NeuroClass VR: A Journey For an Inclusive and Adaptive Classroom

Project Duration: 2023/9 ~ 2023/10

Abstract

In our pursuit of equitable and inclusive education, we confront a landscape fraught with challenges posed by diverse learning styles, cognitive abilities, and special educational needs.

Traditional methods have largely fallen short, leading to a system where approximately 14% of all public school students in the U.S. require special education services, and only 68% of students with learning disabilities complete high school. Our research addresses these systemic issues by introducing a scalable, modular, and adaptive educational platform delivered via Virtual Reality (VR) and monitored by Brain-Computer Interfaces (BCIs), named NeuroClassVR.

Initially, we sought to build a one-size-fits-all platform targeting common learning differences like ADHD and dyslexia. However, we pivoted towards a more modular architecture upon recognizing the complexity and diversity of cognitive profiles in classrooms. Drawing inspiration from the principles of software modularity and personalized medicine, we designed a base VR platform that incorporates specialized “modules” for various cognitive needs. Each student receives a customized educational experience by selecting modules that best fit their cognitive profile.

As a proof of concept, we developed ReadScapeVR, a specialized module focusing on dyslexia— an issue affecting 5-10% of the population. Unlike traditional paper-based methods, ReadScapeVR immerses students in a 3D world, leveraging a gamified interface to maximize engagement. The platform is deeply rooted in empirical evidence; we conducted comprehensive studies involving dyslexic children and healthcare practitioners to ensure that our solution addresses the shortcomings of current treatments. One of the groundbreaking features of ReadScapeVR is its real-time neurophysiological monitoring through BCI technology. This allows the platform to adapt its teaching methods based on a student’s focus and emotional state. This adaptability was identified as crucial by clinicians and users alike. Moreover, the platform is designed to be financially feasible, health risk-minimized, broadly accessible, and secure, addressing key concerns of healthcare providers. Importantly, ReadScape VR serves as a foundational piece in a much larger puzzle of creating a modular educational platform that would allow for specialized

‘modules’ targeting distinct cognitive profiles through the use of VR and BCI-NeuroClassVR.

NeuroClassVR, when fully deployed, will allow for greater customization and adaptability. It employs machine learning algorithms to continually refine module selection based on real-time performance metrics and cognitive states. Its modular design also ensures the system stays abreast with emerging research findings and evolving educational needs, allowing new modules to be seamlessly incorporated. Our approach doesn’t merely seek to accommodate learning differences; it aims to celebrate neurodiversity. We challenge the stigmatization often linked with learning disabilities, championing a paradigm shift in how society perceives cognitive diversity. We envision a future where every student feels valued for their unique cognitive abilities, enhancing not just educational outcomes but also self-worth and social inclusion.

In summary, our research culminates in the conception of NeuroClassVR—a pioneering educational platform that combines VR and BCI technology to deliver a personalized, adaptive, and inclusive educational experience. As a prototype, ReadScapeVR serves to illustrate the capabilities of our framework. The innovation lies not just in the technology but also in the underlying philosophy that celebrates neurodiversity as an asset rather than a limitation. As we continue to develop more specialized modules, NeuroClassVR holds the promise of becoming a cornerstone in realizing an educational system where every student, regardless of their cognitive profile, is given the resources and opportunities to thrive.

Snippet of the final presentation