ArticleProceedings of the National Academy of Sciences of the United States of America2026
Computer-assisted learning in the real world: How Khan Academy influences student math learning.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Computer-assisted learning in the real world: How Khan Academy influences student math learning.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors.
Funding
Abstract
Computer-assisted learning (CAL) offers an affordable way to implement a mastery learning approach in the classroom. However, while experimental research suggests CAL can enhance student outcomes, such findings often rely on experimental conditions not easily replicated in ordinary classroom settings (e.g., opt-in participation, extensive training and support, and high CAL usage targets). To assess the real-world impact of CAL, we draw on a large three-year panel of administrative data covering over 200,000 students in school districts that licensed Khan Academy's Measures of Academic Progress accelerator, a program designed to support math learning. To identify causal effects, we exploit within-teacher and within-school changes in average classroom CAL practice time-a strategy that yields precise, policy-relevant estimates even at modest usage levels. We find that a classroom with 6.6 h of annual Khan Academy practice (about 11 min per week) experiences a [Formula: see text]0.031 SD gain in math test score performance compared to no practice. For classrooms with higher usage levels, we find approximately linear gains, with projected effects rising to [Formula: see text]0.085 SD at the recommended 30 min per week. Higher-achieving students benefit most, in part because they spend more time on CAL and progress through more skills than lower-performing peers. Teachers might reduce achievement gaps and boost overall gains by encouraging more productive use of the platform (focused on skill mastery)-especially among struggling students.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.