The rapid proliferation of large language models and adaptive algorithms has fundamentally altered the American pedagogical landscape. Schrag and Short (2025) suggest that integrating computational linguistics into secondary literacy education represents a necessary evolution rather than a mere elective upgrade, reflecting a broader national shift toward data-driven instruction. While the United States has historically led technological innovation in the classroom, the current scale of artificial intelligence (AI) integration presents unprecedented challenges to traditional instructional models (Goralski & Górniak-Kocikowska, 2022). This transition forces a re-evaluation of how knowledge is produced and verified within academic settings. The primary tension in modern American education stems from the disconnect between the utility of generative tools and the maintenance of cognitive rigor. Basch and Hillyer (2025) found that while college students extensively utilize AI for coursework,