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.
Support Students with Disabilities’ Independence with Mobile Devices
This brief examines how mobile devices can support the independence of students with intellectual disabilities as they navigate college campuses and community settings. Drawing on Dr. Hester’s discussion of her collaborative work with Lori Cooney and Dr. Don McMahon, it explains how Google My Maps can be customized according to individual students’ destinations, preferences, support needs, and person-centered plans. The brief also considers how mobile technology can be incorporated into teacher preparation, how educators can develop more balanced perceptions of mobile devices, and what future research is needed to strengthen technology-supported transition and inclusive postsecondary education practices.
CIDDL Research and Practice Brief: Digital Accessibility and Accessible Educational Materials
This brief explores what digital accessibility means in practice, why it matters for students with disabilities, and what teacher preparation programs and school leaders can do to build educator capacity in this area. Drawing on Cynthia Curry’s decades of experience and her current leadership of NCADEMI, the brief highlights the most pressing challenges schools face, and the opportunity to embed. accessibility into existing instructional initiatives, and practical resources educators and preparation programs can use to get started.
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.
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.
Special Education Teachers’ Use of Generative AI
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.
Technology Innovations in Rural Special Education
The brief begins with context on the background of rural special education, highlighting longstanding unequal access to services, evidence-based practices, and representation in research. Readers will learn how Dr. Hott’s work addresses these challenges by combining simple technologies with strong community partnerships to support instruction and behavioral interventions. The brief also shares how her team engages rural schools in meaningful research and coaching, and how teacher preparation programs can foster technology-enabled, relationship-driven approaches that respond to the realities and assets of rural communities.
AI Literacy in Teacher Preparation
As Artificial Intelligence (AI) becomes increasingly integrated into daily life and educational settings, teacher preparation programs face a critical challenge: ensuring that pre-service educators are equipped to navigate, integrate, and critically assess AI in their practice. AI literacy refers to the ability to understand, utilize, and critically evaluate AI technologies, including their functionality, societal implications, and how to engage with them responsibly (Long & Magerko, 2020; Ng et al., 2021). However, many in the education field still approach AI with uncertainty, often viewing it as a potential threat to academic integrity. As Dr. Victor Lee noted, misconceptions about AI’s capabilities, such as assuming it is highly intelligent or inherently subversive, can limit meaningful integration. Without shared understandings, practical frameworks (e.g., AILit Framework, CODE.org), and intentional dialogue, there is a risk of reducing AI to a reactive concern rather than embracing it as a powerful tool for teaching, learning, and innovation.
Game-Based Learning for STEM Education
This brief highlights how game-based learning can transform STEM education for all students, including those with disabilities. Readers will gain insights into how game-based learning fosters student engagement, collaboration, and conceptual understanding, supported by real-world projects and research. It also explores how iterative design principles and AI-enhanced personalization can be integrated into teacher preparation. Dr. Marino’s approach illustrates how evidence-based game development and reflective practice can bridge the gap between research and classroom implementation.
In-Service Educators’ Changes in Reasoning About Technology Integration
As educational technologies evolve rapidly, especially with the rise of artificial intelligence (AI), many in-service teachers face challenges in meaningfully integrating these tools into inclusive instructional design (Mosher et al., 2024). Without sufficient professional development, teachers risk using technology in ways that encourage passive rather than active learning. This misalignment can hinder student engagement, particularly for students with disabilities, and limit the effectiveness of technology in promoting critical thinking and meaningful learning outcomes. Jackson and Rosenblatt (2025) identified that when teachers are not grounded in pedagogical frameworks like Universal Design for Learning (UDL) and Triple E, technology use may become superficial, inequitable, or even counterproductive.