Systematizing Cognitive Inclusion In Online Learning Through Maturity Modeling

The enrollment of students with autism spectrum disorder (ASD) and ADHD in Higher Education has grown substantially, driven by inclusion laws. However, Distance Learning (DL) modes exhibit concerning dropout rates for this demographic. The core problem to be addressed involves the barriers within Virtual Learning Environments (VLEs) that overlook cognitive variability, creating a digital ecosystem that is often inaccessible to neurodivergent students. A Systematic Literature Review (SLR) of 38 studies revealed that, while visual accessibility guidelines (WCAG) are well-established, previous research and related works have yet to solve the absence of an engineering framework for Cognitive Accessibility. As expected contributions, this doctoral research proposes the development of the Cognitive Accessibility Maturity Model (CAMM), a novel technical artifact designed to guide the evolution of DL systems. The study’s primary contribution is the development of the Cognitive Accessibility Maturity Model, a novel technical framework designed to guide the engineering of Virtual Learning Environments that account for cognitive variability. By moving beyond traditional WCAG guidelines, this work provides a structured roadmap for institutions to evolve their digital ecosystems, ultimately fostering higher retention and academic success for students with ASD and ADHD.