Slow Math: AI Helps Students Learn More by Making Them Review Mistakes

A recent study has found that students may learn more when artificial intelligence (AI) makes them slow down and review their mistakes. The study, conducted by researchers from the University of Toronto and the University of Pennsylvania's Wharton School, involved over 6,000 middle schoolers in Tennessee.

The researchers tested four approaches to practicing fractions, including conventional computer-based instruction and AI tutoring. Within each of these groups, half the students had to correctly answer practice questions covering the same skill three times in a row if they made a mistake. The students used software built by researchers, which was similar to Khan Academy's videos and exercises, once for 50 minutes during math class.

The winning combination wasn't the addition of AI tutoring alone, but AI tutoring plus repetition. The students who practiced math with this AI-enhanced "mastery learning" approach scored about 3 percentage points higher than students receiving conventional computerized instruction.

The researchers think AI helped because it walked students through their mistakes instead of simply showing them a solution. Without AI, students could see a step-by-step example after getting a problem wrong, but a student can easily skim through the steps to a solution and move on, without figuring out what went wrong.

The AI tutor, by contrast, could respond directly to a student's work and guide the student through the mistake. The students who used AI combined with mastery learning spent more time per question than students in any of the other groups - a sign that they were engaging more with the material. These students were also more likely to get the next question right after making a mistake.

However, there was a limit to the benefits for students in this study. Students in the AI-plus-mastery group performed better primarily on the easiest fraction questions - the ones most similar to what they had practiced. The advantage did not extend to more challenging problems.

The study's lead author, Philip Oreopoulos, cautions against concluding that mastery learning is the best way to use AI in learning math. The researchers tested only the four combinations in their study; there could be better ways to enhance computer-assisted learning and make practice work more effective.

## AI and Mastery Learning: A Promising Combination

The study suggests that AI and mastery learning may be a promising combination for improving student learning outcomes. By requiring students to demonstrate mastery of a skill before moving on, AI can help students develop a deeper understanding of the material.

However, the study also highlights the limitations of AI in improving student learning outcomes. The benefits of AI and mastery learning were only seen in the easiest fraction questions, and the advantage did not extend to more challenging problems.

## The Potential of AI in Education

The study's findings have implications for the use of AI in education. By making students slow down and review their mistakes, AI can help students develop a deeper understanding of the material. However, the study also highlights the need for further research into the use of AI in education, particularly in terms of its potential to improve student learning outcomes in more challenging subjects.

The study's lead author, Philip Oreopoulos, is cautious about the potential of AI in education, but notes that it "has a little bit of benefit, and talk about its potential." The study's findings suggest that AI and mastery learning may be a promising combination for improving student learning outcomes, but further research is needed to fully understand its potential.