Learning Is Slower Than You Think

Learning Methods and Pace

• Several comments endorse slow, consistent learning: micro-learning “one small thing a day,” spaced repetition, and active recall as powerful for retention.
• Discussion distinguishes learning vs remembering: spaced repetition is mainly about recall, but can still support understanding via second‑order effects if encoding is meaningful.
• Some argue that you haven’t “learned” what you can’t recall; others stress elaborative encoding, self‑explanation, and dual coding as prerequisites for spaced repetition to matter.
• Anecdotes: 1‑on‑1 homeschooling or tutoring can cover a year of math in months, suggesting classroom formats are the bottleneck, not children’s capacity.

Alpha School, AI Tutoring, and Education Models

• Multiple commenters think the article misrepresents Alpha: they say it’s mastery‑based and self‑paced, not “speed at all costs.”
• Others, drawing on outside commentary, argue Alpha’s gains mostly come from unusually high adult involvement, selective cohorts, and resources, not the 2‑hour software platform.
• High tuition ($75k/year) raises questions: some say you could nearly fund a private tutor; others note comparable teacher costs in SF and class‑size tradeoffs.
• One thread suggests the piece is effectively arguing for “¾ project‑based, ¼ instruction,” and that Alpha is closer to that than the article admits.

School vs Homeschool: Social and Civic Roles

• Strong disagreement over homeschooling: some claim homeschooled kids do well on tests but lack exposure to diverse peers and “real world” socialization.
• Others report the opposite: weaker test performance but better adult functioning, more varied real‑world experiences via flexible field trips and work.
• Public schools are framed not just as education, but childcare, welfare, healthcare, and a place to mix across backgrounds—though disruptive students and unfixable family dysfunction are seen as major drags on learning.

AI Writing and “AI Slop”

• A large subthread fixates on the article’s style: heavy em‑dash usage, rhythmic sentences, metaphors, and LinkedIn/TED‑talk cadence lead many to conclude it’s LLM‑assisted.
• Some push back that these are normal literary devices; others argue the piece feels like “AI slop”: lots of evocative lines, weak causal argument, more pathos than logos.
• Broader worry: AI‑authored essays blur authenticity, make arguments harder to parse, and expose how much human essay writing was already empty rhetoric.