own work live, then the written artifact is not measuring what you think it is measuring.” – Panos Ipeirotis

In response, he and a colleague built an “AI examiner” using conversational speech technology that probed students’ thinking about their capstone projects and that could question students about one of the cases discussed in class. With a class of over 30 students, a single instructor could not conduct such individualized oral exams, but Ipeirotis’ AI agent assessed 36 students for about 25 minutes each over nine days. Ipeirotis even had ChatGPT, Claude, and Gemini score students’ responses and asked them to review the scores and generate a final grade, with Claude designated as the “chair” of the panel to synthesize the decisions. Student reactions were mixed — most found the format more stressful than traditional written tests, but many also acknowledged it was a more authentic measure of their understanding 

Large-scale developments in assessment that might eventually be used at the classroom and school level

Efforts to develop digital and multimodal assessment tasks for large-scale assessments may also provide models for how educators might assess capacities not normally measured in conventional assessments. Notably, the Program for International Student Assessment (PISA) has introduced a Creative Thinking assessment to examine the creative capacities of 15-year-old students in more than 60 countries. This assessment differs from conventional standardized measures by incorporating interactive digital tasks, including opportunities for students to produce drawings and respond to open-ended prompts with multiple possible solutions rather than a single correct answer. In addition to documenting creative expression, the assessment reflects broader efforts to capture dimensions of student learning that extend beyond strictly cognitive outcomes, such as engagement, flexibility in problem solving, and responsiveness to novel tasks. These kinds of tasks provide a model for other multi-modal assessments of competencies that may eventually find their way into tools and technologies available to educators. 

Similarly, with the concerns about the authorship of college applicants’ personal essays, tech-enabled video interviews may become a more common part of the college application process. Even before the AI boom, companies like InitialView were developing platforms that allowed students to record video interviews they could send with their applications to a number of US colleges. Particularly popular with international applicants, the platform had, by 2014, attracted over 17,000 applicants from China. In the last few years, the company has developed a related application, VIVA, in which students upload a research paper or project, and an AI agent then generates a series of questions about their project that students answer during a recorded video interview. Originally offered by Caltech to accompany research papers that some applicants submitted as application supplements, the same video-based approach could be used to support oral defenses and classroom presentations in both K-12 and higher education. 

Caltech’s application instructions & a sample image from the VIVA video interview

Questions for the future

These examples illustrate some of the ways AI and other digital tools may help educators conduct assessments tailored to specific skills, competencies, and subjects at different levels and in more- and less-developed contexts. At the same time, these examples demonstrate how quickly things are changing and how difficult it is to obtain detailed information about the effectiveness and impact of most AI-related developments. In this context, many educators and students may find themselves using these AI and technology tools without really knowing: 

  • Which of these tools is most likely to improve learning?
  • For which students?
  • Under what conditions?
  • At what cost to professional judgment, student agency, and curricular coherence?

Under these conditions, AI developers and researchers have a responsibility to work with educators to keep these critical questions at the forefront of their collective work.

The Emerging Affordances of Teacher-Directed Platforms, EdTech Tools, and Multimodal Assistants: AI, New Technologies and the Future of Assessment (Part 3)

What are the benefits and drawbacks in using different AI-powered tools for assessment? In part three of this four-part series, Philip Seyfried, Suet Cheah, Alok Sharma, and Dana Bassynbekova highlight the differences in the key features and level of teacher oversight and control that several prominent AI platforms, tools, and chatbots offer for assessment and development of student learning. Their analysis was produced as part of a project working with District 79 of the New York City Public Schools. Part one of this series provided an overview of some uses of AI in both large-scale standardized tests and classroom-based assessments. Part two described some of the new platforms, apps, and tools that teachers can use to create, analyze, and score assessments, particularly those that support more student-centered learning. Part three took a deeper look at and compared the strengths and weaknesses of the assessment capabilities of selected teacher-directed AI platforms, EdTech tools, and AI “assistants” with multimodal capabilities. In the final post in this three-part series, Adelaida Kim and Thomas Hatch provide examples of “micro-innovations” in assessment that leverage AI and new technologies to support the development of specific skills and abilities across subjects and levels. For related stories on AI and education, see: Can AI “ignite the mind and heart”? Stability & change in the education system in China (Part 3); Scanning the global headlines for recent news on AI, schools, and education; AI, Cellphones, Literacy, Students’ Mental Health, Political Turmoil and More: Scanning the Headlines for the Top Education Stories for 2025.

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Artificial intelligence (AI) is rapidly reshaping what is possible in educational settings. AI enables new pathways not only in how students learn, but in how their understanding can be demonstrated, assessed, and developed over time. But the benefits and drawbacks of AI for assessment differ substantially, depending on the affordances of different platforms and tools. Broadly, three categories of AI-powered tools differ in their key features and the degree of teacher oversight, which has important implications for assessment, particularly assessments that move beyond traditional text-based responses toward multimodal, creative, and conversational demonstrations of understanding.

  • Teacher-Directed AI Platforms: Purpose-built EdTech tools designed to put curriculum and guardrails in teachers’ hands, with visibility into student interactions
  • Creative AI Tools: Platforms that empower students to demonstrate learning through the creation of videos, presentations, podcasts, and images
  • Multimodal General AI: Large-scale AI assistants that can generate text, images, and interactive experiences, and which are increasingly finding educational applications

Comparison at a Glance

ToolTeacher SetupStudent CreationQuiz / FeedbackMultimodal OutputTranscript Access
Magic School AI
School AI
Flint AI
NotebookLM
Canva (AI)
Google Gemini
Google Gems

Note: Current capabilities as of July, 2026. “Teacher Setup” refers to the teacher’s ability to configure the AI experience before students use it. “Student Creation” refers to whether students can produce their own multimodal artifacts (images, video, slides, audio) within the tool. “Quiz / Feedback” refers to the ability to quiz or provide feedback on student work. “Transcript Access” refers specifically to the teacher’s ability to read the student’s conversation with the AI.

Teacher-Directed AI Platforms

The tools in this category have been built specifically for K–12 and higher education contexts. Their defining features are teacher control, transparency, and safety. Educators can design AI-powered activities and chatbot experiences, set parameters for student interaction, and critically review what students have said and done on the platform. These features help make these tools useful for formative assessment, differentiated practice, and the ethical deployment of AI in school settings.

Magic School AI

Magic School AI  |  Teacher-Directed AI Platform
OverviewA comprehensive AI platform for educators offering 60+ AI-powered tools, including a “Magic Student” suite that lets teachers build structured AI activities for their classrooms.
Key FeaturesTeacher-designed AI chatbots and activities; student guardrails; access to conversation transcripts; learning analytics dashboard; differentiation tools.
Assessment UseTeachers can assign AI-facilitated activities and review student interactions to assess comprehension, reasoning, and writing development.
Access ModelFree tier available; paid plans for full feature access. Widely adopted in US K–12 schools.

School AI

School AI  |  Teacher-Directed AI Platform
OverviewA student-facing AI learning environment built around “Spaces,” which are teacher-configured AI experiences with defined purposes, personas, and guardrails.
Key FeaturesCustom AI Spaces for each assignment or learning context; teacher visibility into all student-AI conversations; real-time monitoring; safety filters.
Assessment UseTeachers can use conversation data as evidence of student thinking; Spaces can be configured to ask Socratic questions rather than simply provide answers, generating richer assessment evidence.
Access ModelSchool and district licensing model. Designed to integrate into existing classroom workflows.

School AI’s “Spaces” architecture can support alternative assessment approaches. Because teachers define what the AI does and does not do within each Space, they can design experiences that elicit student thinking rather than simply complete tasks for students. The transcript visibility feature is central to its use as an assessment tool.

Flint AI

Flint AI  |  Teacher-Directed AI Platform
OverviewAn AI tutoring and classroom engagement platform that enables teachers to create custom AI tutors with specific personalities, knowledge bases, and behavioral constraints.
Key FeaturesCustom AI tutor creation; teacher monitoring of all student interactions; analytics on student engagement and learning; content guardrails; assignment integration.
Assessment UseAI tutors can be configured to probe student understanding through questioning. Teacher-facing analytics provide formative data. Conversation logs serve as qualitative assessment artifacts.
Access ModelSchool and district licensing. Offers LMS integrations.

Flint emphasizes the tutoring relationship and students receive personalized support while teachers maintain visibility and control. For assessment purposes, the combination of analytics and conversation transcripts offers a window into student thinking that traditional written assessments may not capture.

What Teacher-Directed Platforms Share

Across Magic School AI, School AI, and Flint AI, three features stand out as essential to their value for learning and assessment:

  • Teacher-designed activities and guardrails: the teacher shapes the learning experience before students ever interact with the AI
  • Conversation visibility: teachers can read what students said and how the AI responded, creating a rich record of student thinking
  • Learning analytics: aggregate and individual data surfaces patterns in student engagement and understanding

Together, these features make teacher-directed platforms particularly useful for formative and alternative assessment at this time.

Creative AI Tools

The tools in this category empower students to create multimodal products, such as videos, podcasts, slide presentations, images, and diagrams, to demonstrate their learning. Teachers can ask students to produce an explanation, a visual argument, or a narrated presentation. AI dramatically lowers the technical barrier to these forms of expression, making them accessible to more students.

NotebookLM

NotebookLM  |  Creative AI Tool (Google)
OverviewGoogle’s AI-powered research and synthesis tool that allows users to upload source documents and interact with an AI grounded in those sources. Increasingly capable of generating multimedia outputs.
Key FeaturesSource-grounded AI responses (reduce hallucination); podcast-style audio generation from documents; study guide and FAQ generation; mind map and visual summary creation; video overview generation.
Assessment UseStudents can upload a set of sources and ask NotebookLM to generate a podcast, video overview, or visual explanation of a concept, thereby creating a multimedia artifact that demonstrates synthesis and understanding. Teachers can assess the quality of the artifact as evidence of learning.
Teacher OversightNo direct teacher oversight or transcript visibility built in. Teachers assess the final product rather than the process.

One way to use Notebook-LM for assessment is to ask students to upload primary or secondary sources and then produce a NotebookLM-generated podcast or video that explains a concept, event, or argument. The quality of the output reflects the quality of the sources students selected, and the prompts they used can reveal meaningful understanding. Students then can analyze the results, identifying what AI did well and what important information and perspectives it misses. Notably, however, selecting lower quality texts and prompts may make it harder for students to demonstrate more sophisticated analyses.

Canva (with AI Tools)

Canva  |  Creative AI Tool
OverviewA widely used design platform that has integrated a suite of AI tools for image generation, photo editing, presentation creation, video production, and more.
Key FeaturesAI image generation and editing; AI-assisted slide presentation design; video creation with AI voiceover; photo background removal and editing; “Magic Write” for text generation; diagram and infographic templates.
Assessment UseStudents can edit images for a visual argument, build an AI-assisted presentation to explain a concept, create an infographic to synthesize research, or produce a short video demonstrating the process they went through. These artifacts serve as alternative assessments of understanding.
Teacher OversightNo built-in teacher monitoring of AI interaction. Assessment focuses on the finished product. Canva for Education offers classroom management features, including assignment sharing.

Canva’s value for alternative assessment lies in its accessibility and range. Students who might struggle with a traditional essay may demonstrate a more sophisticated understanding through a well-designed infographic or a narrated video. Photo-editing tasks, such as adjusting an image for a presentation, can also demonstrate visual literacy and design thinking alongside content knowledge.

Both NotebookLM and Canva shift assessment from the process of thinking to its product, which can have both benefits and drawbacks. For instance, these tools enable simultaneous assessment of content knowledge and creative and technical skills, and the reduced technical barrier means more students can demonstrate learning in ways that suit their strengths. However, teachers must develop criteria for assessing multimodal products, not just written responses. Furthermore, the artifact itself (the video, the podcast, the presentation) becomes both the assessment and the evidence of learning, but neither tool currently provides teachers with visibility into the AI interactions that produced the artifact.

Multimodal General AI

General-purpose AI assistants like Google Gemini are increasingly capable across modalities by generating text, producing images, creating video, and supporting interactive experiences. As these tools add educational features (like Google Gems), they occupy a middle ground between creative tools and teacher-directed platforms. They are powerful and flexible, but their oversight features are currently more limited than those of purpose-built EdTech platforms.

Google Gemini

Google Gemini  |  Multimodal General AI (Google)
OverviewGoogle’s flagship AI assistant, available across the Google ecosystem. Gemini is increasingly multimodal, capable of generating text, images, and video, and of reasoning across multiple formats.
Key FeaturesText generation and conversation; image generation; video generation (Veo integration); code generation; document analysis; integration with Google Workspace tools.
Assessment UseGemini can quiz students on a topic, provide feedback on submitted writing or work, and help students explore ideas through conversation. Its multimodal output capabilities allow students to create a range of artifacts.
LimitationAt this time, Gemini does not provide teachers with access to transcripts of student conversations. Assessment of AI-assisted work must rely on final products or student self-reporting.
AccessGemini Advanced is available through Google accounts with a Google One subscription. Integrated into Google Workspace for Education.

Gemini’s growing multimodal capabilities make it a versatile tool for student creation. A student might ask Gemini to generate an image illustrating a concept, then embed it in a presentation with an explanation they have written. Or they might submit a draft essay and receive detailed feedback, an experience that mirrors personalized writing conferences. However, the absence of teacher-visible transcripts is a key limitation for use in formal assessment. Teachers can assess what students produce with Gemini’s help, but not the quality of their reasoning within the conversation itself.

Google Gems

Google Gems  |  Configurable AI Agents within Gemini
OverviewGems are customizable AI personas within Google Gemini. Teachers or institutions can create Gems with specific roles (a research assistant, a writing coach, a practice quiz partner) and share them with students.
Key FeaturesCustom AI persona creation with defined roles and instructions; ability to set a specific knowledge focus; shareable with student groups; supports Socratic questioning, practice environments, and research assistance.
Assessment UseA teacher can create a Gem configured to quiz students on a specific topic, ask follow-up questions, or provide scaffolded feedback on submitted work. Students interact with a purpose-built AI experience within the broader Gemini environment.
LimitationLike Gemini generally, Gems do not currently provide teachers with access to conversation transcripts. The teacher sees neither what the students asked nor how the Gem responded.
Comparison NoteGems offer similar configurability to teacher-directed EdTech platforms (Magic School AI, School AI, Flint), but currently lack the teacher-visibility features that make those platforms most useful for assessment.

Google Gems represent an important development: a mainstream AI platform that adds teacher-configurable experiences. However, Gems’ usefulness for assessment depends on whether or not future versions add teacher visibility into student interactions.

Implications for Assessment Design

Each category of tool implies a different approach to assessment design. Understanding these distinctions helps educators choose the right tool for the right assessment purpose.

Process-Visible Assessment

When using teacher-directed platforms (Magic School AI, School AI, Flint AI), the conversation itself is an assessment artifact. Teachers can evaluate:

  • The depth and relevance of questions a student asks the AI
  • How a student responds when the AI pushes back or asks a clarifying question
  • The progression of a student’s thinking across a multi-turn conversation
  • Whether a student recognizes when the AI has made an error

This form of assessment is particularly valuable because it surfaces metacognitive processes that traditional written products often obscure.

Product-Based Assessment

When using creative tools (NotebookLM, Canva) or general AI (Gemini), assessment focuses on what the student creates. Rubrics for product-based assessment should address:

  • Accuracy and depth of content knowledge demonstrated
  • Quality of synthesis across multiple sources or ideas
  • Clarity and effectiveness of communication in the chosen medium
  • Evidence of original thinking beyond AI-generated content
  • Appropriate attribution of AI-assisted elements

Product-based AI assessment works best when teachers pair it with reflections or oral explanations, giving students the opportunity to articulate what they made and why, which provides additional assessment evidence and can help reveal when students have not thought through or critically analyzed their use of AI.

Feedback and Practice Environments

Both teacher-directed platforms and Google Gems can serve as low-stakes practice and feedback environments that provide students with iterative responses to their work without the pressure of a formal grade. These uses include:

  • Submitting a draft for AI feedback before a teacher conference
  • Practicing for a presentation by interacting with a Gem configured as an audience member
  • Working through a problem set with an AI tutor that provides hints rather than answers

In these contexts, the AI functions less as an assessment instrument and more as a rehearsal space that frees teacher time for higher-order feedback and conferring.

Looking Ahead

The landscape of AI tools in education is evolving rapidly. Several trends are worth watching:

  • Growing teacher oversight of general AI tools. Platforms like Google Gemini and its Gems feature may add transcript visibility and classroom management features as they develop education-specific versions. This would significantly expand their usefulness for assessment.
  • Richer multimodal assessment. As students gain facility with tools like NotebookLM and Canva, educators will have the opportunity to design assessments that require video explanations, well-designed presentations, or AI-assisted research products, pushing assessment beyond text-based demonstrations of knowledge.
  • The conversation as curriculum. In teacher-directed platforms, the transcript of a student’s conversation with AI is a new kind of learning record that documents not just what a student knows, but how they think. Assessment frameworks will need to evolve to make productive use of this data.
  • Questions of attribution and academic integrity. As AI becomes embedded in the creation process, assessment design must grapple with what it means to demonstrate learning when AI has contributed to the product. Clear expectations, reflection requirements, and process-visible assessment approaches all play a role.

Next week: “Micro-Innovations” in Assessment for Specific Subjects, Levels, and Contexts: AI, New Technologies and the Future of Assessment (Part 4)


Can Online Platforms and Digital Tools Support More Student-Centered Learning? AI, New Technologies and the Future of Assessment (Part 2) 

Can new developments in assessment support more student-centered learning? In the second part of this three-part series, Adelaida Kim summarizes how AI and other technologies already offer educators new ways to generate, administer, and analyze assessments, including more student-centered and competency-based assessments. Part one provided an overview of some of the uses of AI in both large-scale tests and classroom-based assessments. Part three will compare the strengths and weaknesses of the assessment capabilities of selected teacher-directed AI platforms, EdTech tools, and AI “assistants.” Part four will provide examples of “micro-innovations” that already demonstrate how AI and new technologies can assess and support the development of specific skills and abilities across subjects and levels. For related stories on AI and education, see: Can AI “ignite the mind and heart”? Stability & change in the education system in China (Part 3); Scanning the global headlines for recent news on AI, schools, and education; AI, Cellphones, Literacy, Students’ Mental Health, Political Turmoil and More: Scanning the Headlines for the Top Education Stories for 2025.

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The rush to incorporate AI into all manner of educational platforms and products has already equipped educators with new ways to assess their students. Many of those tools support conventional tests and quizzes, but some may offer educators opportunities to develop alternative assessments, including portfolios, performance tasks, evidence demonstrations, peer reviews, and self-assessments. In particular, emerging technologies, including AI, could assist teachers in generating more complex, real-world tasks, facilitate data collection, analysis, and feedback, and perhaps foster the development and assessment of a wider range of abilities and overall well-being. Although it is too early to tell how effective many of the new developments will turn out to be, an examination of some of the news and research on assessment over the past few years points to new developments in digital platforms, digital portfolios, learning management systems, and tools for adaptive learning that all bear watching. 

New Platforms, Portfolios, Learning Management Systems, and Assessment Tools

Teachers and students in the US and around the world now have access to a host of different learning platforms. Some of those platforms include features that may help educators manage the complexity of competency-based and personalized assessment. Lift Learning, Foundry, Headrush Learning, Epiphany Learning, and Building 21 represent systems designed specifically around competencies rather than content sequences. These platforms provide structures for organizing student evidence, tracking mastery, supporting project-based learning, and facilitating personalized learning plans. These elements aim to make it easier for teachers to capture artifacts from daily classroom work, such as quick reflections, conference notes, or mini-tasks, and align them to clear performance indicators. The flexibility of these systems allows educators to support formative assessments, such as “micro-conferences,” that provide students with quick feedback and collect and analyze data teachers can use to inform instruction. 

Online platforms

Online platforms may also provide an environment that makes it easier for teachers and students to develop digital portfolios (e-portfolios) that track the development of skills and competencies that extend far beyond those measured by conventional tests. Digital portfolios can capture multimedia materials documenting the processes, products, and performances that students complete. The hope is that by creating a living, accessible collection of work, students, parents, and future educators can all trace academic growth and evolving interests over time, making learning more transparent, equitable, and aligned with real-world competencies.

Learning management systems

Traditional learning management systems have also evolved to support alternative assessment practices. Schoology and Canvas, for example, offer features for rubric-based assessment, multimedia submissions, peer review, and mastery tracking. Meanwhile, Canvas Credentials extends this functionality through digital badges and micro-credentials, intended to indicate when students have demonstrated specific competencies by completing specific activities or producing particular products. These environments aim to provide teachers with an easy way to access new assessment tools, allowing them to integrate tools such as exit tickets, short video explanations, iterative revisions, or authentic performance tasks into familiar LMS workflows.

Platforms for “real-world” skills

Another emerging category includes tools that help bridge classroom learning with real-world skills and career pathways. Territorium, LifeJourney, and Lightcast help schools align student assessments with employability skills and labor-market data. These platforms support a broader vision of alternative assessment: one that recognizes not only classroom competencies but also skills demonstrated in internships, co-ops, community experiences, or extracurricular learning. By mapping student evidence to industry-recognized competencies, these tools help teachers and schools emphasize authentic tasks and support the development of abilities that go beyond conventional academic tasks. 

LifeJourney Homepage showcasing mentors from various industries

Adaptive learning environments

New developments are also supporting the kind of adaptive learning and personalized assessment environments that many hope will make it possible to individualize and differentiate instruction more effectively than in the past. Area9 Lyceum, for example, uses adaptive algorithms to provide continuous formative checks and individualized learning pathways. In these contexts, students can receive real-time feedback, progress through dynamic question pathways, and engage in small-scale, personalized tasks that adjust to their performance.  Similarly, some programs, such as Learn Everywhere, expand the boundaries of where assessment can occur. Allowing students to earn competency-based credit for learning outside the traditional classroom encourages schools to adopt flexible, evidence-driven assessment models. In this approach, teachers use short reflections, artifact documentation, and performance checkpoints to verify learning in diverse settings.

Tools that support multilingual learning and multimodal assessment

To extend the power of this support for alternative assessments, other new tools like Flint AI and School AI can help educators to create assessments that support multilingual learners. These tools enable students to read and respond to prompts, activities, and feedback in different languages. These tools can be particularly useful in subjects that focus on knowledge acquisition, critical thinking, and deeper learning – rather than simply on learning English or another non-native language. In addition, platforms like Canva and Notebook LM increasingly offer opportunities to create and analyze assessments in multiple modalities. These platforms enable students to demonstrate their learning through video-based presentations, audio podcasts, and graphic descriptions, providing windows into their thinking that conventional written responses cannot offer. Again, these alternative formats can be especially useful when students are still developing their capacities to express themselves in writing or in a non-native language. 

Notebook LLM using multiple sources to create assessments such as flashcards, quizzes, and student patterns. Ditch That Textbook, 2026

Implications? 

All these developments are creating a new ecosystem for learning and assessment. The hope is that these new tools and platforms will reduce the burden on teachers, increase transparency for students, and support richer, more authentic, and more personalized demonstrations of learning. However, if the past is any guide, these new developments may be more likely to reinforce conventional testing and instruction than to lead to an immediate revolution. An account of the remarks of Larry Cuban, author of books like Oversold and Underused: Computers in the Classroom, to Google engineers put it this way: “AI will not force educators to rethink how teachers teach, and students learn. Instead, teachers will simply adapt AI to fit the ‘contours’ of their classrooms, keeping it on the periphery of their teaching repertoire.” 

Platforms like Kahoot!, Wayground, Blooket, Gimkit, Quizlet, Formative, Mentimeter, and Plickers can make it easy for teachers to quickly generate formative assessments that students find engaging and that provide frequent information on what students are and are not learning. At the same time, those tools are much better for creating tests and quizzes that measure recall and basic skills than for assessing deeper learning. As with all new technologies, issues of implementation, bias, equity, safety, and effectiveness must be addressed. So far, surveys suggest that the use of AI is growing at a pace that outstrips evidence of its effectiveness and efforts to produce guidelines to support ethical, equitable, and safe use. As a report from Milken Institute published at the end of 2025  indicated, 60% of schools and districts in the US had no guidance on AI use at all, with decisions about how to use AI left largely up to individual teachers.  Under these conditions, concerns about AI among educators, parents, and even students are growing, leaving open a critical question: Can concerns about the use of AI and other new technologies for assessment be addressed as they become ubiquitous? 

Next week:  The Emerging Affordances of Teacher-Directed Platforms, EdTech Tools, and Multimodal Assistants: AI, New Technologies and the Future of Assessment (Part 3)

This work is licensed under a Creative Commons Attribution 4.0 International License.

For Better and for Worse? AI, New Technologies and the Future of Assessment (Part 1)

What effect will AI and other new technologies have on testing and assessment? In the first part of this four-part series, Adelaida Kim and Thomas Hatch provide an overview of how both large-scale tests and classroom-based assessments are changing as AI and new technologies continue to develop. Part two will describe some of the new platforms, apps, and tools that teachers can use to create, analyze, and score assessments, particularly those that support more student-centered learning. Part three will provide a deeper look at and a comparison of the strengths and weaknesses of the assessment capabilities of selected AI platforms, EdTech tools, and AI “assistants”. Part 4 will share examples of “micro-innovations” that are already demonstrating how AI and new technologies can assess and support the development of specific skills and abilities across different subjects and at different levels. For related stories on AI and education, see: Can AI “ignite the mind and heart”? Stability & change in the education system in China (Part 3); Scanning the global headlines for recent news on AI, schools, and education; AI, Cellphones, Literacy, Students’ Mental Health, Political Turmoil and More: Scanning the Headlines for the Top Education Stories for 2025.

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Almost every aspect of assessment is already being affected by AI and new technologies. These new technological developments intersect with long-standing debates about the role that testing and assessment should play in improving learning, teaching, quality assurance, and accountability, contributing to both hopes and fears for the future.  For some, the hopes revolve around making standardized tests more efficient, while others envision a future where conventional standardized testing is obsolete and gives way for the assessment and development of a much wider range of competencies. As Ulrich Boser, co-author of a series of articles about the future of testing, predicted in 2021: “AI is going to eat assessments for lunch.” Of course, those hopes come along with widespread concerns about excessive screen time, cheating, surveillance, privacy, safety, bias, and equity. Although it’s impossible to take stock of every possibility and concern, scanning the headlines for articles about AI and assessment over the past year provides a sense of some of the latest developments in the use of AI for both large-scale standardized testing and classroom assessments.

How might AI affect large-scale testing? 

Many policymakers and researchers argue that standardized testing is an essential tool for accountability and for promoting equity in consequential decisions like college admissions. But critics raise significant concerns, including delays in reporting, which make it difficult, if not impossible, to use the results of these tests to inform instruction and support learning. Chad Aldeman has done the math to show that in 2025, only 6 states released their annual test results by July, while 16 states reported theirs only after October. As he explained, “states have gone from paper-and-pencil tests to computers and somehow gotten slower.” 

The extent of testing also interferes with the time students and teachers have to spend on teaching and learning. A 2015 study from the Council of Great City Schools showed that in large urban districts, U.S. public school students take an average of 112 standardized tests between pre-K and 12th grade. Annually, this testing can take up 20-25 hours of class time. In 2013, a study from the American Federation of Teachers reported that in heavily tested grades, testing might take about 50 hours a year, with over 100 hours of test prep, together consuming almost 15 percent of instructional time. Accountability measures in some states contribute to this problem by instituting year-round testing that requires administering multiple tests over the course of the year, in the hope that the resulting data will help teachers improve student performance. 

Compounding these concerns, the pressure to perform well on all these tests can contribute to a narrowing of the curriculum and a hyper-focus on a limited set of academic skills, making it difficult to support the development of a wider range of abilities and student wellbeing. This disconnect between what’s tested and what’s valued creates considerable frustration among educators. According to a survey by the EdWeek Research Center, almost 60% of educators do not believe that current state standardized tests appropriately measure what students need to know and be able to do.

Regardless of how one views standardized tests, it’s clear that AI is already changing almost every aspect of large-scale testing. Among other things, generative AI can

  • Produce test items
  • Generate sample responses 
  • Create automated feedback 
  • Write reports
  • Adjust item “delivery” to accommodate learning differences
  • Analyze responses to suggest revisions to test items

With these new developments, AI is already being used to grade most writing on New Jersey’s standardized tests; platforms like Classtime give students and teachers almost instant feedback designed to make test-prep more efficient; and test-makers are struggling to keep up with the new developments that enable some students to game the system and cheat on the newest online tests. If the past is any indication, these new developments in testing are likely to both foster long-needed improvements at the same time that they exacerbate some of the most critical problems of over-testing, disengagement, and inequity that continue to plague education. 

Can AI contribute to the development of more powerful classroom assessments? 

AI and new technologies are already changing key aspects of the classroom assessments teachers use day to day. It is far from clear how effective some of these changes will be, but developments may help teachers to measure greater skills, provide more useful feedback, and make assessments more relevant, useful, and personalized. 

Measuring deeper understanding and complex skills. AI technologies, such as natural language processing, can support the development and analysis of alternative assessments, such as performance tasks and portfolios. In particular, teachers may be able to take advantage of AI to help them create tasks such as interactive scenarios in which students interview virtual experts to decide whether a historical artifact belongs in a museum or use a chatbot to research a topic. These kinds of tasks can be difficult for teachers to design and grade, but they give students opportunities to develop and demonstrate skills such as critical thinking, creativity, communication, and problem-solving that are not easily measured by simpler conventional tests. As a UNESCO think piece on the future of assessment argues, AI’s challenge to traditional testing is also “an opportunity to fundamentally realign educational evaluation with more authentic demonstrations of human learning, thinking, and creation.”

Providing Actionable Feedback. Beyond providing final scores, AI can analyze student responses to identify patterns in individual, group, and whole-class answers. These analyses give teachers immediate, concrete data they can use to adjust their instruction and help students right away. As Lauren Katzman points out, providing feedback can be an “unmanageable” task, since spending just 10 minutes reading each student’s draft in a class of 20 can take almost 2 hours. For a high school teacher with 100 students in different classes, reading that one draft can take almost 16 hours. To relieve that workload, initiatives are underway to train AI to provide teachers with information on students’ errors when explaining their reasoning for math problems, enabling teachers to correct student misconceptions in real time. 

Automated writing evaluation (AWE) systems also provide AI-powered scores and feedback on writing directly to students. One meta-analysis found that this automatic feedback had a “moderate” effect size with larger effects for multilingual learners. However, wide variation in results led the researchers to warn that “automated feedback should be combined with other forms of support, such as teacher feedback and individualized learning opportunities, to ensure its effectiveness.” Correspondingly, research reveals that students who write without AI assistance but then use AI to revise their writing show the strongest learning-related brain activity. In contrast, students who use AI to help them write from the beginning show lower brain activity and “lower satisfaction and ownership over their work.”

Weekly Learning Gain Comparison: AI-Driven vs. Traditional Learning Methods (Weeks 1-8). Ayeni, A. O., Ovbiye, R. E., Onayemi, A. S., & Ojedele, K. E. (2024)

“Personalized” and adaptive assessment and instruction. Numerous educational programs, particularly tutoring programs, are already using AI to “personalize” or individualize assessment and instruction in various ways. Among recent developments, educators can use AI to adapt assignments and tests to student learning differences by translating assessments into different languages; taking advantage of chatbots designed to respond to the behavioral cues of students with autism; and employing computer-assisted environments designed specifically for voice and gesture recognition. 

AI can also generate test items that measure core skills but are tailored to a student’s individual interests. At the simplest level, that might include testing fractions by providing a student who loves baking with questions based on a cookie recipe or a student who loves sports might get questions based on the dimensions of a football field. AI can also help educators to generate more complex questions that draw on students’ experiences and local knowledge. For example, questions about physical phenomena that students have observed can replace more generic physics problems. Conceivably, more personalized testing can be more engaging for students, potentially reducing test-taking anxiety and increasing motivation and providing a more accurate representation of their knowledge and abilities. For the most part, however, these claims still need to be tested and verified. 

Beyond tailoring content to student interests, many educators and researchers are exploring adaptive assessment — a form of personalization in which AI analyzes each student’s responses in real time and adjusts subsequent questions and tasks. This is the underlying logic of AI-powered many tutoring tools like Khan Academy’s Khanmigo, which guides students through problems by responding to their specific answers rather than simply providing correct ones, and platforms like Squirrel AI, which has been named one of TIME’s Best Inventions of 2025 for its ability to break subjects down into granular knowledge points and continuously adjust a student’s learning path based on their interactions. A systematic review of AI-driven intelligent tutoring systems in K-12 education finds that these systems can “monitor student progress, identify difficulties and errors, navigate structured subject content to offer and tailor the difficulty level, thus developing an optimal path for learning.” Researchers at the University of Michigan are developing adaptive chatbots that go further still, carrying out dialogue with students and providing scaffolding based on both the accuracy and the sentiment of their responses, with teachers able to customize the question sequences to match their own instructional goals. With new AI-based adaptive approaches far outpacing research on their effectiveness, how quickly and equitably these approaches can be implemented across schools remains an open question. 

The future for AI and assessment? 

New possibilities and challenges for AI and assessment will continue to emerge as AI and other technologies develop, making it difficult to predict exactly what might happen next. Regardless, some of the benefits and challenges are already clear.  With these challenges in mind, some experts believe that smaller shifts in assessments and instruction are more likely in the next few years rather than a dramatic revolution. As Matt Johnson, a principal research director at  Educational Testing Service (ETS), puts it: “My opinion is that there will be a slow creep of new stuff.”  So far, some of the developments most likely to be a part of that “slow creep” include the use of AI by test makers and teachers to generate test items and tests. But Janet Garcia, CEO of PSI and President of the ETS, sees even bigger changes ahead: “One of the clearest trends I see emerging is the movement away from single-point, multiple-choice exams toward more continuous, real-time demonstrations of competence.” 

It remains to be seen how quickly these kinds of developments in large-scale testing and the assessment of a wider range of competencies might take hold, but, more concerning, it’s far from clear whether changes like these will make things better or worse for students and teachers

Next week: Can Online Platforms and Digital Tools Support More Student-Centered Learning? AI, New Technologies and the Future of Assessment (Part 2)

Unforgetting Histories and Imagining Futures: The Lead the Change Interview with Daisy Salazar-Garza

In the fourth part of this month’s Lead the Change (LtC) interview, Daisy Salazar-Garza discusses her firsthand experience of the inequities in the public education system and the impact this has on students, families, and communities. Salazar-Garza is a Ph.D. student in the School of Educational Studies’ Urban Leadership Program at Claremont University. German is a recipient of the Student Travel Award from the Educational Change Special Interest Group (SIG) of the American Educational Research Association (AREA). The LtC series is produced by co-editors Dr. Soobin Choi and Dr. Jackie Pedota and their colleagues who lead the Ed Change SIG. A PDF of the fully formatted interview will be available on the LtC website.

Lead the Change (LtC): The 2026 AERA Annual Meeting theme is “Unforgetting Histories and Imagining Futures: Constructing a New Vision for Educational Research.” This theme calls us to consider how to leverage our diverse knowledge and experiences to engage in futuring for education and education research, involving looking back to remember our histories so that we can look forward to imagine better futures. What steps are you taking, or do you plan to take, to heed this call? 

Daisy Salazar-Garza: The 2026 AERA theme, “Unforgetting Histories and Imagining Futures: Constructing a New Vision for Education Research,” calls us to draw upon our diverse knowledge and lived experiences to engage in meaningful “futuring” for education. For me, as a Chicana educator, scholar, and first-generation doctoral student, this theme feels deeply personal. It is a call that echoes the lessons my family instilled in me from an early age.

My family, especially my father, taught me about life’s harsh realities and the beauty of resilience through the power of storytelling. Around family meals, during long drives, or in quiet moments on the porch, I listened to stories of our history—stories of struggle, perseverance, and hope. These narratives shaped my understanding of who I am and filled me with a deep sense of pride. They taught me to honor the strength passed down from my ancestors and to recognize that storytelling is not only an act of remembrance but also a tool for transformation.

This foundation shapes how I approach educational research. To truly “unforget” our histories, we must center the voices and stories that have been pushed to the margins. Leveraging our collective knowledge requires valuing the lived experiences of those most impacted by educational inequities. By empowering communities with a vested interest in the future of education, we can imagine possibilities rooted in justice, equity, and collective empowerment.

As I continue to heed the 2026 AERA theme, I draw upon this legacy of storytelling and historical remembrance to inform my work. Understanding the social, economic, political, and racial contexts that have shaped communities is essential to serving them authentically—honoring both their strengths and the systemic injustice they have endured. Through remembering and honoring these histories, we can envision and build educational spaces that celebrate our roots and uplift our voices. In doing so, we can cultivate a just and hopeful future that directly confronts the inequities we must transform. 

Source: Bank Street Graduate School of Education website

LtC: What are some key lessons that practitioners and scholars might take from your work to foster better educational systems for all students?

DSG:  Recently, I had the privilege of working with Dr. Osworth to co-author “Outward Portrayals of Equity: An Examination of Diversity, Equity, and Inclusion in Los Angeles County School Districts.” In 2024, we collected data from 80 public school districts to assess the current state of DEI commitments in Los Angeles County districts.

From this work, several lessons emerge for practitioners and scholars in the field of Educational Change. First, our findings highlight the need to look beyond surface-level portrayals of equity and focus on how DEI policies are enacted in districts and schools. Value statements made toward DEI without creating infrastructure through policy to support the work does not address the racialized nature of the structures within school districts (Salazar-Garza & Osworth, 2026). Second, schools as organizational systems often reproduce existing inequities. Recognizing these structural patterns is the first step toward redesigning them. Ultimately, transformative change needs to occur at the systemic level to disrupt and dismantle entrenched systems of inequality (Salazar-Garza & Osworth, 2026). Finally, pairing enforcement mechanisms, such as culturally responsive teaching, with policy can contribute to conscious efforts to alter internal patterns of organizational inequity (Salazar-Garza & Osworth, 2026). 

Together, these insights emphasize that fostering educational change requires both reflective practice and systemic change. Equity efforts translate into improved student experiences and outcomes when we can redesign structures enacting patterns of inequity. 

LtC: What do you see the field of Educational Change heading, and where do you find hope for this field for the future?

DSG: As a scholar-practitioner, I believe the field of educational change is heading toward a deeper partnership with people who are the most affected by our current educational realities. By centering the voices of teachers, students, families, and communities, we can inspire real progress. Change comes when research and practice work go hand in hand to bridge the gap between theory and lived experience. 

Given the current polycrisis world we’re navigating, where social, economic, and environmental challenges continually intersect, I find hope in collaboration within the field of education (Virella, 2025). Dr. Virella’s Crisis as Catalyst: Equity-Oriented School Leadership During Difficult Times reminds me that even in moments of uncertainty, there is great potential for transformation. As a school principal who was interviewed and whose narrative is present in this research alongside numerous other school leaders, it is a reminder that practitioners are engaging in powerful practices that are meeting the needs of our present moment. It is also a call to action that we can study practices from the field, derive key lessons, and create frameworks that empower and sustain more educators across the field.

What gives me hope is seeing more educators and researchers approach their work not just as inquiry, but as partnership with students, families, communities. When our research centers humanity and lived experience, educational change can lead us toward a more just and human-centered system for all students.

References

Salazar-Garza,D. and Osworth, D. (2026) Outward portrayals of equity: an examination of diversity, equity, and inclusion in Los Angeles County school districts. Leadership in Education Racial Equity and the Organization: An Educational Change Call to Action. Frontiers in Education. https://doi.org/10.3389/feduc.2026.1642675

Virella, P. M. (2025). Crisis as catalyst: Equity-oriented school leadership during difficult times. Harvard Education Press.

How innovations in school facilities can address climate change and support learning: Sustainability, students and schooling (Part 3)

What does it take to create more sustainable school facilities? In the third part to this series, Carter Hyde and Hannah Nguyen discuss some of the new developments in facilities and facilities management that schools across the country have implemented to conserve energy, cut costs, and support students’ learning and wellbeing. The first post explored the negative impact that climate change and related disruptions have on students, and the second post focused on how schools are making busing and other aspects of school transportation more sustainable.

This series is a part of IEN’s ongoing coverage of what is and is not changing in schools and education following the pandemic school closures. For more on the series, see “What can change in schools after the pandemic?”  For examples of micro-innovations in other areas, see Access to food and school meals in the US and around the world; Innovations in providing children with food and nutrition; Building Student Relationships Post-Pandemic in School and Beyond; Scanning the Post-COVID Challenges and Possibilities for Access to Colleges and Careers in the US ; New Pathways into Higher Education and the Working World? (Part 2)Tutoring takes off and Predictable challenges and possibilities for effective tutoring at scale.

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Environmental changes are contributing to disasters, crises, and day-to-day conditions that disrupt schooling, increase costs, and undermine students’ health and learning. Combatting these problems is profoundly complex, often requiring difficult trade-offs. Efforts to improve student health and learning environments may conflict with long-term sustainability goals and cost-effectiveness. These tradeoffs force school administrators to weigh the benefits of expensive structural upgrades against smaller, more affordable interventions. Despite the challenges, schools in the US and around the world are taking innovative steps that range from major infrastructure upgrades to homegrown, creative adjustments made by teachers in their classrooms.

A student from John McDonogh Senior High School’s first graduating class since Hurricane Katrina walks past a damaged wall on the way to commencement June 8, 2007, in New Orleans, LA, K12 Dive

Major Infrastructure Upgrades and Renewable Energy 

After salaries, energy represents a critical area for both reducing costs and addressing sustainability. In the US, energy bills make up the second highest cost for school districts, amounting to roughly 8 billion dollars per year. To address these significant expenses, many institutions are moving beyond reactive budgeting and toward strategic roadmaps that help schools set sustainability goals that are aligned with national sustainability targets. Schools can use these roadmaps to help reduce the schools’ energy and water consumption, waste, and greenhouse gas emissions. 

In addition to strategic budgeting, some schools are turning to high-impact technology to reduce energy costs and to promote sustainable practices. For instance, some schools are now putting in place geothermal wells because they offer a particularly sustainable way to heat and cool schools without burning fossil fuels. At the same time, some schools are turning to solar energy so that they can develop their own sources of energy. Though a costly up-front investment, solar panels can help reduce the electrification gap by providing a sustainable way to power schools that reduces costs over time and contributes to better air quality. 

Countries with large with large school electrification gaps tend to have high potential for solar power generation, UNESCO via Gem Statlink

Improving HVAC Systems and the Building “Envelope” 

Beyond energy sources, improvements to the school’s physical “envelope”—the walls, windows, and climate systems—can support student performance. Upgrading old HVAC systems, in particular, provides a way to cool classrooms and create better learning conditions at the some time. As one review of survey data from New York State schools showed, improving HVAC systems contributed to a 2% increase in attendance and a 3% increase in math scores over multiple years. Among other benefits, HVAC improvements can produce better air flow, which reduces the spread of disease and helps students focus. Improving air filtration through the use of air purifiers and portable air cleaners, can also help improve cognition and mitigate illness-related absences. 

At the same time, air conditioning alone is not always a sustainable solution, as these systems can expel hot air outdoors and contribute to global warming. As architect Francis Kere explains, “energy-intensive air conditioning, which expels hot air outdoors, contribute to global warming, which then fuels demand for more air conditioning.” Instead, Kere recommends using passive cooling techniques, such as overhanging roofs to improve air circulation and generate cross-ventilation.

A student leaves the secondary school building built by Pritzker Prize-winning architect Francis Kere, in Kere’s home village of Gando, Burkina Faso, The Japan Times via Reuters

Schools can also make improvements in the outdoor environment to address sustainability. For instance, planting trees on asphalt playgrounds can reduce temperatures through shading, and painting roofs white, adding vegetation of false ceilings, and creating more green spaces can reduce the “heat island” effect.

Balancing Lighting and Temperature

Lighting represents another area where schools need to consider potentially conflicting benefits. In a 2020 review of 130 studies, lighting was found to be one of the environmental factors that had the biggest impact on students’ learning and wellbeing. Maximizing the amount of natural light in classrooms, in particular, has been shown to have a number of benefits including reducing eye strain, boosting mood, and improving cognition. Although artificial lighting may lead to lower motivation and eye strain, research reviews highlight that students in classrooms with more natural light showed higher productivity, engagement, and attention level. Despite these benefits, some classrooms may still suffer from poor lighting or rely too heavily on  artificial sources. This problem is exacerbated by the fact that, in an effort to reduce energy consumption and costs, many schools have implemented LED lighting in classrooms. 

In addition to finding a balance that maximizes the benefits of natural lighting with the costs, schools have to take into account the fact that both too much direct sunlight and too little light can negatively impact student engagement and impair test scores. Furthermore, schools have to take into account mitigating factors, including structural limitations that prevent some classrooms from relying on daylight, as well as the increases in classroom temperature and energy costs that come with larger windows. One way to deal with these challenges is to use temperature-treated or double-paned glass to provide light while keeping the heat out. The use of window shades may also be useful in eliminating glare. 

Teachers’ Role in Sustainability

Whether or not schools have the resources for major structural changes or sustainability upgrades, teachers play a key role in striking the right balance between lighting and temperature and supporting both sustainability and an optimal learning environment. For instance, teachers have demonstrated a host of creative ways to combat heat and to improve the environment including using fans, creating window art to reduce glare, and turning off heat-generating electronics. In some cases, the simplest solutions may be the best solutions, as teachers in schools located in temperate regions with good air quality can open windows to allow for natural air flow.

Improving Facilities in “Old” Buildings

Along with so many natural disasters and rising temperatures, many communities face a long-standing demand to improve aging or inadequate school buildings. One of the most recent assessments of school infrastructure in the US shows that it would cost almost 200 billion dollars to bring all K-12 school buildings into good overall condition and the American Society of Civil Engineers gives the condition of America’s 100,000 public school buildings an overall grade of D+. Estimates suggest it would take as much as 85 billion dollars a year to make the needed improvements. On top of that, the costs of deferred maintenance continue to compound with every one million dollars worth of needed improvements deferred in one year leading to  $1.08 – 1.12 million in costs the following year.

In the US, the burden and responsibility for addressing this problem falls on individual school districts and communities, but many lack the resources to pay for the significant upfront costs of building new facilities. Some districts have tried to mitigate these costs – and the sustainability problems that new construction often produces – by repurposing older buildings. For instance, struggling malls have opened the doors to charter schools as tenants to use the empty spaces. One charter school in South Carolina opened up in a former JC Penny Store. In Massachusetts, instead of building a new high school, one district opted to co-locate a school in the community’s senior center. center down the road. 

Liberty STEAM Charter School in Sumter, S.C., is one of many schools that have opened up in malls across the nation, The New York Times

For more information regarding infrastructure and sustainability, see:  

Officials promised all NYC classrooms would get air conditioning. 1 in 5 still lack it. (ChalkBeat

Is your NYC school using the air purifiers that were distributed during COVID? (ChalkBeat) Why improving air quality in schools would minimize the threat of bird flu spread (ChalkBeat) California’s K-12 schools often lack sufficient shade and natural surfaces (UCLA Luskin School of Public Affairs)

Measuring schoolyard heat one step at a time (UC Davis College of Agricultural and Environmental Sciences)

Alabama is Bringing Forests Into Schoolyards (Governing)

What Works and For Whom? Effectiveness and Efficiency of School CApital Investments Across the U.S. (Biasi, Lafortune, & Schonholzer)

‘A place for kids to play and a place to store water’: the stormwater capture zone that is also a playground (The Guardian)

NYC to install solar panels at 72 public schools by year’s end, helping kids learn about clean energy (Daily News)

What Will Districts Do With All Those Empty School Buildings? Some Look to Fill Them With Younger Kids (EdSurge)