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Tutoring adds two standard deviations
The tutoring effect
The finding goes back to the 1980s. Parents who know it get their kid a tutor, and with a tutor it is easy to reach 1200, 1300, or 1400 on the SAT.
Who gets a tutor
Families who cannot afford a tutor get nothing like that from the public school system. An AI tutor offers a motivated student whose family cannot afford a tutor the same one-on-one attention, which is the case for adaptive learning.
The AI question
The open question is how to give students that tutor without letting it do their thinking. Most parents do not want their kids to skip the work and have their brains atrophy, and want them to learn to read and write on their own first, then use AI to augment what they can do.
What did Bloom's study actually find?
Benjamin Bloom, an educational psychologist at the University of Chicago, reported the result in a 1984 paper called The 2 Sigma Problem. Students tutored one-on-one using mastery learning scored two standard deviations above students in conventional classes. That puts the average tutored student above about 98 percent of the classroom group. The data came from studies run by Bloom's graduate students on topics such as probability and cartography.
Why does one-on-one tutoring work so well?
A tutor sees each error as it happens and corrects it before the next step builds on it. Bloom's tutored groups used mastery learning, in which a student had to show command of one unit before moving to the next. Tutors can also change an explanation on the spot and keep a student working at the edge of what they can do. A classroom teacher managing dozens of students cannot do this for each child.
Does modern research confirm two sigma?
Later studies found smaller effects. A 2020 meta-analysis by Andre Nickow, Philip Oreopoulos, and Vincent Quan covered 96 randomized trials of tutoring in preschool through twelfth grade. It found an average improvement of about 0.37 standard deviations. Effects were largest for tutoring delivered by teachers and paraprofessionals.
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