Artificial Intelligence

Beyond AI Adoption: Why Asking Better Questions About Privacy and Security Matters

Artificial intelligence (AI) has quickly become part of conversations about teaching and learning. Much of the discussion has focused on what AI can do for education—personalizing instruction, increasing accessibility, reducing teachers’ workload, or supporting student learning. As these opportunities continue to expand, schools are increasingly faced with another challenge that receives far less attention: How do we know whether an AI tool is trustworthy enough to use with students?

Students working at tables in a K-12 classroom

What Does the Research Actually Say About AI in K-12 Classrooms?

Artificial intelligence tools are entering classrooms faster than the research base evaluating them can keep up with. For educators, that gap creates a real dilemma: how do you make sound instructional decisions about AI when rigorous evidence remains so thin? This post summarizes a new report from Stanford’s AI Hub for Education, The Evidence Base on AI in K-12: A 2026 Review (Fesler et al., 2026), which offers one of the clearest pictures yet of what we currently know and, just as importantly, what we don’t.

From Blank Page to Literature Review: How AI Can Support Early-Stage Research and Writing Over the Summer

Conversations about AI in education often fall into two camps: advocates who emphasize its potential and skeptics who warn about its risks. Yet both perspectives tend to ask the same central question: Should students use AI? While this question is important, it may not be the most meaningful one for understanding what is actually happening in classrooms. A more productive question might be: What happens to students’ thinking when they use AI, and under what circumstances does AI become more beneficial or risky? This shift moves the conversation away from simple approval or rejection of AI and toward a deeper examination of how learning itself is changing. In our recent paper by Seung and Dr. Basham (2026), Cognitive Offloading in the Age of Generative AI: What Does It Mean for Students With Learning Disabilities? (published in Learning Disability Quarterly), we explore this question through the lens of cognitive offloading, a concept that helps explain how students redistribute their mental effort when using AI.

man sitting at desk looking at his laptop

Cognitive Offloading in the Age of AI: Opportunities, Challenges, and Mechanisms

What New National Evidence on School Phone Bans Means for Special Education Personnel Preparation

Roughly two-thirds of U.S. states have enacted legislation restricting student phone access during the school day, and more than half of countries worldwide have followed suit (D’Addio, 2025; Prothero et al., 2026). Nearly 5,000 schools deployed them by 2026 (Allcott et al., 2026). The pace has outstripped the evidence.

Advancing Writing Outcomes Through AI: Implications for Special Education Teacher Preparation

This brief explores how artificial intelligence can support writing instruction through prompt engineering, feedback systems, and increased access to supports. It highlights how AI can reduce barriers to writing while maintaining student ownership and independence. The brief also provides practical recommendations for integrating AI into teacher preparation programs.

Teacher leads a discussion in a bright classroom, standing beside seated students with laptops open on the table.

AI and Educational Assessment 101

One of the most common inquiries CIDDL receives is about Artificial Intelligence and assessment. The integration of AI throughout the education system is affecting nearly everything educators do daily, from small tasks such as emailing students to planning instruction. But one of the largest concerns educators often have about AI is how to design effective assessments. Well, just like nearly everything else with this powerful technology, the key is to understand the basics and then design to support the most effective human interaction.

Is AI Helping Students Think, or Doing It for Them?

Artificial intelligence is quickly becoming part of students’ everyday learning routines. They use it to generate ideas, summarize texts, solve problems, and even draft full assignments. But as AI becomes more embedded in classroom workflows, an important question often goes unasked: Is AI helping students think, or doing the thinking for them? This question matters because not all uses of AI support learning in the same way. In some cases, AI can extend students’ thinking, provide meaningful feedback, and open new possibilities for learning. In others, it can unintentionally reduce effort, bypass critical thinking, and limit opportunities for growth. The difference is not always obvious, but it is crucial for instructional decision-making.

Group of individuals standing around a conference table

Students Are Already Using AI: What Educators Should Understand About AI Guidance and Support

Recent research highlights an important shift. Students are not waiting for schools to introduce artificial intelligence. They are already experimenting with these tools independently. Understanding how students perceive and use AI helps educators respond thoughtfully and guide responsible use of technology.

Generative AI and IEP Goal Development: Implications for Special Education Teacher Preparation

The brief begins with context on the background of AI integration in education, focusing on special education teachers’ early adoption of generative AI tools. Audiences will learn about the current usage patterns among special educators, the factors that influence their decision to use (or not use) AI tools, and the practical implications for professional learning and teacher preparation. Drawing on Naatz and Ruppar’s (2025) exploratory survey, this brief highlights actionable insights for designing ethical, effective, and inclusive AI training that reflects the realities of classroom implementation and supports teachers of students with extensive support needs.

Post series: Artificial Intelligence