As AI Transforms education, new article highlights the human dimensions of teaching

 

As artificial intelligence and digital technologies continue to reshape education, the role of teachers is becoming increasingly complex and demanding. A new article published in ECNU Review of Education (https://journals.sagepub.com/doi/10.1177/20965311261421964) on May 13, 2026, by Andreas Schleicher of the OECD explores what constitutes quality teaching in the age of AI and argues that the future of education depends not only on technological advancement, but also on the human qualities of teachers.

Expectations for teachers have always been high and continue to grow. Teachers are expected to possess deep subject knowledge, understand diverse learners, and apply effective pedagogical strategies. Beyond these traditional responsibilities, they are also expected to respond to students' varied needs, promote inclusion and social cohesion, and foster collaborative learning environments. In addition, teachers today are increasingly expected to serve as role models for lifelong learning. Students are more likely to develop lifelong learning habits when they see their teachers continuously expanding their own knowledge and questioning existing ideas.

The article highlights how AI and digitalization have introduced new challenges for teachers. These include managing information overload, addressing issues such as plagiarism, and protecting students from online risks including fraud, privacy violations, and cyberbullying. Teachers are also expected to help students become critical users of digital technologies and informed consumers of online information. In this context, teaching extends far beyond academic instruction.

Looking ahead, the article presents AI as a powerful but neutral tool that could reshape educational opportunities. According to the author, AI has the potential to make learning more accessible and better tailored to individual learners' needs. It may also create more flexible learning pathways, allowing learners greater control over what, how, and when they learn. At the same time, however, the article stresses that AI is not inherently beneficial. It can amplify both effective and ineffective educational practices. AI may help reduce inequities in some contexts while reinforcing them in others. Although it can support inclusion through adaptive learning opportunities, it may also deepen existing inequalities, as seen during the pandemic. Similarly, AI can help teachers design innovative learning experiences, but it may also limit teacher autonomy by encouraging reliance on pre-set algorithms or scripted teaching methods.

A central argument of the article is that human capacities remain essential in education, particularly in areas where technology has clear limitations. Teachers need strong social and emotional competencies to effectively support students. The author notes that many people attribute their success to teachers who provided emotional support, showed genuine care, or served as role models. These dimensions of teaching are difficult to measure, yet they are fundamental to student development and well-being.

In addition to emotional competence, teachers need professional judgment to navigate the complexities of classroom practice. Classrooms are described as dynamic environments shaped by diverse learners, limited resources, and unpredictable challenges. Teachers must therefore combine subject knowledge and pedagogical expertise with adaptability, creativity, and responsiveness.

In this sense, teaching is portrayed as both a science and an art. On the one hand, effective teaching draws on research-based knowledge of learning processes and pedagogical strategies. On the other hand, it requires adaptability, creativity, and sensitivity to the unique needs of each classroom. Teachers must constantly make complex decisions in dynamic and often unpredictable environments, balancing curriculum demands with students' individual differences and emotional needs.

Ultimately, the article concludes that the future of teaching lies in preserving the human dimensions of education while thoughtfully integrating technological advances. Teachers are encouraged to act as designers of learning experiences, critical guides in a digital world, and role models for students. By balancing technological innovation with human judgment and empathy, teachers can support meaningful and equitable learning in an increasingly digital society.

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Journal

ECNU Review of Education

DOI

10.1177/20965311261421964 

The absence of gender and racial minorities often goes unnoticed in the classroom

 During a staff meeting we may look around to take account of who is present—an observation that could consider the race or gender of who is in the room. But would everyone notice a complete absence of women, colleagues of color, or even men, in these settings?

Probably not, shows a new international study by a team of psychology researchers. 

A series of surveys and laboratory experiments conducted in the United States and Israel finds participants quite often failed to notice when men, women, and racial minority groups were absent from certain settings, including university campuses, kindergarten classrooms, and academic conferences. This bias was found regardless of political ideology and was evident even among participants from the same minority group. 

Moreover, across these studies, participants were more likely to notice when even one woman or member of a racial minority group was present than they were to spot the complete absence of a female, male, or a non-White person—depending on the context. They were also more likely to notice the absence of the majority group than the minority group—for instance, participants were more likely to notice the absence of women among kindergarten teachers, where they compose the majority, than they were the absence of men, who are a minority in the profession. 

“These findings suggest that underrepresentation can be hard to see—regardless of who you are,” says Rasha Kardosh, a postdoctoral fellow at New York University and the lead author of the paper, which appears in the journal Proceedings of the National Academy of Sciences. “People often notice who stands out, but not who is missing altogether, with these blind spots occurring in everyday settings.” 

The study included an examination of participants’ ability to detect the absence of female neurosurgeons—a STEM profession in which women are less represented relative to men—and the absence of men among kindergarten teachers, who are predominantly female.

“The results reflect a broader feature of human attention: people tend to notice what is in front of them, while absence requires more deliberate attention,” adds Ran Hassin, a professor at the Hebrew University of Jerusalem and one of the paper’s authors. “A person might attend a conference, read an article, or move through the workplace without realizing that an entire group is absent.”

It’s been long established that the human mind is tuned to what is present and is unlikely to notice, consider, or learn from what is not—in other words, from what is absent. However, the circumstances of when and how this phenomenon takes place are less understood. 

To address some of these questions, the research team, co-led by NYU’s Yaacov Trope, conducted a series of experiments in which American participants were asked about the presence or absence of different groups based on texts they read or on faces they were shown on a computer screen:

• In one text experiment, participants read a short article that quoted six expert neurosurgeons. Some participants read a version in which all six experts were men. Others read a version that included five men and one woman. Afterward, participants were asked about the experts. Most failed to notice when no women were quoted at all, but they were much more likely to notice when even one woman was included.

• In one visual experiment, female and male American participants viewed blocks of faces that, as a whole, largely mirrored the prevalence of each social group in the US population. The test block varied among the participants: in one condition, White faces were absent and in the other Black faces were absent. Participants were then asked about the group that was absent in their condition. Participants were 14 times more likely to notice when White faces were absent than when Black faces were absent.

• In an experiment of classroom settings, participants were shown visuals of teachers and asked if they noticed the absence of male or female teachers. Participants were far less likely to notice the absence of male teachers than they were female teachers. 

Across the experiments, participants failed to detect the absence of the minority demographic group in that context. Notably, this finding held across demographic and ideological differences, including among female and Black participants when their demographic was the minority group in a given experiment. In addition, participants were more likely to notice the absence of White faces than they were Black faces. Notably, neither ideology nor social attitudes had an impact on these perceptions. The same held, conversely, for the classroom experiment—two-thirds of the participants did not notice the absence of a male teacher.

“Because this blindness appeared across the political spectrum and even among people who themselves belong to minority groups, it appears that the effect is not about prejudice or political ideology, but about shared expectations regarding who is typically present in different social settings,” observes Trope.

The experiments were supplemented by three surveys—with the aim of detecting whether or not respondents recognized the absence of minority groups in real-life professional or educational settings. The researchers surveyed faculty, undergraduate, and graduate students at Hebrew University and attendees at an international academic conference held in New York City. 

Overall, the majority of those surveyed in both settings gave responses that were consistent with the experimental outcomes. For instance, 86 percent of the participants reported that they did not attend any talks by a Black speaker throughout the duration of the academic conference. Among these, 52.9 percent reported that they did not notice this absence until they were asked about it by the researchers. Additionally, nearly 90 percent of surveyed employees at Hebrew University reported not noticing the absence of Palestinian colleagues until they were asked. The study’s authors add that once the absence was pointed out, a majority of participants in all the surveys expressed support for addressing matters of representation in their professions and at their institutions. 

“Our research points to a practical lesson: representation is not always obvious to the eye,” concludes Kardosh. “This bias in perception can mask inequality and make our environments appear more diverse than they truly are. Simply prompting people to ask ‘Who is missing?’ may change how they see a setting and how they think about possible responses.”

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Journal

Proceedings of the National Academy of Sciences

DOI

10.1073/pnas.2516655123

Impacts of Free Community College on Degrees and Earnings

This study involves Tennessee Promise, Tennessee’s tuition-free community college program, which preceded similar programs in over twenty states and multiple federal proposals, examining how Promise affected college enrollment and early adult outcomes as the program expanded from a single-county pilot to statewide eligibility. 

Promise increased college enrollment by 5.4 percentage points among 19-year-olds, increased transfers from two-year to four-year schools, increased associate’s degree attainment by 2.9 percentage points among 21-year-olds, imprecisely increased bachelor’s degree attainment by age 24, and weakly increased income from age 21. 

The authors estimate that the program pays for itself under reasonable assumptions about returns to college.

Will The University Endowment Tax Slow Scientific Progress?

 The 2025 university endowment tax hike and other sources of financial pressure may lead the schools that train the most prolific economics researchers to reduce graduate enrollment. Will this affect long-run research output? 

This study uses a novel sample of MIT Economics PhD program applicants to estimate the research value-added of eight elite schools. The estimates mitigate selection bias by controlling for MIT admissions committee rankings—a remarkably strong predictor of long-run research success—and for applicant aspirations as revealed by their application portfolios. 

While rank controls substantially reduce estimated gaps between elite and non-elite graduates, large differences in value-added remain. Graduates of high-tax and other top-eight schools produce 60-75% more impact-adjusted publications than do comparable graduates from non-top-eight US schools. The elite-school advantage is especially pronounced for top five journal publications. Differences in research success within the elite tier, however, are relatively modest. The out-performance of elite-school PhDs does not appear to be explained by editorial connections or peer effects in elite programs.

Generative AI calls for assessment reform in higher education

Higher education must rethink assessment practices in response to the growing integrity challenges posed by generative artificial intelligence (GenAI), say authors in this Policy Forum. They analyzed data on student use of this technology across 20 major public research universities in the United States. The impact of GenAI on higher education is highly debated. In many ways, the technology is making common forms of evaluation, such as tests, projects, or term papers, less reliable as a measure of student capability. 

This highlights the need for a better understanding of where GenAI use is most prevalent and where misuse is most likely to occur. Igor Chirikov and colleagues analyzed survey data from more than 95,000 students across 20 U.S. research universities during the 2023-2024 academic year. Their findings reveal widespread GenAI use among students: roughly two-thirds of students reported using it over the study period, with 37% using it regularly. 

However, usage patterns differed considerably by discipline, with higher adoption in STEM fields. For example, 62% of computer science students reported regular usage, compared with only 24% of students in the arts. Notably, some social science disciplines, such as business and economics, also demonstrated high levels of adoption. Patterns of GenAI-assisted cheating also varied across disciplines. Estimated rates of misuse were generally higher in non-STEM fields, with economics (17%) and journalism (16%) showing relatively high rates, whereas biology (5%) was among the lowest. 

The study also found significant demographic disparities in GenAI use, with higher adoption among male, White, and Asian students than among female and underrepresented minority students. 

Although differences tied to socioeconomic status and disability were smaller, the authors suggest that the findings raise concerns about unequal access to AI tools and literacy. 

Chirikov et al. propose several paths forward. They note that there is no single “AI-proof” assessment model and suggest reforms tailored to individual disciplines. They place a focus on preparing students to use AI responsibly in professional contexts.

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Journal

Science

DOI

10.1126/science.aec5115 

Article Title

Widespread AI misuse by college students

  Large numbers of college students are now using artificial intelligence to complete – and cheat on – their assignments, suggesting that colleges and universities need to change how they are evaluating students, new Cornell University research finds.

An analysis of survey responses from more than 95,000 students at 20 public research universities in the U.S. finds about one-third regularly used generative AI (GenAI), such as ChatGPT or other models to produce text, video or code, when completing assignments, and 9% had used it to cheat.

“Assessment reform is necessary and urgent,” said study co-author Rene Kizilcec, associate professor of information science and director of the Future of Learning Lab. “The fact that students are misusing GenAI is a problem for assessment validity, and that’s a problem for the credibility of university credentials.”

The study, “Generative AI Use and Misuse Call for Assessment Reform in Higher Education,” published May 21 in the journal Science.

Kizilcec partnered with Igor Chirikov, director of the Student Experience in the Research University (SERU) Consortium at the University of California, Berkeley, to investigate AI use and misuse among university students. Each year, SERU sends out surveys to undergraduates, asking students’ opinions on engagement, belonging, affordability and other topics.

The questions regarding GenAI usage, collected during the 2023-24 academic year, was the largest survey of its kind at the time, which enabled researchers to break down responses by discipline.

Overall, 37% of students reported using AI at least monthly, with disciplines requiring large amounts of data analysis showing higher rates of adoption. Rates varied, with 62% of computer science students reporting regular usage, compared to 24% of students in the arts.

The survey also showed demographic differences in GenAI use. Researchers found that 33% of female students reported using GenAI regularly, compared to 45% of male students. People belonging to underrepresented racial minorities also had lower rates of regular use at 29%, compared to 39% of white and Asian students.

These demographic differences may reflect equity gaps in the use of AI tools, researchers said. Additionally, they warn these gaps may widen as GenAI tools become more specialized and costly.

To accurately estimate rates of cheating – something students may hesitate to admit – the researchers used a technique called a list randomization experiment. They provided a short list of statements and asked students how many statements – but not which ones – applied to them. By including an additional statement about cheating on some surveys but not others, they could estimate rates of AI misuse.

Overall, the number of students who had used AI to cheat was lower than anecdotal reports had suggested, researchers said. Daily GenAI users had the highest rate of cheating, at 26%, compared to 7% for those who used it monthly.

“As we expect GenAI use among students to only grow, for better and worse, we also expect that GenAI misuse will grow, which is concerning,” Kizilcec said.

The study’s authors call for changes in how universities are assessing students, to promote academic integrity. They suggest three strategies: professors could go back to highly controlled testing environments – just pen, paper and proctors; they can set clearer guidelines for acceptable AI use; or they can adapt assessments to include AI in ways that show off professional skills.

For additional information, see this Cornell Chronicle story.

Universal free school meals improve student behavior

 

A study published in Economic Inquiry provides new evidence that universal free school meals can meaningfully reduce out‐of‐school suspensions in both elementary and secondary schools.

Using updated information and methods that more accurately account for how policies across US schools were adopted over time, the research builds on earlier conclusions showing null effects. Investigators found that adopting universal meals decreased suspensions by approximately 10% for elementary students and 6% for middle and high school students. These impacts were more pronounced in schools with fewer students who were eligible for free and reduced-price meals before the policies were adopted.

With the COVID-19 pandemic, the US Department of Agriculture granted waivers to schools for serving all students free meals since 2020, but in June of 2022, Congress rejected the federal funding required to sustain universal meals. Many states have returned to the traditional way of providing school meals (free, reduced-price, and full- price), some have decided to continue to provide free meals, and others are analyzing the costs and benefits of adopting universal school meals.

“Our findings highlight universal free meals as not just a nutrition policy, but a tool for improving school climate and equity—especially in schools that previously served fewer low‐income students,” said corresponding author Andres Cuadros-Meñaca, PhD, of the University of Northern Iowa.

URL upon publication: https://onlinelibrary.wiley.com/doi/10.1111/ecin.70066