Design Principles for Accelerating Student Learning with High-Impact Tutoring (updated June 2024)
Category: Student Learning
Instrument Overview
The Belonging-Centered Instruction: Observation Protocol is an observational tool used to understand how teachers support students’ sense of belonging during math instruction. It was created to address gaps in existing belonging measures, which often rely on student surveys, focus on school-level belonging, or overlook the role of daily instruction. This protocol shifts the focus to what teachers do in the classroom—both in how they interact with students and how they design learning experiences.
The tool organizes teacher actions into two main areas: interpersonal practices and instructional practices. These areas include several subdimensions that help observers look at belonging from multiple angles. By watching how teachers communicate, structure activities, respond to students, and create space for all learners—especially those who have been marginalized in math—observers can identify patterns that either support or limit belonging. The protocol is designed for researchers, coaches, and school staff who want a clearer picture of how belonging shows up in math classrooms and how instructional choices can promote more equitable and humanizing learning experiences.
Organization
Collection Category(ies)
Content
Grades
6th Grade,
7th Grade,
8th Grade
Languages
English
Respondent
Observer
Administration Information
Length
14 subdimensions, 45-minute observation cycle
Qualifications
Training required
Access and Use
Developer
Jamaal Matthews Associate Professor, Marsal Family School of Education
Price
None indicated
Contact
Jamaal Matthews: jamaalm@umich.edu
Open Access
No
Psychometrics (additional guidance)
Psychometric References
Matthews, J. S., Gray, D. L., Lachaud, Q., McElveen, T., Chen, X. -Y., Victor,
T., Okai, E., & Boomhower, K. (2021). Belonging-centered instruction:
An approach to establishing inclusive mathematics classrooms. Student
Experience Research Network (SERN), Open Science Framework. https://doi.org/10.31219/osf.io/n7bv2
