Teaching in the shadow of AI: An autoethnography of motivation, competence, and learning in the first-year digital communication classroom
Year: 2026
Type: article
Abstract: This article presents an autoethnographic account of teaching first-year digital communication in an AI-saturated classroom. It examines how the widespread use of generative AI tools has transformed students’ relationship to learning, leading to the progressive outsourcing of cognitive tasks such as writing, analysis, and argumentation. Drawing on classroom observations across multiple cohorts, the study identifies a pattern of declining student engagement, reduced motivation for skill development, and a widening gap between AI-assisted outputs and students’ independent abilities. It conceptualizes this process as competence atrophy, reinforced by a feedback loop of dependency and by institutional structures that prioritize efficiency and output over learning processes. The article also reflects on the changing role of the teaching assistant, the challenges of assessing authentic competence, and the broader implications for higher education. It concludes by proposing pedagogical strategies centered on process-based assessment, intellectual ownership, and the revaluation of learning as an intrinsically meaningful activity.
Author: Cristian R. Negrea
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7222903722