Material Expectations: AI Usage and Undergrad Writing Composition in U.S. Higher Education

Abstract

In higher education in the United States, AI usage in writing and composition programs is often seen as a mark of laziness or a lack of creative desire, frequently eliciting a “kids these days” conversation between higher education instructors. But what if students turn to generative artificial intelligence solutions to write papers for them says less about students’ work ethic and more about how education, labor, and creative expectations have been positioned and messaged to them by dominant power structures over their lives? This paper argues that students often see generative AI as a logical and necessary tool to fulfill the strict, standardized, efficiency requirements they’ve been told to meet in a rigid U.S. neoliberal education system. Through auto-ethnographic empirical evidence of two years or writing composition instruction at an R1 institution, discourse analysis of sanctioned AI higher education tools, and a critical feminist STS perspective, I examine the current landscape of higher education and AI in creative writing and composition and present alternative pedagogical positioning of AI and writing expectations that allow for students to embrace the vulnerability of creative expression and the reiterative process of trial and error needed to learn.

Presenters

Kaitlyn Rich
PhD Student, School of Communication and Information, Rutgers University, United States

Details

Presentation Type

Paper Presentation in a Themed Session

Theme

2025 Special Focus: Human Learning and Machine Learning—Challenges and Opportunities for Artificial Intelligence in Education.

KEYWORDS

AI, US Higher Education, Critical Methods, Feminist STS, Creative Writing