{"id":32108,"date":"2026-05-08T10:34:21","date_gmt":"2026-05-08T10:34:21","guid":{"rendered":"https:\/\/www.europesays.com\/ai\/32108\/"},"modified":"2026-05-08T10:34:21","modified_gmt":"2026-05-08T10:34:21","slug":"why-the-middle-path-of-ai-literacy-may-be-the-future-of-english-class-the-74","status":"publish","type":"post","link":"https:\/\/www.europesays.com\/ai\/32108\/","title":{"rendered":"Why the \u2018Middle Path\u2019 of AI Literacy May Be the Future of English Class \u2013 The 74"},"content":{"rendered":"

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Like it or not, generative artificial intelligence is here to stay; the majority of students<\/a> nationwide now use it for assignments at least occasionally. Policing AI use is nearly impossible<\/a>, monitored in-class assessments prioritize quick thinking over deep thinking \u2014 and disadvantage neurodiverse and multilingual learners. And no take-home assignment, however creative or personal, is fully \u201cAI proof.\u201d\u00a0<\/p>\n

Yet just freely letting students use AI to generate ideas, explain difficult concepts and produce\/revise writing removes the necessary \u201cfriction<\/a>\u201d upon which learning depends and accelerates cognitive decline<\/a>.\u00a0<\/p>\n

So I have been attempting the \u201cthird option\u201d recommended by both the Brookings Institution<\/a> and the American Psychological Association<\/a>: teaching AI literacy.<\/p>\n

This year my 10th and 11th grade English students used AI itself as a text to advance their critical thinking skills. We still read novels and short stories, still engaged in discussions and wrote essays, but AI was now a regular part of our work together.<\/p>\n

As we read, we examined how large language models\u2019 recycled novel \u201canalyses\u201d mis-read and oversimplified complex literature, producing distillations that often lacked nuance compared with the creative, discursive yet defensible readings that the students themselves generated. They learned to discern actual analysis from simplistic summaries, and to suspect the allure of AI\u2019s instant \u201ccorrect answers.\u201d<\/p>\n

As we engaged in literary discussions, we sometimes invited chatbots into the conversation; many students described these interactions as \u201cbizarre\u201d and \u201cdisjointed,\u201d adequate for reviewing plot but too circular or directionless for genuinely provocative dialogue. ChatGPT\u2019s sycophancy in particular tended to kill the necessary tension for true debate. One student \u201cstarted purposely saying dumb things just to see how GPT would still find a way to say `great idea.\u2019\u00a0It just felt so fake.\u201d<\/p>\n

As we wrote, we compared LLM-generated essays with human-generated ones, teasing out how AI\u2019s \u201csophisticated-sounding\u201d yet \u201cgeneric\u201d prose differed from the \u201cmessier\u201d but ultimately, in the students\u2019 judgment, more engaging language they themselves created. In a world where everyone has access to LLMs, these students were discovering the value of developing genuine voice. I hope at least some emerged thinking ChatGPT was best reserved for inter-office memos and letters to one\u2019s utility company.<\/p>\n

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RelatedTwo New Reports Urge \u2018Human-Centered\u2019 School AI Adoption<\/p>\n

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As we researched, we studied how AI search summaries \u2014 which users are now 58% less likely to look beyond<\/a> \u2014 don\u2019t actually represent internet searches, but instead reflect word proximity within a static corpus of text, a corpus lacking access to paywalled scholarly research and therefore drawing disproportionately on unregulated chat forums.\u00a0<\/p>\n

Students examined whether LLMs accurately reported their sources and to what extent AI drew from ideologically extreme sites. They saw how wording a query \u2014 e.g., \u201cis abortion safe\u201d vs. \u201cis abortion murder\u201d \u2014 could lead to politically-slanted results based on what the AI thought they wanted to see, and how sources often said something very different than AI summaries claimed they did.\u00a0<\/p>\n

As we took and organized notes, students compared their manual note-taking process to the output of AI note-taking tools, learning how what we choose to include or exclude in summarizing notes, how we use emphasis and phrasing \u2014 did Africa under colonialism \u201cfuel worldwide industrial production\u201d or were African resources and peoples \u201cexploited for the benefit of Western industrial profit\u201d \u2014 create and propagate different narratives.<\/p>\n

These narratives do not arise accidentally; \u201cwhat is ranked at the top\u201d of AI searches \u201cis ultimately influenced by the priorities of LLMs\u2019 shareholders,\u201d so we studied studying the politics of AI magnates like Sam Altman and Peter Thiel, learning how Google monitors and censors<\/a> Gemini\u2019s responses to political questions, and studying algorithmic bias (e.g., image generation requests for \u201cdoctor\u201d returning mainly white males), all helped my students re-think their understanding that AI tools were neutral and simply utilitarian.<\/p>\n

When we studied AI, we simultaneously studied neurological research about how humans, unlike LLMs, don\u2019t just rely on pattern recognition, but also make intuitive leaps, and used Edward De Bono\u2019s lateral thinking<\/a> activities as practice. Students did something else that AI couldn\u2019t: related classroom content to personal experiences.\u00a0<\/p>\n

One multilingual student recalled attending a business meeting with her father where he faltered, because he \u201c[knew] that someone who has the ability to speak English better [me] sat right next to him\u2026 \u2018It makes me want to depend on you\u2019 he told me, \u2018when I\u2019m totally capable of doing so by myself.\u2019 He did much better after I left.\u201d The student then made the leap to consider how, even if AI help is readily available, perhaps we gain something by refusing to rely on it.<\/p>\n

When I abandoned AI bans, I instituted AI audits. Students had to demonstrate their thoughtful, detailed evaluation of each AI tool they used, including knowledge of how it operated, what they felt they gained and lost by using it, how they verified accuracy of information, and how they had not relinquished their own thinking. The students didn\u2019t necessarily conclude \u201cAI is always bad,\u201d but they did see that using it always requires vigilance. Best of all, they didn\u2019t have to take my moralizing word for any of this; they discovered it for themselves.\u00a0<\/p>\n

Yes, I had to teach fewer novels in order to make room for AI literacy, but ultimately my job is not to teach novels; it\u2019s to teach students. Their insights \u2014 how Grammarly\u2019s \u201ccorrecting\u201d language altered integral parts of people\u2019s unique voices, how personal evolution often comes from struggle and discomfort, how our desire for ease can hold us back from achieving our potential, how dangerous it is to invest authority in words just because they emerge from a machine \u2014 were equally valuable as any takeaway they gleaned from novels. And this time I knew those takeaways were theirs, not ChatGPT\u2019s.<\/p>\n

I teach an affluent population, but teachers<\/a> are employing similar critical AI literacy lessons<\/a> with more economically and linguistically diverse learners. To be sure, my experience was often fraught. Some of my less-confident students never stopped considering LLMs\u2019 \u201cclear\u201d and \u201cwell organized\u201d writing superior to their own, and still hesitated to trust their own readings of literature over \u201cthe answers\u201d ChatGPT offered.\u00a0<\/p>\n

I struggle with asking students to critically evaluate AI while their own linguistic and analytic skills are still developing, but I also know I cannot create the conditions that allow teenagers to become master writers and thinkers before they are exposed to AI; they will soon arrive at my classroom having been using it since childhood.\u00a0<\/p>\n

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RelatedStudents Want Schools to Incorporate AI in Learning But Express Some Fears<\/p>\n

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Post-pandemic learning science<\/a> suggests that, when teaching anything, we cannot wait for students operating well-below grade level to \u201ccatch up\u201d before introducing higher order thinking skills; we have to figure out how to teach both simultaneously.\u00a0 \u00a0<\/p>\n

That requires creativity, and creativity is what makes humans superior to AI, which can only regurgitate already-created ideas. Teachers excel at creativity; every day we come up with new ways to meet the ever-changing needs of our students, and right now AI literacy is one of those needs.\u00a0<\/p>\n

Research suggests<\/a> that this training is crucial for keeping AI users \u2014 a population swiftly becoming synonymous with \u201chumans beings\u201d \u2014 from engaging in \u201ccognitive surrender, marked by passive trust and uncritical evaluation of external information,\u201d as opposed to \u201ccognitive offloading, which involves strategic delegation of cognition during deliberation\u201d when using AI.<\/p>\n

Doom-prophecies<\/a> about AI rendering English classes obsolete forget that the humanities are about studying what is human about us \u2014 including both our criticality and our adaptability.<\/p>\n

Note: This is an abridged, non-scholarly version of a peer-reviewed article slated for publication in Issue 115.6 of NCTE\u2019s English Journal<\/a>.<\/p>\n

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