Principal Investigator
Matthew Steinberg – Accelerate
Project Description
This initiative supports a coordinated portfolio of rigorous research studies designed to strengthen the evidence base on high-impact tutoring. Through a national grantmaking strategy, Accelerate funds tutoring providers alongside external research partners to conduct RCTs and complementary implementation studies across a range of models, grade levels, and student populations. The portfolio prioritizes areas where evidence is currently limited, including math tutoring, middle grades (six through nine), and supports for underserved student populations such as English learners. In addition to evaluating traditional tutoring models, the initiative includes a set of innovation-focused studies examining how emerging technologies—particularly generative artificial intelligence (AI)—can improve the effectiveness, scalability, and cost-efficiency of tutoring. Across studies, researchers will collect data on student outcomes, program implementation, and costs to better understand which tutoring approaches are most effective, for whom, and under what conditions. The initiative also includes a cross-study synthesis and dissemination effort aimed at translating findings into actionable guidance for districts, states, and policymakers to support evidence-based decision-making about tutoring investments.
Research Questions
- What tutoring models and approaches are most effective at improving student academic outcomes, particularly in math and for middle-grade students?
- How do implementation features, program design, and emerging technologies (including AI) influence the effectiveness, scalability, and cost of tutoring?
- Which tutoring approaches are most cost-effective and scalable, and how can evidence be used to inform policy and district decision-making?
