Computational Physics as an Inclusive Didactic Framework for Autistic Students in Higher Science, Technology, Engineering, and Mathematics Education

Abstract

Students on the autism spectrum frequently demonstrate remarkable intellectual strengths in science, technology, engineering, and mathematics, particularly in disciplines requiring advanced pattern recognition, logical reasoning, and systematic problem solving. Despite these cognitive advantages, autistic students experience disproportionately high dropout rates in university physics programs. This paradox arises less from the intrinsic complexity of physics than from the pedagogical barriers embedded in traditional instruction, including sensory-overloading laboratory environments, linguistically ambiguous problem statements, and the social demands of collaborative learning.

This conceptual study investigates how computational physics can be redesigned as an inclusive pedagogical framework that capitalizes on the cognitive strengths of autistic students while minimizing environmental, linguistic, and social barriers to learning.

Grounded in Simon Baron-Cohen's Empathizing–Systemizing theory, the proposed framework replaces conventional laboratory activities with highly structured computational learning environments based on Python programming and physics simulations designed according to user interface and user experience principles. The framework incorporates explicit algorithmic instruction, sensory-conscious digital environments, deterministic learning activities, and transparent assessment strategies tailored to the cognitive characteristics of autistic learners.

The proposed approach is expected to improve student retention, conceptual engagement, learning autonomy, and psychological well-being by creating predictable and cognitively accessible learning environments. The article introduces comparative pedagogical models, conceptual frameworks, and instructional workflows illustrating how computational physics can reduce sensory and cognitive barriers while promoting deeper conceptual understanding.

Computational physics offers a natural alignment with the cognitive profile frequently associated with autism by emphasizing logical structure, predictability, and systematic reasoning. Designing physics instruction according to principles of neurodiversity and inclusive pedagogy has the potential to transform barriers into opportunities, enabling higher education institutions to better support autistic students while fostering scientific excellence through cognitive diversity.

Keywords: Neurodiversity; Autism Spectrum; Computational Physics; Physics Education; Inclusive Education; Science, Technology, Engineering, and Mathematics Education; Universal Design for Learning; Empathizing–Systemizing Theory; Higher Education.

Received Date: February 22, 2026

Accepted Date: March 14, 2026

Published Date: April 02, 2026

Available Online at: https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/767