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Table of Contents
Special Education Legal Alert
Buzz from the Hub
Update from the U.S. Department of Education
Generative Artificial Intelligence and the Individualized Education Program
Assistive Technology Challenges in IEPs and Classroom Practice
Acknowledgements
Special Education Legal Alert
Perry A. Zirkel
June 2026
This month’s update identifies two recent decisions that respectively reflect the initial appearance of AI and the difficulties of IDEA discipline in the world of special education litigation. For related publications and special supplements, see perryzirkel.com
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On May 14, 2026, the federal district court in Utah issued an unofficially published decision in Wilkes v. Canyons School. In this case, the school district first found a student eligible for special education in kindergarten under the IDEA classification of autism. Although the initial IEPs were successful, the child’s progress stalled in grades 3 to 5. Yet, upon the transition to middle school for grade 6, the IEP team determined, despite the parents’ objections, that he was no longer IDEA-eligible. Instead, the district provided him with a 504 plan. His decline worsened despite multiple revisions to this plan. In December of grade 6, the parents requested another IDEA evaluation, but the district refused. They also requested a functional behavioral assessment, which the district agreed, but failed, to do. In March, the parents hired an attorney, and the district assented to an IDEA evaluation. In late May, the IEP team determined that the student re-qualified under the IDEA. In August, the district held a meeting to develop the child’s IEP for grade 7, but the parents expressed dissatisfaction with the meeting’s brevity and the cursory consideration. In October, they filed for a due process hearing, alleging denial of FAPE extending back to grade 3. In March, the hearing officer issued a decision in favor of the district. In July, the parents filed an appeal with the federal district court based on multiple claims, including (1) Section 1983 for alleged violations of the Fourteenth Amendment; (2) Section 1983 for alleged violations of the IDEA, Section 504, and the Americans with Disabilities Act (ADA); and (3) the IDEA on its own. The district filed a motion to dismiss all the parents’ claims except their appeal of the hearing officer’s ruling for the two-year period within the IDEA’s statute of limitations. |
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The parents argued that the district was liable under Section 1983 for violations of the Fourteenth Amendment’s due process and equal protection clauses. |
The court dismissed this claim without prejudice (meaning that they could submit a revised version) because it unduly overlapped with their claims under the IDEA and Section 504/ADA. |
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The parents separately predicated Section 1983 claims on alleged violations of their child’s rights under the IDEA, Section 504, and the ADA. |
The court dismissed this claim with prejudice due to well-settled precedent that each of these statutes had their own comprehensive enforcement mechanisms. |
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The district’s threshold challenge was to the notable part of the parents’ IDEA claim that was beyond the two-year limitations period (reserving the rest of their challenge for further proceedings). |
The court agreed with the district because for their statute of limitations argument the parents relied on artificial intelligence (AI)-hallucinated case citations. |
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The court held a follow-up show-cause hearing to determine whether the parents’ use of nonexistent citations warranted sanctions. |
The court ruled that the parents’ attorney must pay $7,000 to the school district as reimbursement for legal expenses incurred as a result of the use of non-existent case law. |
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The primary, though not exclusive, lesson from this case is to beware of the misuse of AI in legal proceedings (as well as elsewhere). |
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On April 20, 2026, a federal district court in Virginia issued an unofficially published decision in Richmond City School Board v. V.B. The child in this case, V.B., was a kindergartner with a history of serious behavior problems in daycare programs. Upon enrolling her in kindergarten, V.B.’s parents notified school officials that she had ADHD, although they did not provide documentation of the diagnosis. Despite some good days and apparent progress during the first several months of the school year, V.B.’s behavior was often problematic, including spitting on others, yelling and screaming, cursing, and physical aggression. Her teacher did not report her misbehaviors to the school administration until mid-November, which resulted in notification to the parents. The school implemented various interventions, including the teacher’s color-coded behavioral system, check-ins by the school counselor and social worker, classroom breaks, and—after referral to the school-based intervention team—specific goals with related strategies. However, despite these efforts, V.B. received a one-day suspension on December 14, and on at least a weekly basis, the administration responded to her misconduct by having the parents pick her up long before the end of the school day. On January 11, the school’s child find team referred V.B. for an IDEA evaluation. The parents consented, but well before the evaluation was completed, V.B. received two more one-day suspensions. On February 28, V.B. threw the contents of her desk on the floor, refused to pick them up, and when the teacher did so, V.B. hit her in the hip with a closed fist and said “that’s what you get.” As a result, the principal issued a ten-day suspension. On the second day of the suspension, the district held a manifestation determination meeting. The team determined that the punch was retaliatory rather than impulsive, thus not being caused by V.B.’s reported ADHD. Consequently, the matter proceeded to the regular district disciplinary procedure, which was formal notice of violation of the student code of conduct and a district hearing. The resulting decision was that V.B. could return to the school at the end of the suspension but that further serious infractions would result in her assignment to another district school. However, V.B. did not return, and the parents did not cooperate with the district’s requests for them to make V.B. available for completion of the eligibility evaluation. In July, they filed for a due process hearing, with the advice of a lay advocate. After a 2-day hearing, the hearing officer ruled that the district violated the IDEA by not providing an earlier manifestation determination based on (a) the accumulated removals amounting to a disciplinary change in placement well before January 28, and (b) the “the teacher … express[ing] specific concerns about [the child’s] pattern of behavior … directly to supervisory personnel” (§ 300.534). As the remedy, she ordered an independent evaluation to determine V.B.’s eligibility under the IDEA. The district appealed these rulings to the federal district court. Despite receiving several warnings from the court, the parents, who continued to proceed without an attorney, did not respond to the district’s appeal. |
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The district argued that the cumulative removals did not amount earlier to a disciplinary change in placement. |
The court deferred to the hearing officer’s factual finding and applied a general case law standard for a change in placement (ignoring § 300.536). |
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The district contended that the hearing officer wrongly invalidated its manifestation determination of “No.” |
The court deferred to the hearing officer’s conclusions as meeting the jurisdiction’s broad standard of being “regularly made.” |
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The district argued that the remedy was improper under the IDEA. |
Here, the court agreed, concluding that “[the district] has a statutory right to conduct those evaluations rather than independent evaluators.” |
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This decision is rather surprising in light of the parents’ lack of cooperation for completion of the evaluation and for the proceedings in the judicial appeal, but these two disciplinary protections of the IDEA are murky and turbulent waters to navigate. |
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Buzz from the Hub
https://www.parentcenterhub.org/buzz-may2026/
CPIR Resource Center
Have you checked out the new CPIR Resource Center? The resource center is a collection of curated tools to support families, caregivers, self-advocates or educators, by providing information about rights, services, best practices, leadership development, systems navigation and more. Make it your go-to place for materials to support informed decision-making and building strong collaborative connections.
Explore the CPIR Resource Center here.
Special Olympics Young Athletes
Special Olympics Young Athletes is a sport and play program for children with and without intellectual disabilities (ID), ages 2 to 7 years old. It has a vast library of free resources for families, including digital tools such as the Young Athletes app and in-person Young Athletes programming, that takes place in homes, in the community, and at schools.
Learn about Young Athletes here.
Supporting Your Child’s Reading at Home
Learning to read begins at home through everyday parent-child interactions, long before children attend school. The Regional Educational Laboratory (REL) Program created these Family Activities with easy-to-follow instructions and videos to help you and your child practice foundational reading skills. Using the Family Activities at home can help your child develop language, link sounds to letters, blend letters and word parts to read and write words and read for understanding.
Find the Family Activities here.
Podcast: Beyond the Bell: From Research to Real Life
NTACT:C’s podcast, Beyond the Bell: From Research to Real Life, is a monthly series that breaks down key transition topics in a clear, practical way. Each episode explores strategies to improve outcomes for students and youth with disabilities, including postsecondary education, employment, independent living, and community participation.
Listen to the podcast here.
Digital Literacy
The Arc, The Arc San Francisco, and AT&T have collaborated on a nationwide program that is bringing digital skills training to people with disabilities and their families. The trainings accommodate the different learning styles of people with disabilities.
Explore the different courses available here.
What Makes Kids Hate Themselves?
The updates from the Child Mind Institute are always informative, but today’s headline, “What Makes Kids Hate Themselves?”, stands out in particular. Many parents recognize the moment when a child says something negative about themselves after making a mistake, and it can be difficult to know how to respond.
For those who have encountered similar situations, the resources shared in this edition of the newsletter may offer helpful guidance.
Read the newsletter here.
Stepping forward, stepping back: How parents can support youth moving to adult health care
The process of moving from pediatric to adult health care involves legal and social changes. For youth with intellectual and developmental disabilities, this process often is delayed or incomplete. From sharing information and power to building new skills, this webinar will help families navigate the process of health care transition in ways that empower youth to step forward and take a leadership role in their health and care.
When: June 15, 2026 Time: 2:00 PM ET Register here.
Update from the U.S. Department of Education
Birth to Grade 12 Education-Reources
https://www.ed.gov/birth-to-grade-12-education
Available Grants
https://www.ed.gov/grants-and-programs/apply-grant/available-grants
June 3, 2026
Today, the U.S. Department of Education’s Office for Civil Rights (OCR) issued a warning letter to Jefferson County Public Schools (the District) in Colorado for its ongoing refusal to comply with Title IX of the Education Amendments of 1972.
U.S. Secretary of Education Linda McMahon Visits Vermont on Returning Education to the States Tour
June 2, 2026
Today, U.S. Secretary of Education Linda McMahon visited Vermont on her Returning Education to the States Tour. She began at the Center for Technology, Essex in Essex Junction, a career and technical education school.
June 1, 2026
Today, U.S. Secretary of Education Linda McMahon visited Massachusetts on her Returning Education to the States Tour.
U.S. Department of Education Celebrates June as Second Annual Title IX Month
June 1, 2026
Today, the U.S. Department of Education (the Department) announced that it is again recognizing June as ‘Title IX Month’ in honor of the fifty-fourth anniversary of the Educational Amendments of 1972 (Title IX).
May 29, 2026
Today, the U.S. Departments of Education (ED) and Health and Human Services (HHS) launched the School Safety Enhancement program Fiscal Year (FY) 2026 competition to bolster school safety and school infrastructure security.
May 28, 2026
Today, U.S. Department of Education Senior Advisor for Civic Education Katie Gorka visited Winthrop High School as part of the Department of Education’s national ‘History Rocks!’ Trail to Independence Tour.
“PRESIDENTIAL 1776 AWARD” SPECIAL TO BE BROADCAST TUESDAY, JUNE 30 ON CBS
May 28, 2026
The U.S. Department of Education and CBS announced today that the 1776 PRESIDENTIAL AWARD special will be broadcast Tuesday, June 30.
May 27, 2026
Yesterday, U.S. Department of Education Under Secretary of Education Nicholas Kent visited Mokulele Elementary School as part of the U.S. Department of Education’s national History Rocks! Trail to Independence Tour.
May 26, 2026
As the United States approaches its 250th birthday, the U.S. Departments of Education (ED) and Labor (DOL) issued the Fiscal Year (FY) 2026 competition for the American History and Civics – National Activities (AHC-NA) Program.
May 21, 2026
Today, the U.S. Department of Education (the Department) reached consensus on a proposed regulatory framework to advance the Trump Administration’s vision for reforming and strengthening the nation’s higher education accreditation system.
May 21, 2026
Today, the U.S. Departments of Education (ED) and Labor (DOL) announced that the agencies will make a historic, one-time investment in the Fiscal Year (FY) 2026 competition for the Strengthening Institutions Program.
May 20, 2026
Today, the U.S. Department of Education’s Office for Civil Rights initiated a directed investigation into Loudoun County Public Schools in Virginia.
U.S. Department of Education Approves Louisiana’s Returning Education to the States Waiver
May 20, 2026
Today, the U.S. Department of Education approved Louisiana’s Returning Education to the States Waiver, empowering State education officials with greater discretion over their federal education dollars.
U.S. Department of Education Announces Additional Measures to Reduce Federal Burden on States
May 19, 2026
Today, ED announced it has approved Florida and Illinois’ Ed-Flex applications, marking a record high number of 18 states now utilizing Ed-Flex authority.
U.S. Department of Education Issues Final Rule to Create New Workforce Pell Grant Program
May 18, 2026
Today, the U.S. Department of Education announced a final rule to implement the Workforce Pell Grant program created under President Trump’s historic Working Families Tax Cuts Act.
U.S. Secretary of Education Linda McMahon Visits Wisconsin on Returning Education to the States Tour
May 15, 2026
Today, U.S. Secretary of Education Linda McMahon visited Wisconsin on her Returning Education to the States Tour.
May 14, 2026
Today, U.S. Department of Education Assistant Secretary for Postsecondary Education Dr. David Barker, AR Governor Sarah Huckabee Sanders, and AR Secretary of Education Jacob Oliva visited Lakewood Elementary on the Department’s History Rocks! Tour.
May 13, 2026
The U.S. Departments of Education (ED) and Labor (DOL) today announced a major milestone in federal efforts to strengthen alignment across education and workforce systems.
Secretary McMahon Announces $144M Boost for Students with Disabilities
May 13, 2026
Today, U.S. Secretary of Education Linda McMahon announced a new $144 million investment by the Trump Administration to help states expand proven interventions that support students with disabilities.
May 12, 2026
Today, the U.S. Department of Education (ED) issued the Fiscal Year (FY) 2026 competition for the Comprehensive Centers Program, reaffirming the Trump Administration’s commitment to return education to the states.
May 11, 2026
Today, the U.S. Departments of Education (ED) and Labor (DOL) issued the Fiscal Year (FY) 2026 competition for the Career Pathways Exploration (CPE) and Teacher Quality Partnership (TQP) Programs.
May 8, 2026
Today, U.S. Department of Education Senior Advisor for Civic Education Katie Gorka visited Canyon Hills Junior High School as part of the Department of Education’s national History Rocks! Trail to Independence Tour.
May 8, 2026
Today, the U.S. Departments of Education and Health and Human Services issued the Fiscal Year 2026 competitions for the Ready to Learn Program and the Promise Neighborhoods Program.
May 8, 2026
Today, the U.S. Department of Education’s Office for Civil Rights opened an investigation into the Houston Independent School District in Houston.
May 8, 2026
Antisemitism is on the rise in K-12 schools across the country, and some school districts are seemingly tolerant of it. Today, the U.S. Department of Education’s Office for Civil Rights is opening a complaint against Bay County, Florida School District.
May 8, 2026
Today, U.S. Secretary of Education Linda McMahon visited Mat-Su Career & Tech High School in support of the Returning Education to the States Tour and Knik Charter School as part of the ‘History Rocks!’ Trail to Independence Tour.
May 7, 2026
Today, U.S. Department of Education Senior Advisor for Civic Education Katie Gorka visited Liberty Common Junior High School and Liberty Common High School as part of the Department’s national History Rocks!.
Fact Sheet: The Trump Administration is Making College More Affordable
May 6, 2026
Higher education has been one the fastest-growing expenses for American families over the past 40 years. A significant driver of skyrocketing prices has been uncapped access to federal student loans.
U.S. Department of Education Opens Title IX Investigation into Los Angeles Unified School District
May 5, 2026
The Los Angeles Unified School District appears to be protecting sexual predators at the expense of its students. Today, in response, the U.S. Department of Education’s Office for Civil Rights opened a directed investigation into the District.
May 4, 2026
Today, U.S. Department of Education Chief of Staff Madi Biedermann visited George Washington Academy as part of the Department’s national History Rocks! Trail to Independence Tour.
May 4, 2026
Today, the U.S. Department of Education’s Office for Civil Rights (OCR) opened an investigation into Smith College, one of the nation’s largest all-women’s colleges, for admitting biological men and granting them access to women-only spaces.
U.S. Department of Education Celebrates Presidential 1776 Award Regional Semifinals
May 4, 2026
The U.S. Department of Education celebrates the Presidential 1776 Award Regional Semifinals, which took place on Saturday, May 2nd, 2026.
May 1, 2026
Today, the U.S. Departments of Education (ED) and Labor (DOL) issued the Fiscal Year (FY) 2026 competition for the Competitive Grants for State Assessments (CGSA) Program.
Generative Artificial Intelligence and the Individualized Education Program
By: Sienna Bascus, Camryn Ellison, Silvia Roman, Sarah Sepe, Raena Thelwell, and Alva Ward
Abstract
Generative artificial intelligence is increasingly being used in special education to assist with IEP goal development, data synthesis, and related compliance tasks. This literature review examines recent research on generative AI in the development, implementation, and evaluation of IEPs. Across studies, two themes recur: increased efficiency and structured support for educators. Findings suggest that AI-assisted tools may improve goal quality for less experienced teachers and broaden goal coverage in some preschool contexts, while experienced teachers often produce goals of comparable quality with or without AI support. The literature also identifies significant risks, including reduced individualization, overreliance, bias, privacy concerns, and uncertainty regarding legal and ethical compliance. Overall, current evidence supports generative AI as a support tool rather than a substitute for educator expertise. Human oversight, careful review, and clear implementation of safeguards remain essential.
Introduction
The use of generative AI in special education contexts is growing, particularly in data analysis, lesson planning, and the creation of Individualized Education Programs (IEPs). Generative AI has been proposed as a support tool within special education to help teachers synthesize vast amounts of student data, create quantifiable goals, and enhance the effectiveness of documentation procedures. According to recent studies, generative AI tools like ChatGPT are increasingly being used to help both novice and experienced teachers create IEP goals and match them to the needs of their students. These developments suggest that generative AI may support complex tasks and reduce administrative burden on special education teachers.
However, the application of generative AI raises serious concerns related to accuracy, ethical responsibility, and the integrity of IEP implementation, notwithstanding its potential. Research on AI-generated IEP goals shows that although these tools can provide measurable, structured goals, there is variation in the goals’ appropriateness, quality, and individualization. Additionally, overreliance on generative AI systems could result in programming that is too general and does not sufficiently account for the special needs of students with disabilities. These problems make generative AI in special education a developing at-risk area, especially when technology is applied without adequate supervision, training, or critical assessment.
Generative AI has become relevant to the development and implementation of IEPs since these procedures require accurate, customized, and legally compliant documentation. According to the Individuals with Disabilities Education Act (IDEA), IEPs must be customized to meet the unique needs of each student and include precise, quantifiable goals as well as regular progress tracking. There are dangers and opportunities associated with integrating AI into this process. While generative AI may support data organization and goal framework suggestions, its inappropriate use could jeopardize the integrity and fidelity of IEPs, ultimately affecting student outcomes. The importance of ensuring that generated goals remain developmentally appropriate and aligned with evidence-based practices is further highlighted by research investigating generative AI integration in preschool and K–12 settings.
This literature review examines generative AI’s function in special education, with a particular emphasis on its application in the development, implementation, and evaluation of IEPs. This review evaluates the advantages and disadvantages of these tools, as well as the factors influencing their adoption among educators, by combining the most recent research on generative AI-assisted practices. This review also aims to emphasize the consequences for educators, educational systems, and students with disabilities, as well as to identify potential concerns related to the usage of generative AI. To guarantee that developing technologies are applied in ways that improve rather than impair the caliber and efficacy of special education services, it is essential to understand these dynamics.
Opportunities and Promising Uses of Generative AI in Special Education
This section examines how the literature evaluates the ways generative AI may support special education contexts, with particular attention to IEP development, administrative practice, and instructional decision-making. Several studies suggest that generative AI may support special education practice by addressing two of its most persistent and interconnected challenges: the burden of documentation and the quality of developing Individualized Education Programs. Taken together, the literature indicates a consistent pattern that generative AI tools may meaningfully reduce educator workloads. When used intentionally and with professional oversight, generative AI tools may also strengthen the quality of support designed for students with disabilities.
One of the most direct areas of promise involves developing IEP goals. Rakap (2024) examined the use of ChatGPT among novice special education teachers tasked with writing IEP goals for students with autism. Using a randomized design and the Revised IEP/IFSP Goals and Objective Rating Instrument (R-GORI) as an outcome measure, the study found that teachers in the ChatGPT condition produced goals of significantly higher quality while spending significantly less time on the task than peers in the control group. Notably, the goals generated with AI assistance were more comprehensive, addressing specific student strengths and needs rather than defaulting to generic language. This finding matters because it suggests that generative AI may improve efficiency without reducing individualization. Individualization costs can be a concern in special education because legal compliance requires that goals reflect each student’s unique present levels of performance. Critically, the benefit was present regardless of whether participants had received prior formal training in IEP development, which suggests that generative AI may function as a meaningful equalizer for educators who enter the field with less preparation in this high-stakes skill.
Along with these findings suggesting potential improvements in goal quality, generative AI may also broaden the developmental range of goals produced. Rakap and Balikci (2026) extended this line of inquiry to preschool-age children with autism, and their study found that teachers who used ChatGPT produced goals with statistically higher quality ratings than a comparison group who did not. An additional pattern emerged in the distribution of goal domains: the control group’s goals concentrated on preacademic skills and behavior, whereas the ChatGPT group’s goals addressed a broader range of developmental areas. This broader range includes communication, social skills, motor and sensory development, and self-care. This finding is important because it suggests generative AI may prompt educators to consider domains they might otherwise overlook under time pressure. Thus, generative AI may produce more holistic and legally compliant IEPs. Despite this potential, the authors described their study as preliminary, and the small sample size warrants caution in generalizing these findings to broader populations or disability categories.
Research indicates that generative AI tools may also assist educators in navigating the structural demands of IEP compliance without diminishing goal quality at the experienced-teacher level. Waterfield et al. (2026) conducted a convergent mixed-methods study with experienced special educators across multiple states, comparing the quality of IEP goals written independently to those produced with ChatGPT assistance. While quantitative analysis revealed no statistically significant difference in rated goal quality between the two conditions, qualitative data indicated that participating teachers held predominantly positive perceptions of generative AI as a tool for managing their workload. This absence of a quality difference is meaningful because it implies that for experienced educators, AI does not degrade the standard of their work. Rather, it redistributes their cognitive effort. When teachers are not spending limited planning time generating sentence structure and goal formatting from scratch, they have more capacity to apply their professional judgment to the substantive decisions that require it: interpreting assessment data, weighing student preferences, coordinating with families, and monitoring implementation. This finding, as well as Rakap’s (2024), suggests generative AI’s benefit may be most striking for those with the least preparation and least disruptive for those with the most, which provides a distribution that has equity implications across the field.
Beyond IEP goal writing, generative AI may also support the broader administrative infrastructure within which IEPs are developed and monitored. Marino and Vasquez (2024) presented an exploratory mixed-methods case study in which special education administrators utilized a generative pre-trained transformer with specific “data analyst” functions within a generative AI platform to synthesize large and disparate student data sets. What had previously constituted a three-month administrative project involving the integration of case manager records for hundreds of students was completed in just three days. The generative AI synthesized the data and generated a narrative summary supporting graphics that administrators then used to inform staffing decisions and resource allocation. This finding extends the conversation about generative AI in special education beyond the individual teacher and the IEP document. If generative AI can support administrators in making data-driven decisions about caseloads, resource distribution, and compliance monitoring at scale, then its utility may be felt indirectly but substantively at the student level through better-resourced and better-supported classrooms. Marino and Vasquez (2024) acknowledged, however, that challenges using AI-generated outputs can include data consistency, staff training, and administrator familiarity, which require solutions before reliably implementing generative AI at a district level.
Collectively, these findings suggest that generative AI’s most defensible promise in special education is a support function. Generative AI is a tool that amplifies educator capacity in specific, bounded tasks rather than displacing the professional judgment that is both legally and ethically required. The literature reviewed here does not support the conclusion that generative AI should operate autonomously in IEP development or administrative decision-making. Rather, it supports the more modest but practically significant claim that generative AI may help educators work more efficiently without reducing, and in some cases improving, the quality of individualized planning for students with disabilities when implemented under appropriate conditions. The conditions in which the literature reports benefits matter considerably: structured prompting, AI literacy, human review, and institutional support appear consistently across studies as factors that mediate whether generative AI use produces meaningful gains or introduces new risks. These conditions can serve as contextual examples to responsibly incorporate generative AI into special education.
Risks, Limitations, and At-Risk Areas
Despite these promising applications, the literature identifies several significant risks and limitations in AI-assisted IEP development and special education practice. These concerns include reduced individualization, overreliance, and diminished educator engagement with students’ needs.
In 2025, Waterfield et al. conducted a study that compared IEPs written by human educators to those created by the AI platform ChatGPT. The study reported that although these AI-generated goals were well structured and useful as a starting point, they lacked the professional judgment required in educational decision-making. Because AI-generated content is created strictly from written prompts rather than full-range information that human educators gather (observations, familial input, student relationships), it cannot capture the full depth of information required. The result is an IEP with generalized, generic language which can be widely applied to nearly any student. Generative AI doesn’t “know” any of the students that it’s producing IEPs for; it can only produce from the information it’s given. Documented data alone are insufficient for developing a strong IEP; contextual and relational information also matter. Relevant considerations may include family context, cultural factors, and variation in student behavior across instructional settings. Most of these behavioral nuances are typically understood through observations from teachers or families and are sometimes hard to put into words to get an accurate generative AI-written IEP in response; this is a major limitation.
It’s important, Naatz & Ruppar (2026) say, for educators to always keep in mind that AI should not be seen as a time-saving tool rather than a resource to enhance teachers’ skills in helping support students with disabilities. However, this mentality is often not the case, Naatz & Ruppar argue. It’s easy to get carried away when using generative AI and cognitively check out; you type in a prompt, and the generative tool produces a masterfully written IEP plan. As educators, it’s so important to ensure that professional judgment and human oversight in teaching and decision-making remain, because they are the ones responsible for addressing any possible errors, biases, or inequalities that are embedded into the technology. When trained on unbalanced, unrepresentative, or stereotypical data, generative AI can feed off this and produce discriminatory responses. If left unchecked, which very well could happen if educators become too trusting and over-reliant on these generative AI tools, this type of stereotypical, misinformed data could end up in a child’s IEP.
To summarize, the use of generative AI in the generation of IEPs introduces both significant opportunities and limitations. While it can increase efficiency and support organization, it also raises major concerns related to individualization, bias, and overreliance. These risks and limitations emphasize the importance of maintaining professional judgment and human oversight in special education, where educators must evaluate their students based on both qualitative and quantitative data. These educators must also be ready to critically evaluate the AI-generated responses to ensure that IEPs remain accurate and supportive to the unique needs of every student.
Legal, Ethical, and Compliance Considerations
The risks, limitations, and at-risk areas highlight concerns that extend beyond instructional quality and into legal and ethical responsibilities. IEPs are legally binding documents governed by federal law. Issues such as lack of individualization, bias, and overreliance on generative AI raise important questions about compliance, student rights, and, most importantly, data protection. Legal guidelines, privacy, ethical considerations, and accuracy remain unclear. Although federal laws protect students and families, it is still necessary to examine how the use of generative AI tools aligns with legal standards and ethical expectations in special education.
Legal guidelines and potential ramifications of using generative AI tools in the special education classroom, especially for writing Individualized Education Plans (IEPs), remain unclear. The Individuals with Disabilities Education Act (IDEA) requires that every student’s IEP be individualized, based on their current performance, and designed with clear, measurable goals. While generative AI tools may support the organization and structure of an IEP, these tools cannot capture the full picture of a student. Generative AI systems often rely on patterns from large datasets, leading to generalized responses. This becomes a major problem when the law requires individualized educational planning. For IEPs to be student-centered, both the knowledge of the student and the expertise of education professionals are essential. Generative AI tools do not know the students. Therefore, it is crucial for teachers to rely on student data to guide the creation of IEPs. If AI-generated content is used, teachers must review and revise it to ensure it accurately reflects the student and meets legal standards.
As generative AI tools become easier to access, more educators may be tempted to input student information into these tools, compromising the privacy of students and families. Most generative AI tools are not designed with educational privacy laws in mind. Therefore, sensitive information such as disability status, academic performance, or behavioral data can be exposed when entered unsecured systems. As noted above, laws such as FERPA and IDEA are intended to protect this information from unauthorized disclosure; however, many generative AI tools operate outside school-controlled environments and may lack these guardrails. Research has shown that even when systems seem secure, identifying information can still slip through (Marino & Vasquez, 2024). On top of that, there is often very little transparency about how long data is stored or who can access it (Naatz & Ruppar, 2026). Because of these risks, educators must exercise caution when using generative AI tools to support IEP writing.
In addition to privacy, ethical concerns also come into play, especially because IEP development is not just a technical task but a collaborative effort involving multiple professionals and sources of information. Teachers rely on more than just data to develop an IEP. They consider family input, cultural context, behavior patterns, social-emotional needs, and if applicable, input from related service staff. Generative AI cannot fully account for these things. When educators rely too heavily on generative AI, there is a risk that their professional judgment takes a back seat (Naatz & Ruppar, 2026). That is where problems can arise. There is also the issue of bias. Generative AI systems are trained on existing data, and if that data contains bias, those same biases can appear in AI-generated recommendations (Waterfield et al., 2026). This is why the research consistently stresses that generative AI should support teachers, not merely replace them. Educators are still responsible for reviewing, questioning, and refining anything generative AI produces (Rakap & Balikci, 2026).
There are also important legal considerations related to parent and student rights. IDEA gives families a voice in the IEP process. These rights allow them to participate, give consent, and challenge decisions if needed. If generative AI is used behind the scenes without clear communication, that transparency starts to break down. For example, if a parent asks how a goal was developed and the teacher cannot clearly explain it because generative AI was used, that may create confusion or mistrust. This becomes even more serious in situations involving disputes or due process. Overall, decisions must be based on data, observations, and professional reasoning. Teachers must be able to explain and carry out goals and plans for IEPs. That is why professional expertise must remain at the center of every decision.
Educators must remember that IEPs are legally binding documents, so the details matter. Even though AI-generated text often looks polished, it may still be incorrect or inappropriate for a specific student. In some cases, the language may be too vague or not fully aligned with actual assessment data (Waterfield et al., 2026). In addition to accuracy, generative AI doesn’t show its reasoning in a clear, traceable way. If a decision is ever questioned, it can be difficult to explain how that output was created. Because of this, teachers must carefully review everything, ensuring it aligns with real student data and can be defended if needed (Rakap, 2024).
Generative AI is a tool that should be used within clear parameters and with care. Current research supports using generative AI as a starting point, not a final product. It can help with drafting, organizing ideas, or structuring goals, but it should never be used to make final decisions about placement, services, or outcomes. Those decisions require professional expertise and an understanding of the law. Studies continue to emphasize the importance of training, clear guidelines, and ongoing oversight to make sure generative AI is used appropriately (Rakap & Balikci, 2026; Marino & Vasquez, 2024).
Generative AI can be helpful, but it cannot replace the role of the educator. Legal compliance, ethical responsibility, and student-centered decision-making all depend on active professional involvement. Generative AI can function as a support tool, and it is important that educators do not use it as a decision-maker (Waterfield et al., 2026; Rakap, 2024). When used thoughtfully and responsibly, it may improve efficiency. But without careful oversight, it can also create serious legal and ethical issues in special education.
Synthesis and Practitioner Perspectives
When synthesized across studies, the literature indicates that generative AI is most useful in special education when it is used as a support tool rather than a replacement for teacher expertise. Across the research, a clear pattern shows that generative AI may improve efficiency and provide structure, especially for IEP goal writing and organizing student data. At the same time, concerns about accuracy, over-reliance, and maintaining individualization are consistently noted. This shows that the impact of generative AI depends on how it is used in practice.
Across studies, the benefits are most noticeable for teachers who need more support with developing IEP goals. Research shows that beginner teachers produced higher-quality goals when using generative AI, while experienced teachers produced goals of similar quality with or without generative AI support (Rakap, 2024; Waterfield et al., 2026). This suggests that generative AI may assist less experienced teachers in turning present levels into measurable and individualized goals. However, the literature also makes it clear that AI-generated goals can become too general if they are not carefully reviewed, which can take away from the individualized focus required under IDEA.
From a practitioner perspective, these findings suggest that generative AI should be used as a starting point rather than a final product. Teachers and IEP teams can use it to support drafting, organizing information, and generating ideas, but they remain responsible for ensuring that goals are aligned with student data and are developmentally appropriate. At the school and district level, research supports cautious implementation, particularly around data accuracy, staff training, and ethical use (Marino & Vasquez, 2024; Naatz & Ruppar, 2026). Overall, the literature indicates the importance of maintaining professional judgment and clear expectations for use so that IEPs remain individualized and legally compliant.
Conclusion
The literature supports not an expansive, but a measured claim about generative artificial intelligence in special education. As such, generative AI is best interpreted as a bounded support tool, not a broad solution. Its primary usefulness in IEP development is in organizing information and drafting goals. This can reduce the documentation burden tied to compliance tasks. These benefits appear strongest for educators who need additional support in translating present levels into clear, measurable, individualized annual goals and are stronger for less experienced educators. With more experienced educators, generative AI-assisted goals are often comparable to independently written goals, and there is no evidence of consistent superiority. The literature also suggests that developmental context matters. Findings vary by setting and age group. Early childhood studies reveal broader developmental coverage, with greater attention to communication, self-care, and motor/sensory domains. As important as what the literature supports is what it does not support. It does not support generative AI as an autonomous decision maker, as a replacement for educator judgment, nor as a final authority in IEP development or implementation. Concerns throughout the studies include overreliance, reduced individualization, bias, privacy, data quality, and legal compliance. The strongest defensible position of generative AI at this moment is that it may improve efficiency; it may provide structural support, but both benefits depend on the conditions under which the tool is used. While current research is still limited and unable to support broad claims yet, now is the time to create safeguards and necessary conditions for use. These non-negotiables include trained professional review of all outputs, careful handling of student-specific data, legal and ethical safeguards, and ongoing human oversight. Future research requires more disability categories, more age groups, more school settings, and attention to implementation fidelity, decision-making quality, and student outcomes. Generative AI can be effectively used as a support mechanism in a judgment-intensive process. It is not a substitute for individualized obligations in special education. It is not a substitute for educator expertise.
References
Marino, M. T., & Vasquez, E., III. (2024). Special education administrators use of artificial intelligence (AI) to synthesize data. Journal of Special Education Leadership, 37(2), 62-76. https://files.eric.ed.gov/fulltext/EJ1441836.pdf
Naatz, A. J., & Ruppar, A. (2026). Special education teachers’ use of generative artificial intelligence (AI): An exploratory survey of frequency and factors influencing adoption. Journal of Special Education Technology, 41(2). https://doi.org/10.1177/01626434251379800
Rakap, S. (2024). Chatting with GPT: Enhancing individualized education program goal development for novice special education teachers. Journal of Special Education Technology, 39(3), 339-348. https://doi.org/10.1177/01626434231211295
Rakap, S., & Balikci, S. (2026). Enhancing IEP goal development for preschoolers with autism: A preliminary study on ChatGPT integration. Journal of Autism and Developmental Disorders, 56(4), 1682-1687. https://doi.org/10.1007/s10803-024-06343-0
Waterfield, D. A., Coleman, O. F., Welker, N. P., Kennedy, M. J., McDonald, S. D., & Cook, B. G. (2026). IEPs in the age of AI: Examining IEP goals written with and without ChatGPT. Journal of Special Education Technology, 41(1), 57-71. https://doi.org/10.1177/01626434251324592
Assistive Technology Challenges in IEPs and Classroom Practice
By Melissa Cella-Perez, Rebecca Martinez, Sulay Palenque, Melissa Placido, and Michelle Prenat
Literature Review
Assistive technology (AT) is an essential component of equitable special education practice, offering students with disabilities increased access to instruction, communication, and participation. When implemented appropriately, AT can reduce academic barriers, support independence, and promote inclusion across a range of educational settings. Despite its potential, research consistently shows that AT is not always considered, selected, or used in ways that align with best practices. Instead, students often encounter fragmented systems where AT is overlooked during Individualized Education Program (IEP) meetings, implemented inconsistently, or limited by outdated devices and inequitable access. These gaps increase the risk that students with disabilities will not receive the full benefits of technologies designed to support their learning.
Understanding these at-risk areas is critical because AT decision-making does not
occur in isolation; it reflects broader systemic issues related to teacher training, resource
allocation, school-wide accessibility policies, and the level of collaboration among
educators, families, and specialists. When AT is not discussed during IEP development,
when educators are unsure how to use devices with fidelity, or when families lack
training to support communication tools at home, students experience missed
opportunities that affect their academic and social progress. Therefore, a review of the
literature is needed to examine the challenges that continue to limit AT’s effectiveness in
schools and identify the factors that place students at risk for receiving inadequate support.
This literature review synthesizes research on five interconnected challenges: (1)
assistive technology not being considered during IEP meetings, (2) reliance on outdated
or inappropriate technology, (3) inequitable access to AT across schools and districts, (4)
teacher and parent training needs, and (5) implementation fidelity concerns. In addition,
our group’s professional experiences: as educators, ESE liaisons, and Registered
Behavior Technicians (RBTs) provide real-world insight into how these challenges
manifest within school systems. By integrating research with practitioner perspectives,
this review highlights the systemic issues that hinder effective AT use and identifies
recommendations for improving access, training, and implementation across educational
environments.
AT not Considered during IEPs
Although the Individuals with Disabilities Education Act (IDEA) requires
IEP teams to consider AT for every student with a disability, research shows that this step
is not consistently implemented. In their systematic review, Fernández-Batanero et al.
(2022) found that AT is widely recognized as beneficial for improving accessibility,
participation, and overall inclusion, yet its use in schools remains inconsistent. Their
analysis shows that AT is often not embedded into routine educational planning,
including the processes of IEP development, despite its documented potential to support
academic engagement and independence.
The authors note that many schools lack structured procedures to help IEP teams
identify and discuss AT options, This absence contributes to uneven decision-making,
resulting in AT being overlooked when teams evaluate student needs. Although AT has
the potential to enhance learning and expand participation, the studies reviewed by
Fernández-Batanero et al. (2022) reveal that it is frequently omitted from planning
conversations, suggesting that AT consideration is not yet a systematic or intentional part
of the IEP development.
Our group’s professional experiences closely reflect these findings. Across our
roles as general education teachers, special educators, and RBTs, we have participated in
numerous IEP meetings where AT is rarely discussed. Typically, discussions focus
heavily on accommodations, behavioral supports, or service minutes. AT, however, is
often absent from the conversation. These real-world observations align with the patterns
identified by Fernández-Batanero et al. (2022), who emphasize that AT continues to be
underutilized despite its demonstrated benefits.
Together, the research and our collective experiences suggest a critical issue: AT
consideration is not yet a consistent or embedded component of IEP meetings in many
educational settings. When AT is not discussed, students may miss opportunities to
receive tools that could enhance learning, communication, and promote independence.
Ensuring meaningful AT consideration during IEP development is therefore a key step in
improving equitable access that supports and promotes inclusion.
Outdated/Inappropriate
Technology integration in K–12 special education (SPED) is both an equity
concern and a financial challenge, as many schools lack the resources to provide up-to-
date AT that aligns with students’ individualized needs. Although AT is intended to
enhance access and promote learning, students frequently encounter devices that are
outdated, unreliable, or poorly matched to their disability-related needs. Starks and Reich
(2022) found that budget limitations and inequitable resource allocation significantly
restrict the availability of appropriate AT in schools, often forcing teachers to rely on
general-purpose technologies that do not fully support accessibility. These systemic
barriers highlight a mismatch between what AT is designed to provide and what students
actually receive in practice.
The findings from Starks and Reich (2022) further illustrate how these resource
limitations affect everyday practice. In their study, 65% of teachers reported inadequate
student access to devices, Additionally, 90% of participants reported insufficient
technology focused training, contributing to SPED teachers feeling “left out” of district-
level technology planning and decision-making. When educators lack both updated tools
and the support needed to use them effectively, reliance on outdated or generic devices
becomes the default.
Collectively, these challenges restrict students’ opportunities to engage with AT
tools that support communication, independence, and participation. Outdated or poorly
matched technology not only limits access to curriculum but also undermines efforts to
design inclusive learning environments. The literature underscores the need for more
equitable resource distribution, specialized professional development, and sustainable
funding structures to ensure that SPED classrooms have AT that is current, functional,
and responsive to student needs.
Equity and Access
Equitable access to AT remains a persistent challenge in special education, as
resources, training, and policy implementation vary widely across districts. Even when
AT is included in policy language, students’ actual access to devices and support often
depends on local priorities and funding decisions. In a multiple case study of U.S. school districts, Shaheen (2022) found that students’ access to accessible and assistive
technologies was strongly influenced by how districts interpreted and enforced
accessibility requirements. Although federal law mandates equitable access, Shaheen’s
findings show that implementation is uneven, resulting in significant disparities in the
availability and quality of AT across educational settings.
A recurring challenge involves gaps in teacher knowledge and misconceptions
about what qualifies as AT. Many educators assume that AT refers only to high-tech
tools, which leads to the underuse of low-tech supports, such as graphic organizers, visual
schedules, timers, or adapted materials, that fall squarely under IDEA’s definition of
assistive technology. When teachers overlook these tools, they also overlook
opportunities to support student learning with easily accessible, low-cost options. These
misconceptions contribute to inconsistent AT documentation in IEPs and missed
opportunities to integrate AT into classroom routines.
Shaheen’s (2022) research underscores that equity in AT access is shaped by three
interconnected factors: district funding decisions, educator preparation, and the level of
commitment to enforcing accessibility policies. Improving equity will require districts to
establish clear procedures for AT evaluation, prioritize ongoing professional
development, and implement stable funding systems that support timely access to
appropriate devices. When educators have both the tools and the knowledge needed to
use AT effectively, schools can provide more consistent and equitable support that
enhances learning for students with disabilities.
Teacher/Parent Training
AT and augmentative and alternative communication (AAC) play a critical role
in supporting students with disabilities by expanding their access to instruction and
enhancing communication. Understanding how these tools are used in classrooms and at
home is essential, particularly because their effectiveness depends heavily on the adults
who support them. Research shows that when teachers and families receive appropriate
training, students who rely on AT or AAC demonstrate stronger communication,
participation, and academic progress.
Hansen and Donne (2025) examined how special education teachers incorporate
AT into classroom practice, finding that although many educators feel confident using
basic technologies, they often lack formal training and ongoing support. Teachers
reported frequent use of universal tools; such as touchscreens, keyboards, and basic
computer accessories, but far less comfort with specialized AT, including AAC systems,
adaptive switches, and eye-gaze technology. Despite nearly two-thirds of participants
having students who relied on AAC, many indicated a need for additional professional
development and more consistent guidance from AT coordinators or specialists. These
findings suggest that limited training creates gaps between students’ needs and teachers’
comfort or expertise in using advanced AT tools.
While Hansen and Donne (2025) focused on school-based implementation, Soto
and Vega (2024) explored how families are prepared to support AAC at home. Their
review of caregiver training programs identified several competencies that improve
children’s communication outcomes, such as responsivity, setting up the environment to
encourage interaction, using wait time, modeling language through AAC, providing
prompts, and recasting or expanding children’s communicative attempts. However, Soto
and Vega (2024) found that many parents receive minimal training and often feel
overwhelmed by the responsibility of managing complex communication systems on
their own. The authors emphasized the importance of strong home–school collaboration
to help children transfer communication skills across settings.
Together, these studies highlight that teacher and parent training are essential
components of effective AT and AAC use. When educators and caregivers lack
structured preparation, coaching, and ongoing support, students have fewer opportunities
to practice communication skills or apply AT tools meaningfully. Improving training
requires targeted professional development, clear and accessible family training
programs, and consistent collaboration among teachers, therapists, and families. When
the adults who support a child are confident and well-prepared, assistive technology can
lead to significant gains in communication, engagement, and academic success.
Fidelity
High-fidelity implementation of AT is critical for ensuring that students receive
the full benefit of the tools provided to support communication, learning, and
participation. Fidelity refers to how accurately and consistently educators embed AT into
daily instruction; modeling device use, integrating it across activities, and individualizing
the system to meet student needs. Even when AT is available, inconsistent or partial use
can significantly limit its impact.
Evmenova et al. (2022) examined how schools move from initial adoption of
technology to sustained, high-quality implementation, offering insights that align closely
with fidelity challenges in AT. Their findings show that educators are more likely to use
technology with fidelity when they have structured opportunities to practice, receive
feedback, and reflect on implementation. Without these supports, technology use
becomes irregular or superficial, reducing the likelihood that students will engage with
AT consistently throughout the school day.
A key contribution from Evmenova et al. (2022) is the emphasis on ongoing
coaching rather than one-time training. Their research indicates that fidelity improves
when teachers receive continuous guidance that helps them integrate technology into
existing instructional routines. This process builds the confidence and fluency necessary
to use AT naturally and effectively, rather than viewing it as an additional or isolated
task. For AT specifically, this means embedding device use in authentic communication
opportunities, modeling vocabulary, and providing students with repeated practice across
contexts.
Importantly, the work of Evmenova et al. (2022) positions fidelity as a systems-
level component of effective technology use. High-fidelity implementation requires clear
expectations, time to collaborate with specialists, and consistent opportunities for skill
development. When these elements are in place, AT is more likely to be used as intended;
supporting communication, increasing student engagement, and strengthening access to
Instruction.
Across the literature, it is evident that AT can significantly improve
communication, participation, and learning for students with disabilities, yet many
barriers prevent its full impact. AT is not always considered during IEP meetings, and
when devices are provided, they are often used inconsistently or with limited fidelity.
Inequitable access, outdated equipment, and gaps in teacher understanding further
complicate the effective use of AT in classrooms. Families also need clearer training and
support to help students generalize communication skills beyond school. Together, these
challenges highlight the systemic nature of AT implementation and the multiple points at
which support can break down.
These findings underscore the need for stronger structures that prioritize
accessibility and consistency. Schools must ensure meaningful AT consideration during
IEP development, invest in sustained and high-quality professional development,
maintain reliable funding systems that allow for updated and appropriate AT devices.
Strengthening collaboration among teachers, therapists, specialists, and caregivers is
essential so that students receive consistent support across home and school
environments. When these elements are in place, AT is more likely to be used as
intended; functioning as a powerful tool for inclusion and helping students participate
more fully, communicate more effectively, and engage confidently in their educational
environments.
References
Evmenova, A. S., Regan, K. S., Schladant, M., Hall, T. E., Buzhardt, J., Erickson, K. A., Ai, J., Sudduth, C., & Jackson, T. (2022). Stepping-Up Technology Implementation—How Does it Happen? Journal of Special Education Technology, 38(1), 61–74. https://doi.org/10.1177/01626434221074357
Fernández-Batanero, J. M., Montenegro-Rueda, M., Fernández-Cerero, J., & García-Martínez, I. (2022). Assistive technology for the inclusion of students withdisabilities: a systematic review. Educational Technology Research andDevelopment, 70(5), 1911–1930. https://doi.org/10.1007/s11423-022-10127-7
Hansen, M. A., & Donne, V. (2025). Special education teachers’ post-pandemic use of assistive technology. Disability and Rehabilitation: Assistive Technology, 1–17. https://doi.org/10.1080/17483107.2025.2584414
Shaheen, N. L. (2022). Technology accessibility: How U.S. K–12 schools are enacting policy and addressing the equity imperative. Computers & Education, 179, 104414. https://doi.org/10.1016/j.compedu.2021.104414
Starks, A. C., & Reich, S. M. (2022). “What about special ed?“: Barriers and enablers for
teaching with technology in special education. Computers & Education, 193, 104665. https://doi.org/10.1016/j.compedu.2022.104665
Soto, G., & Vega, J. (2024). Exploring core competencies for language facilitation in parent training programs in AAC. Disability and Rehabilitation: Assistive Technology, 20(4), 1035–1043. https://doi.org/10.1080/17483107.2024.2429687
Acknowledgements
Portions of this or previous month’s NASET’s Special Educator e-Journal were excerpted from:
- Center for Parent Information and Resources
- Committee on Education and the Workforce
- FirstGov.gov-The Official U.S. Government Web Portal
- Journal of the American Academy of Special Education Professionals (JAASEP)
- National Collaborative on Workforce and Disability for Youth
- National Institute of Health
- National Organization on Disability
- Substance Abuse and Mental Health Services Administration
- U.S. Department of Education
- U.S. Department of Education-The Achiever
- U.S. Department of Education-The Education Innovator
- U.S. Department of Health and Human Services
- U.S. Department of Labor
- U.S. Food and Drug Administration
- U.S. Office of Special Education
The National Association of Special Education Teachers (NASET) thanks all of the above for the information provided for this or prior editions of the Special Educator e-Journal
Sarah S. Ayala, LSU | Associate Editor, NASET e-Journal
