The core purpose of education is to foster meaningful learning: developing students’ knowledge, skills, and critical thinking. Thus, the most pressing question is how ubiquitous AI assistance affects student learning and engagement with course material. There are valid concerns that easy access to generative AI may encourage academic shortcutting at the expense of learning. Writing an essay or solving a problem set is not busy work; it is structured adversity that develops reasoning, creativity, and resilience. If AI tools simply hand students the answers, they risk short-circuiting that developmental journey. Indeed, early evidence suggests some students are becoming less engaged in the learning process when AI is there to do the heavy lifting. This attitude is troubling: if a generation of students concludes that studying is futile because a chatbot can do it for them, education could face a crisis of engagement.

As educators, we’re constantly bombarded with new technologies promising to revolutionise our classrooms. Artificial Intelligence has certainly generated its share of both excitement and skepticism (and let’s be honest, a fair bit of eye-rolling too). However, beyond the debates and theoretical discussions, there are practical, immediate applications that can genuinely enhance our teaching practice today.

At Stanford HAI, we believe AI is poised to be the most transformative technology of the 21st century. But its benefits won’t be evenly distributed unless we guide its development thoughtfully. The AI Index offers one of the most comprehensive, data-driven views of artificial intelligence. Recognized as a trusted resource by global media, governments, and leading companies, the AI Index equips policymakers, business leaders, and the public with rigorous, objective insights into AI’s technical progress, economic influence, and societal impact.

Ethnologue is a global voice. We exist to help you understand more about the people of the world, and how each language community is distinct.

AI, when intentionally integrated, offers unique opportunities to deepen critical thinking. AI-powered platforms can support inquiry-based learning, providing students with immediate feedback on the logic and coherence of their arguments or exposing them to multiple perspectives on contentious issues (Luckin et al., 2016). Advanced models can simulate debates, challenge students with counterarguments, and prompt metacognitive reflection: “Why do you believe this? What assumptions are you making? What evidence supports your claim?” In these cases, AI becomes a “thinking partner” rather than a shortcut or crutch.

While people who have spent years cultivating their writing skills might bemoan the arrival of AI-assisted writing, there is also a much more optimistic way to view these changes. Until now, the ability to write well was inherently elitist. People fortunate enough to have the time and financial capacity to pursue higher education were better positioned to produce excellent writing.

The current research landscape may be messy and contradictory, but it illuminates a crucial truth: the impact of AI on education isn’t predetermined by the technology itself—it’s determined by the educational system we choose to implement it within.

We thought it would be helpful to put together a glossary with definitions of some of the most important words and phrases that we use in our articles.

The AILit Framework proposes a shared vision that teachers, education leaders, education policymakers, and learning designers can use to advance AI literacy in schools. The draft competences are organized into four domains—engage, create, manage, and design—that define what every student should know and be able to do in an age of AI.

It is widely acknowledged that continuous professional development (CPD) enhances the quality of teaching. However, there is relatively little high-quality research on CPD initiatives in low-resource contexts. This report has identified 12 key principles that contribute to the most successful CPD opportunities. It highlights challenges such as a lack of high-quality tools and resources, as well as an insufficient focus on student well-being.

Based on our comprehensive risk assessments, we've found that AI companion tools pose unacceptable risks to children and teens under age 18 and shouldn't be used by kids, regardless of whether the tool is intended for use by kids or not.

When I compare the 7 years I had battling the cellphone in the classroom, vs almost an entire year of phone free schooling, there is no comparison. Our kids are smarter, more social, and more motivated to do the things they actually want to accomplish in this world when they don’t have a pavlovian vibration derailing their attention every 20 seconds.

If AI allows students to automate routine cognitive tasks – like information retrieval or ensuring that verb tenses are consistent – it doesn’t mean they’re thinking less. It means their thinking is changing.

Teachers and caregivers can support children who are highly sensitive to the school environment and their emotions.