This issue brief is the second in a summer 2024 series of products from the Center for American Progress that will focus on policy recommendations to enhance the use of technology in K-12 public schools.
During the 2023 back-to-school season, the potential of artificial intelligence (AI) to revolutionize or disrupt education—depending on your perspective—was all over media headlines.1 While the excitement and consternation around ChatGPT—which was released in November 20222 and initially banned from many school districts3—may have peaked last year, AI remains front of mind among education philanthropists4 and education technology experts.5
AI’s ultimate impact on education is an important question for the nation’s school systems. As AI tools have continued to evolve, the implications for education go far beyond ChatGPT and other language learning models, with predictions that AI will be used for personalized learning, assisting teachers with routine and administrative tasks, assessment and data analysis, and likely a range of additional purposes not yet imaginable.6
Learning, the brain, and AI: Understanding how humans learn
Beginning in infancy, people have a remarkable capacity to learn about the world around them.7 While humans are born relatively helpless compared with many other species, they are able to develop the knowledge and skills to thrive in a dizzying diversity of environments.8 This ability to learn, which researchers term “neural plasticity,” combined with humans’ social nature, provides them with the motivation and skills to understand and navigate the world.9
Throughout human history, the mechanism for learning has included a mixture of observation, play and imitation,10 and social learning with both peers and adults.11 While it may seem odd to consider thousands of years of evolution in the discussion of a cutting-edge 21st century technology, understanding how human brains are built to learn is crucial to determining when AI is helpful and when it is harmful.
Keeping this in mind, and in addition to the many other ways experts analyze the impact of AI on education, it’s important to think critically about whether adoption of AI tools will further divorce students from how their brains are primed to learn through modalities such as movement, play, and social interaction.
The interaction between learning science and AI technologies will have profound implications for the future of education, particularly as it relates to equity. As discussed in a later section, the demands of modern schooling already push aside or ignore the biological, cognitive, and social needs of children, especially low-income children and children who are Black, Indigenous or other people of color (BIPOC). It is important to be cognizant of this when developing and implementing AI for use in the classroom.
Play is crucial for learning
Play is sometimes thought to be in tension with academic learning, but any good educator knows that this is a false dichotomy. The cognitive benefits of unstructured or imaginative play for children (and adults) are diverse, including improved emotional regulation, problem-solving skills, perseverance, and executive functioning skills—all of which have value in an academic setting.12
Play also has more direct academic benefits, such as improving language13 and correlating with future math achievement.14 In addition, a variety of pedagogical approaches incorporate children’s natural curiosity15 and capacity for play into instruction,16 and many—including the Montessori method,17 project-based learning,18 and active learning19—are associated with positive academic achievement outcomes.
Unfortunately, too many children have scarce opportunities to play. Children’s unstructured play time outside school declined significantly in the late 20th century compared with previous generations, due in large part to a shift in parenting norms,20 and elementary-age students only get an average of 24–28 minutes of recess per day (depending on grade) while at school.21 Play, movement, and face-to face-time are also being crowded out by screen usage, especially for older children: The average teen is using screens for entertainment for more than eight hours per day.22
Recommendations for school and district leaders and policymakers to support play and hands-on learning:
- Avoid adopting new AI technologies that will further crowd out opportunities for play-based and hands-on learning.
- Use AI in the classroom as part of play-based learning or as a tool for hands-on learning, when appropriate and helpful.
- Develop AI tools that harness children’s propensity for unstructured play and the effectiveness of learning strategies that incorporate active engagement.
- Consider developing AI tools that integrate movement as opposed to additional sitting time.
Relationships are central to learning
While modern school environments don’t closely mimic the learning environment of our hunter-gatherer ancestors, which featured significantly less direct instruction and lots of time spent in mixed-age groupings and were primarily self-directed,23 today’s classrooms do maintain a social learning component through the presence and primacy of teachers and peers in the learning process. As humans are a “hypersocial species” whose need for belonging is a strong driver of motivation and behavior,24 it would be devastating for children if schools used AI to take away kids’ main reported reason for enjoying their time at school: interactions with their peers.25 Beyond enjoyment, children’s need for social interaction is central to their social and cognitive development.26
Schools can integrate relationships into the classroom through a variety of strategies, many of which are linked to increased academic achievement. For example, a meta-analysis found that students benefit both socially/behaviorally27 and academically28 from peer tutoring strategies. Group learning has also been shown to improve decision-making skills,29 and, perhaps counterintuitively, collaborative learning has been shown to be an effective strategy for personalizing learning.30 Similar to relationships with peers, positive relationships with teachers can ease students’ transition into K-12 schooling,31 increase engagement,32 improve motivation,33 and foster positive academic outcomes.34
While AI technology is quickly evolving to effectively deliver content, given the facts about the social nature of humans, removing learning from its social context would likely backfire.
Recommendations for school and district leaders and policymakers to support social relationships in learning environments:
- Avoid using AI technologies in ways that further reduce social interaction in the classroom.
- Avoid premature use of AI tools that mimic human interaction; for example, a chatbot that can’t understand how to respond to a kid’s question is going to be frustrating.
- Find ways to use AI that enhance relationships—for example, providing the opportunity for teachers to give each student one-on-one or small-group time or using tools that provide opportunities for students to work together in pro-social ways.
Other cognitive science considerations in design and use of AI
Many educational technology tools already can and do incorporate principles of the cognitive science of learning, and AI opens up new avenues to do so. Other organizations and entities, such as the Institute of Education Sciences,35 Deans for Impact,36 and the National Academies Press,37 have illustrated ways learning science can be applied in classrooms, and the U.S. Department of Education recently released a guide for developers creating AI educational technology tools.38
While many of the strategies that these organizations detail can easily be applied to AI, others don’t lend themselves well. For example, AI can provide opportunities for spaced practice and forced recall and to practice a discrete skill, but it cannot yet identify the reason for a student’s error and provide a concise clarifying explanation.39 It also is not ready to provide students with personally meaningful reasons why they need to learn or understand something, which is one of the key drivers of student motivation for learning.
Recommendations for school and district leaders and policymakers to take into account regarding cognitive science:
- Ask AI providers during the adoption process whether and how they integrated cognitive science and evidence-based practice into their design.
- Train teachers to continue to provide their students with motivation, meaning, and purpose, even if AI is providing some direct instruction in the classroom.
Equity implications of failing to incorporate learning science into AI decision-making
As with all educational technologies, AI shows promise for reducing some inequities, but it could exacerbate others. The below sections discuss some of the risks of expanding AI tools and ways to ensure that AI adoption decisions are made with equity at the forefront.
1. AI may deepen the digital divide
Expanded use of AI tools has the potential to exacerbate the digital divide and other educational inequities—implications that education and policy organizations have capably covered.40
While pandemic relief funds made noteworthy investments in internet connectivity,41 there exists a broader digital divide in how schools leverage such technologies that won’t change without significant shifts in policy and practice. Students at affluent schools tend to use technology for creativity,42 research and analysis, and experimentation, while students at lower-income schools are asked to use technology for narrower purposes such as repetitive drills.43 In starker terms, students at affluent schools get to use technologies in ways that facilitate hands-on learning that takes advantage of their curiosity and playfulness, rather than suppressing it.
Education technology standards for digital literacy reflect the importance of using technology to assist and facilitate this type of higher-level learning.44 Unsurprisingly, given their greater access to this type of work and education, higher-income students and white students also have higher levels of digital literacy than their counterparts who are low income or students of color.45
Without thoughtful implementation of AI tools, digital literacy disparities will persist and even worsen. Given the transformative effect that AI technology is expected to have on the economy and workforce,46 AI-specific digital literacy will be an incredibly important and valuable skill for today’s K-12 students. As with technologies that came before, the way schools use AI in the classroom will be just as important as the level of access students have to AI tools.
However, this is not an argument for rushing to expand the use of AI tools in low-income classrooms. As with other available educational technologies,47 the speed of AI advancement makes it difficult to discern which tools are effective, and the quality48 and evidence basis49 is likely to vary significantly. What’s more, many examples reveal racial bias in existing educational technology50 and AI51 tools. AI developers and purchasers will need to exercise considerable intentionality and awareness to ensure that they are not bringing educational tools into schools that exacerbate racial biases.
2. AI may further reduce access to learning opportunities that incorporate cognitive science principles
The fact that students at low-income schools are asked to use technology in narrow and repetitive ways reflects a broader disparity in their educational experiences. Researchers found that students in low-income schools in Colorado experienced a narrower curriculum, fewer opportunities for choice in their learning, more time during which they were expected to sit quietly and wait, and less time for movement and physical activity.52 Low-income students are also given less exposure to grade-level work, even when they have shown they are capable of completing challenging assignments,53 and tend to have less recess time than students in more affluent schools.54
Taken together, this means that students attending low-income schools experience a larger “evolutionary mismatch”:55 the difference between the learning environment provided and the one that humans have evolved to learn within. Schools often use educational technology available today to keep students sitting and quiet and for drilling and other passive forms of learning. One risk of increased use of AI educational technology tools is that they will be used in the same ways and worsen this trend.
3. AI may disrupt safe and supportive learning environments for BIPOC students
About one-third of Black and Hispanic students attend schools with a high concentration of students in poverty,56 where they are more likely to experience a learning environment with a high level of evolutionary mismatch. But regardless of income, Black students and other students of color face additional obstacles as a result of racial inequity and injustice.
Teachers overall tend to have less-positive perceptions of their Black students, more negative interpretations of and responses to their behavior,57 and lower expectations of their academic abilities.58 Black students are also disproportionately suspended from school for minor infractions compared with their white peers who exhibit similar behavior.59
Unsurprisingly, Black students tend to accurately perceive their teachers and the school climate and culture as unfair.60 Black students are also more likely to report that they do not feel a sense of belonging at school,61 which is correlated with motivation and a number of positive school-related outcomes.62
While there isn’t the same breadth and depth of scholarship about the school experiences of students of other races and ethnicities, research on Latino and American Indian/Alaska Native students finds similar themes of negative expectations and schools that too often fail to meet students’ and families’ needs through cultural competence and quality instruction.63
Humans’ hypersocial nature and the importance of positive relationships aren’t going away anytime soon. Safe supportive schools in which all students, including BIPOC students, have positive relationships with their teachers are a foundational condition for learning and should remain a priority for policymakers and education leaders concerned about racial equity. Because this work is hard, slow, and complicated, it can be all too easy to overlook when an exciting new technology such as AI promises to disrupt education, but that would be a serious and costly mistake.
Researchers consistently find that having a Black teacher is associated with a number of positive academic and nonacademic effects, particularly for Black students64—unsurprising given that relationships are an important, maybe even the primary, motivator for all types of learning. Black teachers are also more likely to make space to affirm Black students’ identities and abilities, bolstering student-teacher relationships.65
Education leaders and policymakers who want to understand the best way to bring new and emerging technologies developed using AI into the classroom should build on these learnings. Rather than focus on the technological tools in isolation—or worse, crowd out opportunities for meaningful and positive teacher-student relationship building—they should look to successful BIPOC-led nonprofits that offer opportunities for meeting role models and building relationships while also increasing digital literacy. Black Girls Code66 and the Hidden Genius Project67 provide examples of these types of models.
Recommendations for school and district leaders and policymakers to boost equity and support low-income and BIPOC students:
- Tread carefully before implementing AI tools widely in low-income schools; assess whether new tools enhance the learning environment in ways that work with how students learn best.
- Ensure that access to humans never becomes an educational luxury; be wary of AI as a cost-cutting tool or a replacement for teachers, paraprofessionals, or tutors, especially in underresourced schools.
- Find ways for students at low-income schools to develop AI literacy and prepare them to access AI-related jobs and to use AI tools that are prevalent in the workforce.
- During the adoption process, ask AI providers whether they considered diverse perspectives and needs in their design to ensure that the technology itself isn’t biased. Consider using existing frameworks for this type of analysis, such as the Edtech Equity Project’s product certification68 or AI in Education Toolkit for Racial Equity.69
In addition, federal policymakers at the U.S. Department of Education should use their existing statutory authority to continue to regulate and issue guidance in ways that mitigate concerns and risks related to AI for K-12 students.70
Conclusion
Technology has always been most successful when it works in concert with human tendencies and behavior; ask anyone who spends too much time on social media. And just as a young child won’t learn language as well from a voice on the TV as from the voice of a parent, even advanced AI technologies can never usurp the need for human connection and the learnings that come from unstructured play. AI will undoubtedly have a place and role in the future of education, but policymakers and educators must be careful to preserve a classroom environment that reflects students’ needs and does not assume that humans’ bodies and minds can adapt as rapidly as the technologies being employed.