David Seki

A University of Chicago psychologist published a short paper in 1984 proving that the average tutored student outperformed 98% of students in a normal class, and almost nobody outside education research has read it. His name was Benjamin Bloom. He called it the 2 Sigma Problem. Two of his PhD students, Joanne Anania and Joseph Arthur Burke, compared three ways of teaching the same material: > A normal class with one teacher and a room full of students. > Mastery learning, where students take regular quick tests and get corrections before moving on. > One-to-one tutoring, combined with mastery learning. The tutored students beat the normal class by two standard deviations. In Bloom's words, "the average tutored student was above 98% of the students in the control class." And about 90% of tutored students reached a level that only the top 20% of the normal class reached. Here's the part that matters. These were ordinary students in ordinary schools. Same kind of kids, different conditions. Bloom's conclusion was blunt. One-to-one tutoring works, but it is too costly for most societies to provide at scale. So he set a challenge for researchers: find methods of group teaching that work as well as a personal tutor. He also ranked the cheaper levers. Feedback and correction before moving on was worth about one standard deviation by itself. Graded homework, about 0.8. Cooperative learning, about 0.8. For 40 years, that challenge mostly sat there. Now AI tutors are being pitched as the answer. But the early evidence says the design decides everything. A tutor that hands you answers is a shortcut. A tutor that makes you try, checks you, and corrects you is closer to what Bloom measured. The 2 sigma never came from the tutor knowing more. It came from someone making sure you could not skip the hard part. Who was the one person who taught you one-to-one and changed how you learn?