# Efficacy of a Computer Tutor that Models Expert Human Tutors

arXiv: https://arxiv.org/abs/2504.16132 · HTML: https://mlsanity.com/paper/2504.16132/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 0 of its 34 references that are in the map.
- First posted on arXiv 21 Apr 2025.

## Abstract (arXiv)

Tutoring is highly effective for promoting learning. However, the contribution of expertise to tutoring effectiveness is unclear and continues to be debated. We conducted a 9-week learning efficacy study of an intelligent tutoring system (ITS) for biology modeled on expert human tutors with two control conditions: human tutors who were experts in the domain but not in tutoring and a no-tutoring condition. All conditions were supplemental to classroom instruction, and students took learning tests immediately before and after tutoring sessions as well as delayed tests 1-2 weeks later. Analysis using logistic mixed-effects modeling indicates significant positive effects on the immediate post-test for the ITS (d =.71) and human tutors (d =.66) which are in the 99th percentile of meta-analytic effects, as well as significant positive effects on the delayed post-test for the ITS (d =.36) and human tutors (d =.39). We discuss implications for the role of expertise in tutoring and the design of future studies.
