Tono: A Cross-Cultural Conversation Platform; University of Virginia Policy: Large Language Models

Author:
Derzon, Matthew, School of Engineering and Applied Science, University of Virginia
Advisors:
Earle, Joshua, EN-Engineering and Society, University of Virginia
Morrison, Briana, EN-Comp Science Dept, University of Virginia
Abstract:

My technical report explores Tono, a student-led organization at the University of Virginia that connects North and South American students for conversations, but as it grew the previous methods for connecting students became inefficient. My partner and I run this organization together and we decided that a platform needed to be built to manage the increased load and automate certain tasks moving forward. I implemented this platform using Django as the web framework, PostgreSQL as the database, and Heroku to host the platform with the help of my partner. We managed the continued development of the platform through GitHub to allow multiple people to work on the platform at the same time. While helpful overall in terms of managing the meetings between students, a few of the features were beyond our realm of expertise. The platform was initially intended to be the place the meetings occurred, but as of now, they are still happening through Zoom and the links are just posted on the platform. In the future the platform will have the capability of hosting these meetings, and some form of matching algorithm will be implemented to match students to people with whom they will have good conversations.

In my STS paper I discuss the impacts of large language models (LLMs) on higher education through a Social Construction of Technology (SCOT) lens. Specifically, I analyze how different stakeholders such as students, teachers, and administrators interact and shape policies regarding LLMs at the University of Virginia. I identify the benefits of these systems in the classroom such as personalized learning experiences, immediate feedback, and streamlined administrative tasks while also discussing drawbacks such as academic integrity concerns, economic disparities, and environmental impacts. I also examine current policies at the University of Virgina regarding generative AI usage, offering critiques and suggested policy changes with the end goal of the different stakeholder groups achieving a consensus on generative AI in the classroom. My proposed strategies include requiring hand-written essays for first-years, standardizing AI policies across departments, developing AI training and literacy programs, and strengthening academic integrity frameworks. I emphasize the need for proactive and balanced policy development to leverage AI's educational potential responsibly, ultimately advocating for UVA to lead by example in fostering ethical and effective AI integration within academia.

My technical and STS projects, while distinct, share a common thread in their exploration of leveraging technology to enhance educational experiences and cross-cultural understanding. The technical project, Tono, is a practical application designed to bridge cultural divides by facilitating meaningful conversations between students from North and South America. By implementing a user-friendly platform, Tono streamlines logistical aspects and fosters interpersonal connections, highlighting technology's potential to significantly enhance cross-cultural engagement and global citizenship among students.

Conversely, my STS research provides a broader, theoretical analysis of how LLMs like ChatGPT are reshaping educational practices and policies at the University of Virginia. Using the SCOT framework, I examine stakeholder interactions and propose policies that responsibly integrate AI into academia. While
Tono directly employs technology to address logistical and interpersonal educational challenges, the STS research critically assesses the sociotechnical dynamics influencing educational practices and policies. Both projects underscore technology’s transformative power in education, whether facilitating interpersonal, cross-cultural communication or navigating the complexities of integrating advanced AI tools into educational settings. Together, these projects highlight the importance of thoughtful, stakeholder-informed technological integration in achieving meaningful and ethical educational outcomes.

Degree:
BS (Bachelor of Science)
Keywords:
Language-Learning, Large Language Models, Education, Artificial Intelligence
Notes:

School of Engineering and Applied Science

Bachelor of Science in Computer Science

Technical Advisor: Briana Morrison

STS Advisor: Joshua Earle

Language:
English
Rights:
All rights reserved (no additional license for public reuse)
Issued Date:
2025/05/07