U.S. Education Secretary Linda McMahon recently defended the use of artificial intelligence (AI) in K-12 classrooms during a television interview, citing a private school in Austin, Texas, as an example of successful implementation. McMahon highlighted Alpha School, co-founded by an AI entrepreneur, where students reportedly spend two hours daily on personalized learning with the support of AI-driven platforms, monitored closely by teachers.
When questioned about whether this approach might be turning students into "guinea pigs" for unproven technology, McMahon responded that Alpha School’s model is “working wonderfully” and noted that the program has been in place for several years. However, critics emphasize that Alpha School’s methods have not undergone independent evaluation, and as a private institution, it selects its student population rather than serving a broad demographic.
Research on AI use in classroom settings presents a more complex picture. A recent study involving more than 26,000 Chinese students from grades 7 to 12 found that while AI increased homework scores, it corresponded with a significant decline in monthly exam scores—up to 20 percent over six months—and reduced performance on high-stakes entrance exams by as much as 24 percent. Researchers suggested that some students might be relying too heavily on AI to complete assignments without deeper learning.
Educators and experts express concern that the rapid introduction of AI in classrooms is often driven by Big Tech companies, which play active roles in shaping education policy and standards. These companies provide funding for research, teacher training, and curriculum materials while lobbying for expanded roles for technology in schools. This integration has raised questions about whether priorities driven by industry align adequately with educational goals.
Experts emphasize the need for a comprehensive framework to assess educational technology, going beyond simple measures of efficacy such as test scores. Natalia Kucirkova, a professor of early childhood and development at the University of Stavanger in Norway, proposes an evaluation based on five criteria: efficacy, effectiveness, ethics, equity, and environment. She argues that without confirming both efficacy—academic outcomes in controlled trials—and effectiveness—the tool’s practical use in classrooms—other factors like data privacy and equitable access should not be considered.
Kucirkova advocates for involving teachers, students, and early childhood professionals in the development of educational technologies to ensure these products meet real classroom needs rather than serving primarily commercial interests. She also calls for increased government support to develop AI tools as a public good, citing "Sesame Street" as an example of a collaborative, partially publicly funded media project that successfully delivered educational content.
Norway offers a more cautious approach to AI in schools, restricting its use for children under 13 and gradually expanding access under supervision for older students. While Kucirkova notes that Norway’s more homogenous and high-trust social context differs from the United States, she suggests this model could inform policy debates elsewhere.
As AI technologies continue to evolve and enter educational settings, experts contend there is an urgent need for clear standards and regulations to ensure that innovations truly benefit student learning without compromising ethical and equity considerations. Without such oversight, critics warn that technology companies may continue to shape education without sufficient accountability, leaving students as test subjects in a rapidly shifting landscape.