When tutoring programs use data consistently — through ongoing formative assessments, structured reviews, and performance tracking — they are better equipped to personalize instruction, identify what’s working, and make real-time adjustments that benefit students. This section supports Element 2: Data Use of the Tutoring Quality Standards and is organized into three areas:
- 4.1 Ensuring Program Effectiveness and Improvement: This section focuses on setting performance measures, establishing data collection routines, and implementing continuous improvement processes.
- 4.2 Responding to Formative Assessment: This section addresses building an assessment strategy, creating assessment infrastructure, and leveraging blended learning software effectively.
- 4.3 Measuring Long-Term Student Progress: This section explores structured student data review processes, personalized instruction based on data insights, and strategies for monitoring equitable student progress.
Research Insights
Research provides the following guidance to create effective tutoring programs:
4.1 Ensuring Program Effectiveness and Improvement
- Programs sustain success by incorporating continuous improvement practices, including regular data collection, structured review cycles, and adaptive strategies.
4.2 Responding to Formative Assessment
- Frequent formative assessments enable successful tutoring programs to track student understanding while refining instruction and promoting student growth. Programs that utilize ongoing informal assessments see more substantial learning outcomes because they intentionally use data to tailor instruction to individual student needs.
- Tutors need dedicated time, support, and professional development opportunities to analyze assessment data and adjust instruction. Tutor coaches enhance tutors’ ability to make data-driven decisions, ensuring targeted and responsive support for students.
4.3 Measuring Long-Term Student Progress
- Organizations which implement robust data systems to track student progress and tutor performance achieve better decision-making results and continuous program improvement. Programs can improve their tutoring approaches by maintaining ongoing assessments of student performance.
Read the Full Research
Davis, J. P., & Glick, D. (2024). The role of high-impact tutoring in education: A comprehensive analysis (EdWorkingPaper No. 24-923). https://edworkingpapers.com/ai24-923
Robinson, C. D., Kraft, M. A., Loeb, S., & Schueler, B. (2024, June). 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
Makori, A., Burch, P. and Susanna Loeb. (2024). Scaling high-impact tutoring: School level perspectives on implementation challenges and strategies (EdWorkingPaper: 24-923). Annenberg Institute at Brown University: https://doi.org/10.26300/h8z5-t461
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