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Effective and Scalable Math Support: Evidence on the Impact of an AI- Tutor on Math Achievement in Ghana

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arxiv 2402.09809 v2 pith:YLLGPBON submitted 2024-02-15 cs.HC

classification cs.HC
keywords mathgroupstudentslearningroritreatmentcontrolghana
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This study evaluates the impact of Rori, an AI powered conversational math tutor accessible via WhatsApp, on the math performance of approximately 1,000 students in grades 3-9 across 11 schools in Ghana. Each school was assigned to a treatment group or control group; the students in the control group continued their regular math instruction, while students in the treatment group engaged with Rori, for two 30-minute sessions per week over 8 months in addition to regular math instruction. We find that the math growth scores were substantially higher for the treatment group with an effect size of 0.37, and that the results were statistically significant (p < 0.001). The fact that Rori works with basic mobile devices on low-bandwidth data networks gives the intervention strong potential to support personalized learning on other low-and-middle-income countries (LMICs), where laptop ownership and high-speed internet - prerequisite for many video-centered learning platforms - remain extremely limited. While the results should be interpreted judiciously, as they only report on year 1 of the intervention, and future research is necessary to better understand which conditions are necessary for successful implementation, they do suggest that chat-based tutoring solutions leveraging artificial intelligence could offer a costeffective approach to enhancing learning outcomes for millions of students globally.

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Cited by 2 Pith papers

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  1. Utility-Preserving De-Identification for Math Tutoring: Investigating Numeric Ambiguity in the MathEd-PII Benchmark Dataset

    cs.CL 2026-02 unverdicted novelty 7.0 of 10

    The MathEd-PII benchmark shows that math-aware and segment-aware LLM prompting raises PII detection F1 from 0.379 to 0.821 while cutting false redactions of instructional numbers.

  2. Superstudent intelligence in thermodynamics

    cs.CE 2025-06 conditional novelty 6.0 of 10

    OpenAI's o3 model scored higher than all 90 students on a real university thermodynamics exam, zero-shot, including problems with graphical output.

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