Abstract
As artificial intelligence and digital tools become more embedded in everyday life, the way we design technology increasingly shapes how people think, move, and interact with the world around them. My capstone project, WahooWay: An Accessible Navigation System for UVA, focuses on developing an accessibility-centered navigation application to improve mobility across the University of Virginia’s Grounds. This project was motivated by the lack of routing tools that account for barriers such as stairs, steep grades, construction, and temporary hazards, which often force individuals with mobility impairments to manually piece together routes. My STS research paper, The Intertwinement of Artificial Intelligence and Education, examines how generative AI tools such as ChatGPT are reshaping students’ cognitive development and educators’ roles. I undertook this research to explore why reliance on AI for polished and specific responses may diminish opportunities for authentic critical thinking and problem-solving, and what responsibilities computer scientists have in addressing it. These two projects are connected through their shared focus on human-centered design: while my capstone builds a system that supports users’ physical navigation and independence, my STS research evaluates how technological systems can either support or undermine cognitive independence.
My capstone project contributes toward solving the problem of inaccessible and unreliable navigation across UVA Grounds by developing a dynamic, accessibility-first mobile application. Existing tools, such as static maps or general navigation platforms, often fail to reflect real-time barriers like construction, blocked entrances, or malfunctioning elevators. WahooWay addresses this issue by generating personalized routes that avoid stairs and prioritize accessible entrances based on user mobility preferences. The system integrates user-reported obstacles, allowing navigation to reflect real conditions rather than static assumptions. Built using Flutter, Firebase, and Mapbox, the application combines real-time geolocation, customizable routing, and a community-driven alert system. Users can create reports for hazards, view alerts placed by others, and adjust their routes accordingly, making the system both responsive and collaborative.
The overall conclusions of my capstone project demonstrate that an accessibility-centered, user-informed system can significantly improve both the safety and independence of navigation for individuals with mobility impairments. Testing results showed that WahooWay reliably generates accessible routes, allows users to easily report and visualize obstacles, and adapts navigation based on mobility preferences. Users consistently described the application as intuitive, functional, and visually clear, successfully completing all major features such as route generation, alert creation, and preference customization. While areas for refinement remain, such as camera control and expanded campus coverage, the project establishes a strong foundation for a scalable and impactful navigation tool. More broadly, it highlights the importance of designing technology that actively supports user needs rather than expecting users to adapt to technological limitations.
My STS research paper asks how generative AI is impacting critical thinking and cognitive development, and whether engineers are designing these systems responsibly. The significance of this research lies in the rapid integration of AI into education and the potential long-term consequences on learning, particularly for younger generations developing alongside these tools. The methodology combines qualitative research and published case studies, focusing on how students and educators interact with AI in real learning environments and how engineers’ design choices influence these interactions. By analyzing both user behavior and system design, the research draws connections between technological development and cognitive outcomes.
The evidence collected includes cognitive and neurological studies, industry research, and case studies examining AI’s impact on learning. Findings show that reliance on AI for polished and specific responses may diminish opportunities for authentic critical thinking and problem-solving, and that brain connectivity systematically decreases with increased external support. Studies grounded in Cognitive Load Theory demonstrate that while AI reduces cognitive load, it can also lead to lower-quality reasoning and weaker engagement with material. At the same time, the research acknowledges that AI can be beneficial when used with guidance, acting as a support system rather than a substitute for thinking. Ultimately, the research concludes that while AI is not going away, its integration must be carefully managed through ethical design, educator guidance, and conscious use in order to preserve independent thinking and cognitive development.
