Artificial Intelligence

From Local Problems to Community Solutions: Join the Fall 2026 CIDDL AI Community Challenge

What could students improve in their community if artificial intelligence became a thought partner rather than an answer machine?
The Center for Innovation, Design, and Digital Learning (CIDDL) invites students and teachers in Grades 7–12 to answer this question through the Fall 2026 AI Community Challenge. Teams across the nation will identify a consequential local issue, investigate its causes, and design an evidence-informed solution with support from artificial intelligence (AI). The challenge places human reasoning at the center of every submission.

Reimagining Learning Through AI and Extended Reality

The brief begins with context on the growing role of artificial intelligence (AI) and extended reality (XR) in supporting students with disabilities and the opportunities and challenges these technologies present for educators.

Designing AI-Integrated Learning Experiences for Pre-Service Teachers: A Real-Classroom Example

Artificial Intelligence (AI) is no longer a futuristic concept but a present reality that is reshaping how we teach and learn. Dr. James Basham, Yerin Seung, and I recognized that for pre-service teachers, developing a proactive attitude and the ability to leverage AI are fundamental competencies they must possess before entering the field. We designed our course to move beyond mere tool usage, aiming to foster a deep-seated AI literacy that balances technological benefits with pedagogical integrity. This post explores how we integrated AI into our curriculum to prepare the next generation of educators for a tech-driven classroom.

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?

Signal or Noise? Sorting Through AI at ISTELive and ASCD Annual 2026

I went into ISTELive and ASCD Annual 26 expecting AI to show up often. I did not expect it to show up everywhere I turned, in the session catalog and on the expo floor alike. As a Graduate Research Assistant supporting CIDDL, the Center on Inclusive Design and Innovation in Learning, I work on AI and assistive technology research daily. I am not AI averse. Even so, the sheer volume at this conference gave me pause. This post is not an argument for or against AI in schools. It is simply a look at the numbers, drawn from the conference’s own program search, with a few observations as an attendee.

young boy working next to a laptop writing on a pad of paper

Episode 3: Rethinking AI Literacy Through Human Agency

This episode asks a related question: What does it mean to be AI literate while remaining an active human agent?

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.

Vibe Coding for Special Educators: Building Custom Classroom Tools Without Code

What if the most powerful assistive technology tool for your classroom was not something you ordered from a catalog but something you built yourself, in an afternoon, without writing a single line of code?

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

Tag: Artificial Intelligence