What 14 Years In Special Education Taught Me About Accessibility

By Kimberly Barnes, Director of Special Education Learning Experience

As Director of Special Education Learning Experience at HiNAIA, I bring something that's often missing from edtech development: the lived experience of sitting across from a student who's been told they're "not smart enough" for advanced coursework, when the real issue is that the system hasn't figured out how they learn best. 

Fourteen years in special education and mathematics classrooms, from self-contained environments to dual enrollment programs, taught me that the difference between a student who thrives and one who struggles often comes down to whether the learning environment can adapt to their needs. Now, as we build AI-powered tools for students with ADHD and learning disabilities, those classroom lessons are shaping every product decision we make. 

This is part one of a two-part series. In this post, I’ll share three lessons from the classroom that guide our work today, with more to come in part two. Stay tuned. 

Lesson 1: Data Without Context Is Just Numbers 

In special education, we collect data on everything. Behavior frequency charts, academic progress monitoring, social skills assessments. If it can be measured, we measure it. But here's what I learned: data only becomes useful when you understand the story behind it. 

Take Max (a pseudonym), a student I had years ago.  He scored in the severe range on the Childhood Autism Rating Scale. The numbers suggested significant challenges across multiple areas. But when you looked deeper, Max had age-appropriate reasoning skills and strong problem-solving skills. In fact, he loved building complex structures with an Erector Set, manipulating nuts, bolts, and screws with precision. The data told one story; the context revealed his actual potential. 

Most educational platforms stop at the surface data (completion rates, time on task, correct answers). They miss the nuanced patterns that special education teachers learn to recognize: the student who performs better with background noise, the learner with processing differences who needs extra time to formulate responses but demonstrates deep understanding when given the chance. 

Redefining Accessibility in Special Education: We can't just track whether students get answers right. We need to understand how they arrive at those answers, what accommodations they naturally use, and what environmental factors support their learning. 

Lesson 2: One Size Fits None 

My research on ability grouping and tracking systems during my master's program revealed a troubling pattern. Schools consistently sort students into rigid categories (gifted, standard, remedial) based on narrow assessments that often reflect test-taking skills rather than intellectual capacity. Once placed in these tracks, students rarely move between them. 

In my professional experience, I saw this rigidity play out differently but with the same damaging effect. Students could self-select into higher-level courses, which seemed progressive. But if they struggled and tried to switch to a different level, they faced enormous pushback from administrators and counselors. The message was clear: once you've made your choice, you're stuck with it, regardless of what you learn about your own needs or capabilities. 

The same thing happens with educational technology. Most assistive technology and AI tools are designed for the mythical "average learner" and then attempt to accommodate differences through superficial modifications: bigger fonts, slower pacing, or simplified content. But students with learning differences don't need watered down materials that lower the bar. They need different pathways to the same rigorous learning objectives. 

I've worked with students labeled as "low-performing" who could engage in sophisticated mathematical reasoning when the content was presented visually instead of through text, or when they could manipulate physical objects while thinking through problems. The issue wasn't their intellectual ability; it was the limited ways they were allowed to demonstrate and develop it. 

Redefining Accessibility in Special Education: True personalization means creating multiple pathways to learning objectives, not just adjusting the speed or difficulty of a single pathway. It means recognizing that a student who struggles with reading comprehension might excel at spatial reasoning and building tools that leverage and celebrate strengths rather than only addressing needs. 

Lesson 3: Accommodations vs. Modifications 

There's often confusion between accommodations and modifications. 

Accommodations change how students access information or demonstrate knowledge without changing the learning objectives. Modifications alter the actual content or expectations. Both have their place, but the distinction matters enormously. 

Most educational AI and assistive technologies provide accommodations: text-to-speech, extended time, or graphic organizers. These are valuable, but they don't address the deeper challenge: modifying the learning experience based on how individual students process information. 

When I worked with students who had attention difficulties, I learned to recognize the subtle shifts in engagement: fidgeting, eye contact patterns, and changes in responsiveness.  I could adjust my teaching approach in the moment, shifting from direct instruction to hands-on activities, or providing a movement break before cognitive overload led to frustration. 

In my classroom, the approaches I used consistently gave students both structure and agency in their learning. It created a predictable rhythm while still allowing them to feel a sense of control, even when they weren’t particularly fond of the subject. They understood what was expected, could see their own progress, and had the flexibility to engage in ways that aligned with their energy and focus levels that day. Over time, I saw how the right balance of consistency and choice could shift their outlook and strengthen their connection to learning.  

Redefining Accessibility in Special Education: We need solutions that can recognize these same patterns and modify accordingly. Not just when a student explicitly says they need help, but when their behavior indicates that learning demands are shifting. 

Building EdTech That Actually Serves 

These lessons from my special education practice aren't just nice-to-have features, they're fundamental requirements for tools that truly support learners with differences. That’s why at HiNAIA, we're building AI powered tools grounded in Universal Design for Learning principles.  

The most important lesson from 14 years in special education is this: students with learning differences aren't broken versions of typical learners who need to be fixed. They're learners with different strengths, different processing patterns, and different needs for accessing and demonstrating knowledge. 

Accessible assistive and AI technologies have the potential to finally create learning environments that adapt to these differences rather than requiring students to adapt to inflexible systems.  But that potential will only be realized if these tools are designed with a deep understanding of how learning actually works for students who have historically been underserved. 

Every student deserves learning experiences designed with their success in mind.   

This concludes Part I! Stay tuned for Part II coming soon. Sign up below to receive news, notifications and be the first to know when it’s released.