Supporting Neurodiverse Learners through Computational Thinking

A new project uses computational thinking materials with neurodiverse groups of students.

by Knology
Apr 12, 2023

Within educational contexts, the concept of "computational thinking" (CT) has generated increasing interest in recent years. An innovative approach to learning, CT draws on problem-solving techniques often used in computer science. Commonly taught through programming activities, CT-based educational interventions have become especially popular with computer science and technology teachers.

But as researchers have pointed out, CT is "more about thinking than computing." It's a systematic, step-by-step learning methodology that teaches students strategies for breaking big problems down into smaller, more manageable pieces (known as "problem decomposition"). In showing students how to deal with things that feel overwhelming, CT seeks to help them discover generalizable problem-solving processes that can be applied across a wide variety of contexts. Studies suggest that CT offers an effective means of tapping into the cognitive strengths of neurodivergent students (for example, those who might be diagnosed with dyslexia, ADHD, or autism), and that CT-based interventions can help further skills development among neurodiverse groups of learners.

Neurodiversity and CT

The term "neurodiversity" refers to differences and variations in the way people think, process information, complete tasks, and learn. As a concept, the term challenges traditional ways of thinking about commonly labeled disabilities such as autism, ADHD, dyslexia, and dyscalculia. Instead of seeing these conditions as problems that need to be fixed or cured, neurodiversity depathologizes them. It promotes "neurological pluralism"—that is, the recognition that there many are different forms of cognitive functioning, and that instead of trying to bring everyone toward some kind of neurotypical ideal, our goal should be to affirm and accommodate neurological difference.

From an educational standpoint, neurodiversity helps us see that learner variability is a strength–something to be unleashed within the classroom. It entails the creation of learning supports that enable students with wide-ranging cognitive and sensory needs to flourish. In particular, it offers a path for recognizing the unique abilities and aptitudes of different kinds of learners, for creating more diverse approaches to problem-solving, and for helping all students develop valuable skills aligned with their interests and inclinations.


To promote the use of CT among neurodiverse groups of students, in 2019, a consortium of educational developers launched INFACT (Include Neurodiversity in Foundational and Applied Computational Thinking). Led by EdGE at TERC, a team of educators, designers, and researchers who develop and study STEM learning games, the consortium brings together experts in STEM education, CT, and neurodiversity. INFACT seeks to infuse CT in elementary and middle school curricula. To build a foundation for the use of CT in various subjects, project leaders are developing a suite of CT-based learning materials, activities, and practices for students in grades 3-8.

Since the project's inception, Knology has served as INFACT's evaluator. Our role here builds on our work as evaluators of two previous CT initiatives—both of which have informed INFACT's development. Between 2015 and 2019, the EdGE at TERC team re-released a video game for tablets called "Zoombinis," and also developed bridging materials to support teachers using the game for classroom instruction. In our evaluation of this project (NSF award #1502882), we found that Zoombinis constituted a valuable tool for teaching CT in the classroom. For more on this, see our official report or this summary of our main findings.

It was during that project—officially known as "Zoombinis: The Implementation Research Study of a Computational Thinking Game for Upper Elementary and Middle School Learners"—that we first saw evidence of a possible relationship between computational thinking and neurodiversity. Concurrently, starting in 2017, the EdGE team partnered with a medium-sized school district to work with teachers and co-design materials to infuse computational thinking across the existing curriculum (NSF award #1738574). Knology also served as process evaluators for this project.

Many of the ideas emphasized in INFACT grew out of these earlier projects. As with them, thinking about cross-curricular and flexible adaptations of CT was critical to the design of INFACT. Created to be accessible to a broad range of learners, the INFACT curriculum is flexible and customizable: it includes options for both offline activities and online games and programming, and does not require that teachers have a background in computer science or computer programming. A key aim of the curriculum is to ensure that CT benefits students who need support in certain cognitive areas—in particular, those who struggle with attention, working memory, information processing, or other aspects of executive functioning (EF).

In addition to designing a CT program for use in a wide range of classrooms, the INFACT project has several other goals. These include:

  • Creating a suite of pedagogical tools and resources that help teachers implement the INFACT curriculum;
  • Creating a set of outcome measures and assessments that teachers can use to monitor and support learners' progress in both knowledge and use of CT practices; and
  • Studying INFACT's impact on a broad range of learners.

Through all of this, INFACT seeks to improve learners' knowledge and use of CT practices, and to improve their self-efficacy as problem-solvers.

Evaluating INFACT

Through a series of studies, we've assessed the impact of INFACT's interventions, while also providing guidance to project leaders. This landing page provides links to (and brief descriptions) of all of our work with INFACT, which includes position papers and evaluative reports. We'll be updating this as new reports and articles come out, so be sure to check back here frequently as the project continues!

Teaching in the Age of COVID-19: Computational Thinking & Support for Educators (2020)

Based on conversations with 12 educators, this study surveyed the landscape of US education in public, private, and charter schools during the early stages of the COVID-19 pandemic. Focusing on the implications of CT as a distance learning tool, our interviews highlight some of the ways this approach could help teachers navigate the challenges of remote education. Read our full study here.

Education in the Pandemic & the Potential for Computational Thinking (2020)

Based on interviews with 18 educators from across the US, this position paper reviews some of the educational innovations (including experiments with remote and hybrid learning) that emerged in the first year of the COVID-19 pandemic. Drawing out some of the advantages and potential of CT, our interviews revealed that educators familiar with CT saw it as something that would not only help students learn how to think, but also help teachers deal with questions of educational equity in their classrooms. Read a summary, or get the whole paper.

INFACT Efficacy Report (2022)

For this study, we compared outcomes on a computational thinking assessment between neurodiverse classrooms using either INFACT or the "business-as-usual" CT instruction that teachers in control schools were already providing. Read a summary, or get the whole report.

Including Neurodiversity in Computational Thinking (2024)

Published in the journal Frontiers in Education, this study of INFACT’s implementation shows that students using this program showed significant improvements in CT learnings compared to comparison classes. Our findings offer promising evidence that differentiated activities with EF scaffolds situated across several contexts (for example, games, puzzles, physical activities, robotics, and coding) promote effective CT learning in grades 3-5, and also show promise in revealing the problem-solving strengths of neurodivergent learners. Read the paper.

About the Project

The contents of this web article were developed under a grant supported by the Education Innovation and Research Program (EIR) of the U.S. Department of Education under the project INFACT: Include Neurodiversity in Foundational & Applied Computational Thinking, award U411C190179. However, those contents do not necessarily represent the policy of the Department of Education, and endorsement by the Federal Government should not be assumed.

Photo by Robo Wunderkind @ Unsplash

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