Designing Learning for a Neuroinclusive Classroom

Every April marks Autism Acceptance Month, where organizations like the Autism Society move us beyond awareness and toward making accessibility an integral part of a classroom’s design. With this in mind, in this article we take a critical look at how instructional design can support teaching to a diverse class of students and discuss some of the scientific evidence that can be translated into meaningful classroom impact. We focus especially on neurodivergent students, that is, students with conditions like autism that cause their brains to learn and function differently than what is considered neurotypical.

Co-mentorship and neuroinclusive design

Five years ago, I (Stacey) entered HMH’s mentoring program and connected with Francie, who helps lead the company’s efficacy research work. My interest in education research was beginning to take root, and I was eager to learn from a well-established leader in the field. What I didn’t anticipate was that Francie wanted to learn from me as well—a dynamic I have come to recognize as co-mentoring. I offered new perspectives too, and we shared common curiosities and passions.

This reciprocal approach to mentorship is research-based and has been gaining traction as a way of solving problems and improving outcomes. Learning is not anchored by a view of an expert handing information off to a novice, but rather by the structure and intention behind the learning itself. The same philosophy can apply to classroom learning, too, where many students are left out if teachers simply present the information as a whole-class lecture.

Our work at HMH involves not only trying to do well as an organization, but more importantly, trying to do good for those we serve: students and educators. We design our solutions intentionally to the benefit of all our students, keeping in mind that Universal Design for Learning (UDL), an evidence-based framework developed by CAST, requires that we meet the most significant needs of all of our students. This isn’t a matter of compliance for us and our colleagues, but work we undertake with conviction.

The quality of every learning experience relies heavily on design decisions made long before a student enters the classroom. UDL highlights how proactive instructional design can reduce learning barriers before instruction begins. Applied in practice, this means designing instruction for a neurodiverse audience from the outset so that barriers are removed before students are ever asked to overcome them.

Designing learning at HMH

The work at HMH includes conducting scientific studies, doing qualitative research, and listening to our partners who are doing the critical work of teaching our students. Just listening is arguably the most important and impactful work any of us can do. Simply by teaching, educators are addressing the challenge of bringing research to scale in service of every classroom, every student.

Every teacher has a classroom filled with learners who represent extraordinary variability. When we talk about intentional design, this means we design for a range of learning needs from the beginning. Instead of creating a separate learning track for certain students, learner variability is anticipated and fundamentally incorporated into the instructional design. Some describe this as designing curriculum and carrying out instruction with “all minds in mind” or perhaps using the frame, “Students learn best when ___.” Here are some of the lessons from the learning sciences which can help us complete that sentence.

Belonging

I (Francie) taught a class of K–3 students as part of a research effort on multi-age learning. There was only one class configured in this way in my school and district, and the children themselves were somewhat perplexed when asked, “What grade are you in?” I posted a poem adapted from and inspired by the “Breton Fisherman’s Prayer”:

The world is so very big, sometimes I feel so small.
I’m happy that in my classroom there is a place for all.

Research suggests that a sense of belonging has a positive impact on student success. While this benefits all students, it’s of special import when meeting the needs of students who have unique requirements to be successful. Let’s finish the sentence: Students learn best when they experience the feelings of acceptance and respect which come from belonging.

Feedback

All of us want to know how we’re doing. Feedback is most effective when it’s timely and specific. John Hattie’s Visible Learning meta-analysis of what works reveals that feedback has one of the largest impacts on student outcomes. Students learn best when feedback clarifies how they are doing and how they improve. 

Practice

You might have heard the joke: How do you get to Carnegie Hall? Practice! Practice! Practice! There’s a robust evidence base for practice, and here is an area where we can build on learning science to individualize and harness the power of technology. Just like how the dosage of vitamins may be modified for different ages and stages, so may practice be modified to the unique needs of the learner. Students learn best when they have structured opportunities to practice so that they can apply new learning over time.

Multiple representations

There are multiple ways to show what you know. Writing, visuals, and speaking are chief among them. It’s important for teachers to model multiple ways of thinking and doing in their work so that students will learn how to use them to represent their own. Sometimes it’s effective to teach using multiple modes for the same purpose, such as “dual coding,” where students are presented with both a verbal and a visual explanation. Students learn best when they use multiple modes to share their own thinking, too.

Motivation

We ask a lot of our students. On a given day they learn new things in a multitude of subjects and interact with other kids and adults. What gets students to exert the effort to learn and grow is a significant area of variability. We must help all students find their why. Students learn best when they are motivated to invest in themselves because they experience belonging and feel that success is possible.

Supporting neuroinclusive teaching with evidence-based research

We are not alone in this work; across the field, educators, researchers, and accessibility leaders are contributing complementary perspectives on how intentional design can better support neurodivergent learners. We spoke with Beth Raichle, HMH’s director of accessibility and chair of the accessibility advisory board, who explains: “Cognitive accessibility goes beyond a checklist. It’s about supporting diverse needs through specific design choices.” For teachers, those choices include how feedback is delivered and how information is represented.

Neurodiversity‑centered research helps to clarify how those design decisions influence learning. As one example, rather than viewing all redundancy as inefficient, autism‑affirming practice recognizes its role in supporting pattern recognition and confidence—especially when content is scaffolded and offered through multiple modalities that reduce pressure to process or respond in the moment. We also spoke with Cate McCarey, who leads user experience research for HMH’s curricular solutions: “By gathering and comparing assistive technology use year over year, we can better understand how autistic learners—and those with related IDEA disabilities—navigate content, build skills, and demonstrate knowledge.”

A note on language: Here we use the phrase “autistic learner,” but learners on the autism spectrum do not fit neatly into a single label and may prefer another term, such as “learners with autism.”

When learners are given meaningful choices—such as responding digitally instead of verbally during whole‑class discussion, or choosing content based on areas of personal interest—they are more likely to feel intrinsically motivated and genuinely engaged.

Early in our co‑mentoring partnership, I (Stacey) shared a five‑year mind map—images that made my professional goals concrete, including a plan to pursue graduate study. With Francie’s guidance, that plan took shape. Now, I’m a student at Cal State University, Monterey Bay’s Master’s Program in instructional Science and Technology, specifically drawn to research on why design matters and what happens when learning environments place unnecessary demands on neurodivergent students. Here’s some of the work aimed at studying how instruction can be designed with a neurodiverse audience in mind:

• John Sweller’s cognitive load theory shows how reducing unnecessary complexity and improving structure makes learning experiences more cognitively manageable by design.
• Barry Prizant and colleagues’ autism‑affirming research on behavior, such as work developing the SCERTS model for teaching young children with autism, addresses how to design learning experiences that anticipate different sensory and cognitive needs.
• Work by Deborah Lowenberg Ball and colleagues has highlighted the need for a high-quality educational infrastructure, which includes a wide range of interconnected pieces, such as curriculum, assessments, and standards.
• Kathryn Finnigan’s research examines how to design classrooms and other environments in a way that specifically considers autistic children, such as avoiding cluttered, visually busy spaces, which can increase distraction and fatigue. Predictable layouts, clear organization, and intentional pacing support attention and emotional regulation. These are not just aesthetic choices; they are instructional decisions that reduce cognitive load and make classrooms easier to manage throughout the day.

Instructional design and educational technology

Taken together, this research points to the importance of intentional instructional design through environments, materials, and routines that reduce unnecessary barriers before they surface. From a teacher support perspective, educational technologies—including artificial intelligence—can serve as powerful scaffolds, but not substitutes, for effective teaching. AI‑supported tools, such as Writable, can offer targeted feedback and support revision without replacing or compromising student voice.

Using AI in the classroom can also serve as a bridge to participation. Some autistic students find it cognitively easier to rehearse what they plan to say or script ideas with technology before engaging socially. This supports classroom participation while reducing pressure on teachers to individually mediate every interaction. The goal is not automation—it’s accessibility.

In some sense, neuroinclusive teaching can be seen as an act of design. When anyone working in education designs instruction that affirms students’ individual backgrounds and experiences, they create space for autistic students to contribute knowledge, skills, and perspectives worth celebrating. When the instruction is designed carefully, instructional goals remain clear, and multiple pathways are given to learners, ensuring everyone can find a path. A well-designed instructional experience doesn’t just benefit autistic students; it benefits everyone.

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