Section 2: Purpose and Alignment

This section outlines the essential components of developing a high-impact tutoring program and focuses on aligning to district strategy, setting data-driven goals, and selecting a tutoring approach. These are foundational elements for designing a high-impact tutoring program before moving to program development and implementation stages.

The content is organized into three components:

  • 2.1 Aligning to District Strategy: This section has content regarding focus area, district strategy, and early leadership engagement to help you determine how high-impact tutoring fits with your district’s needs.
  • 2.2 Setting Data-Driven Goals: This section provides assistance with insight into the local context and the creation of clear, measurable academic goals to develop a framework that demonstrates progress and success to stakeholders.
  • 2.3 Selecting a Tutoring Approach: This section gives you tips and tools related to expert guidance and the tutoring approach selection to think through and identify the tutoring model that best aligns with your district’s needs.

Research Insights

Research provides the following guidance to create effective tutoring programs:

2.1 Aligning to District Strategy

Focus Area

  • Intensive tutoring can be effective across grade levels and subject matter—even for high school students who have fallen far behind.
  • At the elementary level, substantial research has examined the effectiveness of high-impact tutoring in supporting students' reading and math development. Reading-focused tutoring interventions for kindergarten and first graders provide more than four months of additional learning in elementary literacy on average.
  • At the middle and high school levels, there is more evidence of advancing math proficiency compared to reading outcomes.
  • Student Prioritization: Three main models for prioritizing students for tutoring are needs-driven, curriculum-driven, and universal. Decisions about which students to target should vary depending on the needs of the students, schools, and communities.

District Strategy

Early Leadership Engagement 

2.2 Setting Data-Driven Goals

  • Successful programs integrate data use and ongoing informal assessments to track progress, refine practices, and allocate resources. They are also able to provide information to tutors about student understanding and where to focus instruction to support each student’s learning.

2.3 Selecting a Tutoring Approach

AI Trends in High-Impact Tutoring

Read the Full Research

Fryer, R. G., Jr. (2016). Information and incentives in education (Handbook of the Economics of Education). Retrieved from https://scholar.harvard.edu/sites/scholar.harvard.edu/files/fryer/files/handbook_fryer_03.25.2016.pdf

Fuchs, L. S., Seethaler, P. M., Powell, S. R., Fuchs, D., Hamlett, C. L., & Fletcher, J. M. (2008). Effects of preventative tutoring on the mathematical problem solving of third-grade students with math and reading difficulties. Exceptional Children, 74(2), 155–173. https://doi.org/10.1177/001440290807400202

National Student Support Accelerator. (n.d.). Tutor CoPilot one-pager. Student Support Accelerator. Retrieved from https://studentsupportaccelerator.org/sites/default/files/Tutor_CoPilot_OnePager_0.pdf

Robinson, Carly D., Biraj Bisht, and Susanna Loeb. (2022). The inequity of opt-in educational resources and an intervention to increase equitable access. (EdWorkingPaper: 22 -654). Retrieved from Annenberg Institute at Brown University: https://doi.org/10.26300/ja2n-ys82

Robinson, C. D., Kraft, M. A., Loeb, S., & Schueler, B. (2024). Design principles for accelerating student learning with high-impact tutoring (EdResearch for Action Brief No. 30). Annenberg Institute at Brown University. https://studentsupportaccelerator.org/sites/default/files/EdResearch%20Accelerating%20Student%20Learning%20With%20High-Impact%20Tutoring.pdf

University of Chicago Education Lab. (2023). Not too late: [Subtitle if applicable]. https://educationlab.uchicago.edu/wp-content/uploads/sites/3/2023/10/UChicago-Education-Lab-Not-Too-Late-Paper_03.23.pdf

White, S., Groom-Thomas, L., & Loeb, S. (2022). Learnings from existing research on tutoring implementation: Implications for district leaders & policymakers. National Student Support Accelerator. https://studentsupportaccelerator.org/sites/default/files/Tutoring%20Implementation%20Synthesis%20Brief.pdf

White, S., Groom-Thomas, L., & Loeb, S. (2023). A systematic review of research on tutoring implementation: Considerations when undertaking complex instructional supports for students (EdWorkingPaper No. 22-652). Annenberg Institute at Brown University. https://doi.org/10.26300/wztf-wj14 

Tutoring Quality Standards

High-quality tutoring programs align with key standards that support effective implementation and student success. Learn more about the research and application of the tutoring quality standards relevant to this section: