Published Content
Artificial Intelligence in a Writing Intensive Lifespan Development Course: Rates and Functions of Student Usage
Ashlie Lester and Wenting Sun
Artificial intelligence (AI) has transformed usual processes of higher education, including teaching with writing. Grounded in sociocultural theory, this study considers the role of generative AI (GenAI) within students’ zone of proximal development, where learning is supported through scaffolding that bridges what students can do independently and what they can achieve with guidance. Students (n = 114) enrolled in a writing intensive, lifespan development course in Fall 2024 completed eight writing assignments and disclosed any GenAI use; specifically, they could submit no more than a paragraph of their writing to a GenAI tool to solicit feedback that could be applied throughout the papers. Required AI disclosure statements revealed infrequent GenAI use, with only 22 unique users of GenAI for less than 8% of the assignments. Thematic analysis of the disclosure statements revealed three themes of use: writing mechanics, higher-order writing concerns, and content understanding. Despite students reporting that GenAI feedback was helpful, the impact on writing scores and final grades were mixed. Findings highlight the complex role of GenAI as a potential scaffolding learning assistant and suggest implications for instructors seeking to strategically incorporate GenAI into teaching with writing.
AI Conceptualization and Policy Permissibility
Zea Miller, Kashish Sachdeva, and Jake Walker
When universities create AI policies, they often conceptualize AI as something, such as a tool or a resource. This study questions whether such policies are affected by how they envision AI. In other words, is the permissible a function of conceptualization? To answer, R1 university policies were rated independently by three raters on two axes: conceptualization and permissibility. When visualized, the ratings clearly show that while AI qua TOOL does not inherently attach either to the restrive or permissive, AI qua RESOURCE does not attach to the restrictive. Ultimately, this study shows that universities are unlikely at this time to conceptualize AI as a resource and simultaneously ban it.
The Ethical Implications of AI in the Composition Classroom: From Plato to Parrots and Back Again
Rebecca Cepek, PhD
This article addresses the needs of first-year writing students in regard to the use of generative artificial intelligence programs in the composition classroom. The responses to generative AI in academia have settled into three somewhat predictable patterns: complete resistance, complete acceptance, and the ever-popular middle ground. While generally, I like to avoid extremes, I am unable to do so in this case: I feel for the sake of our students, in terms of first-year writing, we must take the path of complete resistance. The various generative AI systems, as they exist now, are flawed for a variety of reasons, with deeply troubling ethical implications in terms of the environment, the information they produce, and the ways in which they share that information.