Yerin Seung - CIDDL

Meet the Updated CIDDL Chat: Explore Evidence-Based Resources Through AI

What if you could explore CIDDL’s resources by simply asking a question? With the newly updated CIDDL Chat, educators, families, researchers, and other stakeholders can engage with CIDDL’s resources through an AI-powered conversational interface. During a recent CIDDL Office Hour, Daniel Neugent, a PhD student in Computer Science at the University of Kansas and a Graduate Research Assistant for CIDDL, introduced the updated CIDDL Chat, demonstrated its features, and answered questions about how the tool works.

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.

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.

man sitting at desk looking at his laptop

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

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.

From Debate to Design: Reflections on AI, Cognition, and Learning at AERA 2026

Attending the 2026 American Educational Research Association (AERA) Annual Meeting in Los Angeles, I was struck by how much the conversation around AI in education has evolved. Across sessions, scholars from diverse disciplines engaged in rich discussions about integrating AI into teaching and learning. Compared to last year, the tone felt notably more mature. Rather than questioning whether AI should be used in education at all, there was a growing recognition that AI is already embedded in daily life and learning environments. The central question is no longer whether to use AI, but how to use it well.

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.

Shaping the Future of Special Education: CIDDL at CEC 2026

CIDDL is preparing to head to the Council for Exceptional Children (CEC)’s Annual Convention in Salt Lake City from March 11th to 14th. This convention provides special education personnel (e.g., teachers, administrators, and related service providers) with professional development through interactive sessions grounded in application to students with disabilities. It is a fantastic event that brings together special education professionals to “learn, share, grow, and connect.” The CIDDL team is bringing research and practice with technology and innovation to the conference through demonstrations in the Tech Playground and sessions focusing on technology integration and AI. Be sure to check out these sessions to explore how AI is shaping the future of special education and join the conversation on AI in education. Below, we will share the various sessions hosted by the CIDDL team. RSVP to them through our community and on the convention’s Whova app!

Beyond the Tool: Designing Coherent AI Systems in Education

When conversations turn to AI in education, the question I hear most often is, “If you could recommend one AI tool, what would it be?” It is a reasonable question. Educators are navigating full schedules, expanding responsibilities, and increasing learner variability in their classrooms. With new AI platforms emerging almost weekly, asking for one manageable starting point feels efficient and practical. In a field moving this quickly, there is also understandable pressure to adopt something just to avoid falling behind. But I often pause before answering. Instead of naming a tool, I ask, “What do you need?” That pause is intentional.

Individuals sitting around a table with thier laptops open working and talking

AI Integration and the SAMR Framework: A Practical Lens for Instructional Design

Artificial Intelligence (AI) is poised to transform education at every level (CIDDL, 2024). However, this advancement raises a deeper question: “Is AI strengthening education, or is it pulling it away from its core purpose?”
UNESCO’s 2025 report, AI and the Future of Education: Disruptions, Dilemmas and Directions, addresses this global pivot point head-on. Bringing together scholarly voices, the report examines how AI challenges long-standing assumptions about teaching, learning, and the role of the human teacher. While some chapters point to unprecedented opportunities, others urge caution about the structural, pedagogical, and ethical risks that accompany rapid adoption.
I intentionally highlight three chapters—3, 4, and 5—that speak most directly to classroom practice, instructional design, and the evolving work of educators.

Author: Yerin Seung