I tried to replace myself with ChatGPT in my English class

Reactions to the Essay and Writing Quality

• Many readers found the piece warm, funny, and a reminder of why they loved liberal-arts classes.
• Others criticized the author’s style as over‑idiomatic, emotionally manipulative, and poorly cited, contrasting it with “bland” AI prose they consider ideal for clear information transfer.
• Several note that much academic writing already resembles “word salad,” so AI’s sameness mirrors entrenched incentives in academia rather than creating something entirely new.

AI vs Calculators in Education

• Long subthread on whether “AI is like calculators” works as an analogy.
• Historical memories: calculators were initially banned or tightly constrained and phased in over decades; programmable models are still often forbidden.
• Many argue calculators only automate low-level computation after students learn the concepts, whereas LLMs can do the entire intellectual task (idea generation, structure, style), closer to handing students Wolfram Alpha or a theorem prover.
• Others stress the analogy is being over-read: the original point was about current student attitudes, not a deep equivalence.

Cheating, Homework, and Assessment Design

• Proposals: make essays/homework 0% of the grade and assess only via proctored, handwritten, or in-class essays; or weight homework lightly (e.g., 10%) to keep incentives but reduce stakes of cheating.
• Pushback: 100%-exam systems magnify test anxiety, one bad day, and favor “pressure performers”; historically many institutions moved away from that for equity reasons.
• Some instructors who tried 0%-homework report most students simply stopped doing it and then failed exams. Others already de-emphasize homework and see bimodal outcomes: diligent AI users vs. students who outsource everything and crash on tests.
• There’s debate over whether education should accept that many students will self‑sabotage if not externally pushed, or deliberately force discipline (“trial by fire,” “weed‑out” courses).

Student Time, Motivation, and Overcommitment

• Strong disagreement about whether “most students are overcommitted” or just partying and skipping class.
• Some describe intense combined workloads (work + 12–15 credits + recommended study hours) that plausibly hit 50–60+ hours/week; others insist very few actually study that much and recall university as their freest time.
• Several note procrastination, ADHD, and Parkinson’s law: students fill whatever time they have and often rely on last‑minute pressure to work. AI may worsen this by offering a perceived “easy out.”

Using AI Inside the Classroom

• Many praise the described experiment: students confront AI’s clichés, debate authenticity vs. formulaic writing, and end up more critical readers—spotting LLM “tics” becomes a game.
• Others report similar experiments (e.g., AI in science communication courses, or AI-generated ESL exam materials) and mixed feelings: AI can be helpful, but also introduces subtle oddities and quality issues.
• Some suggest reframing writing classes into “prompting classes,” but others object that this sacrifices insight into what students themselves think.

Broader Concerns about Higher Ed and Credentials

• The quoted student who’d rather spend $5,000 on career‑aligned content than on incremental writing gains resonated strongly.
• Commenters tie this to credential monopolies: expensive general‑education requirements vs. cheaper, potentially better instruction without recognized certificates.
• There’s ongoing tension between viewing university as learning and formation versus as a ranking and signaling machine; AI is seen as stress‑testing a system that already leaned heavily toward the latter.