Artificial intelligence (AI) has the potential to enhance learning and increase student participation, yet its incorporation in teaching depends heavily on teachers’ perceptions. This study draws on a survey of 285 teachers to explore their perspectives on the use of AI in education for students with special educational needs. Using statistical analyses and summative content analyses, the results revealed that 15.8% of teachers reported using AI in their schools, while only 7.4% felt confident in their ability to use it. Although current use is limited and familiarity with AI remains low, teachers acknowledge its potential to support student learning and enable innovative teaching practices. However, they also express concerns about equity and the credibility of AI tools, indicating a hesitation to fully embrace AI in the classroom. These findings highlight the importance of targeted professional development to equip teachers with the competencies needed to incorporate AI into their practice.
With the increasing number of students in the United States who qualify for special education and related services, special educators face persistent challenges in developing high-quality, legally defensible individualized education programs (IEPs). Recent research suggests that generative artificial intelligence (AI) can reduce educator workload while supporting the development of high-quality IEPs. This article introduces the AI-Enhanced Transition IEP Framework, a three-phase, seven-step process that demonstrates how large language models, such as ChatGPT, Claude, and Gemini, can support ethical, individualized, and legally defensible IEP development for secondary students. Organized around the phases of Planning, Prompting, and Presenting, the framework guides special educators in developing measurable postsecondary goals based on age-appropriate transition assessments, measurable annual goals, and coordinated courses of study that align with students’ strengths, needs, preferences, interests, and postsecondary aspirations. Throughout the framework, professional judgment remains central to ensuring that AI-generated content is individualized, aligned with legal requirements, and refined through collaboration with students, families, and IEP teams.
Technology-based interventions offer educators a safe, effective, and low-cost option to teach life skills, such as food preparation, to students with intellectual and developmental disabilities (IDD). However, researchers need to explore beyond acquisition and maintenance for technology-based interventions and also assess generalization in real life settings. In this single-case design multiple probe across participants study, researchers taught five middle school students with moderate intellectual disability to cook a grilled cheese sandwich on a stove in a non-immersive virtual reality (VR) environment. The researchers also assessed for students completing the task in real life on a hot plate in their classroom. The students acquired the food preparation skills within the non-immersive VR and improved their ability to make a grilled cheese sandwich in real life. However, generalization was limited and calls into question non-immersive VR for real-world skills demonstration.
This mixed methods study examines pre-service special education teachers’ (PSTs) experiences using an artificial intelligence (AI) tool to support transition planning and evaluated its social validity. Thirty-three PSTs from two Midwestern universities completed three AI-assisted transition planning activities and a post-intervention survey containing 12 Likert-scale and three open-ended items. Quantitative analyses revealed that participants viewed the AI tool positively across all domains, with high ratings for efficiency and ease of use and strong intentions for future adoption. Perceptions of trustworthiness and output quality were moderately positive. Qualitative analyses revealed more nuanced perspectives. While PSTs found the AI tool helpful for generating ideas, organizing content, and enhancing efficiency, they also noted limitations related to accuracy, specificity, and data entry processes. Participants emphasized the need for professional judgment, background knowledge, and ethical awareness when interpreting AI-generated outputs. Together, these findings indicate that AI tools hold promise as supportive resources in special education teacher preparation, particularly when integrated within structured, reflective learning environments. The study highlights both the value and challenges of AI in special education contexts, suggesting that teacher education programs must intentionally embed AI literacy and critical evaluation skills to ensure responsible, equitable, and effective use in future professional practice.
Joint attention (JA) is one of the fundamental early social and cognitive skills that play a significant role in education, language acquisition, social interaction, and autism diagnosis. In educational settings, JA facilitates engagement, collaborative learning, and communication development. However, JA is often weakened in children with autism, accentuating the need for precise assessment to support intervention and individualized learning strategies. This study aims to analyze current JA assessment practices using a qualitative study conducted through a focus group session and one-to-one interviews with specialists and teachers at a special school for autism. Thematic analysis was applied to the collected data to identify assessment practices, challenges, and perspectives on technology-assisted evaluation. Based on the findings, the study proposes a conceptual framework grounded in activity theory to guide the integration of technologies such as eye-tracking, computer vision, virtual/augmented reality, and AI-powered tools into JA assessment, aiming to improve objectivity, scalability, and overall efficacy.
Educator access to high-quality Evidence-Based Practices is often hindered by professional development (PD) websites that are overwhelming, difficult to navigate, or time-consuming to use. This study explored using an AI chatbot to improve the usability and navigability of finding relevant content on a PD website. An exploratory sequential, mixed-methods, single-group design was used in this Design-Based Research study. Phase One involved a needs analysis using focus groups with 13 educators to identify usability challenges. This direct feedback informed Phase Two, the chatbot’s iterative design. A post-survey was administered in Phase Three to the same educators from Phase One to assess the effectiveness and usability of the chatbot-enhanced website. Phase One confirmed strong website content but low usability. Phase Three showed that the chatbot significantly improved perceived usability and efficiency for resource discovery. This research supports developing chatbots, based on practitioner input, to increase the usability of PD website content.
The acquisition of life skills is important for the independence and quality of life of students with intellectual and developmental disabilities (IDD). Educators both have increasingly used technology as a tool to teach life skills to students with IDD and examined various technology-based interventions to support the learning of life skills. Yet, the classification of technology tools as evidence-based practices for teaching life skills to students with IDD continues. This systematic review examined the state of the literature as well as research quality of studies examining VR as a tool for non-social/communication life skills teaching for students with IDD. Relevant articles published between 2010 to June 2025 were screened and evaluated using quality indicators and standards from the Council for Exceptional Children. Of the 10 articles meeting inclusion criteria, researchers determined three methodologically sound single-case studies and one methodologically sound group study. Together, these four studies suggest VR as a potential evidence-based practice for teaching life skills to students with IDD.
Challenges related to travel and transportation are a well-documented barrier to community engagement for young adults with intellectual and developmental disabilities (IDD). It is important for secondary educators to teach young adults with IDD to navigate their communities safely and independently, and technology tools such as smartphone applications are one common way to teach these skills. We used a single-case, multiple probe design to measure the effects of three transition-age students with IDD using constant time delay and the Google Maps application to independently navigate to unfamiliar locations on a college campus. Results indicated a functional relation between variables. Additional measures included generalization to use of Apple Maps, reported social validity of the intervention, and participants’ ability to problem-solve common issues that may occur when following a pedestrian route. We provide limitations, suggestions for future research, and implications for practice to enhance the community engagement of young adults with IDD through technology-based applications such as Google Maps.
Augmented reality constitutes a technology-enhanced learning environment that integrates digital 3D representations with real-world contexts, thereby offering multimodal, concrete supports for students' understanding of complex and abstract scientific concepts. The current study investigated the effects of AR technology on teaching science concepts related to electric circuit components and body systems to three male secondary students with autism spectrum disorder aged 13-14 years. A multiple-probe design across participants was employed to evaluate an AR-delivered discrete trial intervention. Results showed that all students acquired, maintained, and generalized the targeted science concepts. Students also improved their knowledge of non-targeted information and rated the AR intervention as highly acceptable and enjoyable. The findings are discussed in relation to Universal Design for Learning and the potential of AR to create more accessible and motivating opportunities for students with ASD to learn science content.
This study employs an exploratory netnographic research approach to explore how educators in K-12 and higher education settings publicly engage with artificial intelligence (AI) on TikTok as a professional learning network, with an emphasis on supporting students with disabilities. Using deidentified, publicly accessible video data, 209 videos were qualitatively coded, and statistical analysis of thematic coding frequencies identified five overarching themes. These included: (1) AI as a Pedagogical and Productivity Tool for Educators, (2) AI for Personalization, Inclusion, Access, and Student Support, (3) AI Literacy, Ethics, and Societal Implications, (4) AI in the Workforce and Skill Development, and (5) AI Tool Demonstrations. The findings explore ways in which educators and students, especially those in secondary and higher education environments, are using TikTok as an informal professional learning network where AI tools, ethical considerations, and inclusive practices are shared and debated, contributing to emerging scholarship at the intersection of AI, special education, and digital educator culture. These insights and findings aim to better understand how educators and students develop shared knowledge in AI in algorithmically mediated public spaces.
Special education teacher preparation programs have a significant influence on pre-service teachers’ technology integration. This study examined the connection between prior technology coursework and current perceptions of AI use among 420 special education teachers, most of whom completed their professional preparation before the rise of generative AI. Findings preliminarily show a statistically significant, positive, weak-to-moderate correlation between technology preparation and AI use. This suggests that early exposure to technology in training programs may lay the foundation for adapting to emerging technologies such as AI.
As the use of generative artificial intelligence (GenAI) becomes more commonplace in higher education institutions, the extent to which these tools promote inclusive learning environments remains underexplored. Students with disabilities (SWD), who comprise a substantial yet often underrepresented portion of the higher education student population, may benefit from GenAI when these tools are accessible, ethically employed, and responsive to diverse needs. This study investigates student perceptions and use of GenAI with an emphasis on SWD. A cross-institutional survey yielded 383 responses, 48 of which were from participants who self-identified as higher education students having a disability. Findings indicate widespread adoption of GenAI for tasks such as brainstorming, clarification, and supporting writing processes. While most respondents reported academic benefits, concerns regarding ethics, reliability, and institutional policies were also prevalent. Findings underscore the importance of centering accessibility in GenAI design and highlight implications for inclusive higher education practices and policies.
WEGO is a technology-based writing intervention package to support the composition of high-quality essays by students with and without high-incidence disabilities struggling with writing. While existing evidence shows that WEGO can significantly improve students' organization of ideas for a more cohesive opinion-based final product, the challenge to generate those ideas remains. Thus, the WEGO team developed an AI-based brainstorming feature to integrate into the existing intervention. In collaboration with partnering school systems and following their policies and guidelines around artificial intelligence, a retrieval-based chatbot, named Ask Boris AI was developed. It supports idea generation during the brainstorming phase of the writing process. Ask Boris AI addresses teachers’ and school districts’ concern for using open generative chatbots by providing a conversational AI system using a predefined set of responses stored in a knowledge base. While Ask Boris AI does not generate new content, it stimulates users to identify possible ideas related to a writing prompt based on their need in a controlled environment as desired by many practitioners. This article describes how multiple data sources were used to make design decisions and generate a curated knowledge base using existing WEGO essays.
Virtual coaching has become an increasingly used strategy for supporting families of young children with developmental delays and/or disabilities. Due to ongoing provider shortages and the focus on delivering early intervention (EI) and early childhood special education (ECSE) services during the pandemic, a greater emphasis has been placed on using technology to support children and families who receive EI/ECSE supports. This systematic literature review examined 13 single-case design studies focused on virtual coaching families of children ages 2-5. Using a researcher-developed coding scheme and the Single Case Analysis and Review Framework (SCARF), we examined (a) coach and participant demographic characteristics, (b) use of coaching strategies, (c) descriptions about the implementation of virtual coaching practices and technology, (d) use of generalization and maintenance measures, and (e) overall quality of the study. Strengths of the articles, as well as suggestions for increased transparency in reporting studies, are provided in this review.
Post-secondary educational opportunities continue to grow for individuals with intellectual and developmental disabilities (I/DD), with many providing options for independent living. This has intensified the need to teach independent living skills to this population. Complex learning needs in this population often necessitate unique teaching approaches. A single case, multiple probe across behaviors design was used to determine the effectiveness of an augmented reality (AR) video modeling system with user controls delivered on a mobile device as a learning approach. The study examined whether the AR intervention helped participants living independently learn new skills and inquired about the social acceptability of the system. Three individuals, ages 18 - 21, participated in the study. Results indicate that the AR video models were an effective and socially acceptable means of skill acquisition while also increasing independence and autonomy when completing new tasks.
This study examines how educators scaffold students with disabilities to interact meaningfully with generative artificial intelligence (GenAI) tools, specifically ChatGPT, in an inclusive science classroom. While GenAI is gaining traction in education, research on its use among students and educators in inclusive education remains underexplored. Addressing this gap is critical as effective GenAI use among students with disabilities demands cognitive and linguistic engagement that are challenging for them without appropriate scaffolding. This study adopted a collaborative action research approach to explore how educators supported students with disabilities in engaging with ChatGPT in the classroom. Drawing on video-based analysis of classroom interactions, the analysis resulted in an emergent taxonomy of educator support across four domains: instructional, literacy, emotional-behavioural, and technological. The findings illustrate the utility of the taxonomy that frames how established domains of support for students with disabilities are enacted, combined, and intensified in the context of student-GenAI interaction. They also highlight how real-time and adaptive scaffolding enabled students with disabilities to access, interpret, and respond to GenAI. This study reframes GenAI not merely as a tool, but as a mediated dialogic partner whose educational value depends on how it is supported by educators. Implications are discussed for inclusive pedagogy, GenAI design, and teacher professional learning.
Artificial Intelligence (AI) systems are demonstrating significant potential in revolutionizing K-12 education, specifically by offering new ways to improve individualized and inclusive instructional practices in special education. With the sudden integration of Artificial Intelligence tools, many special education teachers still struggle to understand how to effectively use them to foster inclusive classroom environments. In this article, we introduce a practice-oriented integration framework that provides special education teachers with practical guidance for using AI tools to design instruction aligned with two critical frameworks: Universal Design for Learning (UDL) and Culturally Responsive Teaching (CR Teaching). Some of the reliable AI platforms are described in the context of use for diverse students under UDL and CR Teaching frameworks. We conclude with recommendations for practice including ethical use of AI by special education teachers.
Many educators utilize generative artificial intelligence (GenAI) to streamline demanding workloads and accelerate the individualization of instruction for students with disabilities (SWD). However, challenges may arise if such tools perpetuate ineffective instruction for SWDs. To address this issue, CoIEP was developed. CoIEP is a large-language-model-based multi-agent system specially designed to assist educators in developing individualized programming and evidence-based instruction for SWDs. This article describes how CoIEP, combined with an explicit instructional decision-making process, can support special and mathematics education co-teachers in efficiently designing evidence-based instruction for SWDs. To bridge ongoing debates on effective mathematics instruction for SWDs within both special and mathematics education, this collaborative approach intentionally integrates opportunities for SWDs to foster metacognition (i.e., "thinking about thinking") as a bridge, a shared understanding, between the two communities. This article presents a step-by-step overview outlining how co-teachers can effectively prompt CoIEP to design evidence-based, metacognition-aligned mathematics instruction for SWDs.
High-quality Present Levels of Academic Achievement and Functional Performance (PLAAFP) statements and measurable annual goals are foundational to effective Individualized Education Programs (IEPs) for students with disabilities, yet many special education teachers report difficulty writing these components. Targeted professional development may strengthen IEP quality, but limited research has examined how technology-based professional development influences alignment among IEP components and subsequent student outcomes. This correlational study examined the relationships among PLAAFP quality, IEP goal quality, teacher characteristics, professional development software use, and student academic growth following participation in Goalbook Toolkit, a digital professional development platform. Participants included 135 special education teachers and 160 students in Grades 2-8 randomly selected across 22 school districts in a Midwestern state. Archival 2023-2024 IEP documents were scored using validated rubrics to assess PLAAFP and goal quality, and student growth in reading and mathematics was calculated using fall-to-spring assessment data. Results indicated a strong positive relationship between PLAAFP quality and IEP goal quality (r = .63, p < .001), with PLAAFP quality accounting for 40% of the variance in goal quality. However, relationships between IEP goal quality and student growth in reading and mathematics were weak and non-significant. Hierarchical regression analyses showed that teacher characteristics significantly predicted combined student growth, while Goalbook Toolkit usage contributed modest incremental variance. Findings highlight the critical role of high-quality PLAAFP statements in strengthening IEP goal quality and suggest that improving written IEP components alone may be insufficient to produce short-term gains in student achievement. Implications for sustained, technology-supported special education teacher professional development are discussed.
This study examined the effects of a structured instructional approach on improving financial literacy and mathematical problem-solving skills among adults with intellectual and developmental disabilities (IDD). Using a nonconcurrent multiple baseline across participants design, three college students in a postsecondary education program received the intervention remotely via Zoom. The dependent variable, accuracy of participants' performance on a structured task analysis, was measured across three purchase scenarios. Instruction followed an explicit instructional model emphasizing modeling, guided practice, and independent application with a realistic replica of U.S. currency. All participants demonstrated clear improvements in accuracy and efficiency when making monetary combinations. Social validity findings indicated that participants enjoyed the lessons and felt more confident handling financial transactions. Results support the effectiveness of explicit, systematic instruction paired with technology-based delivery to enhance financial competency and independence for adults with IDD. These findings highlight the value of embedding functional money management instruction within postsecondary education curricula to promote autonomy and employability.
