The frequency and nature of student participation in the classroom, with a focus on assessing equity of voice.
Use this measure:
The EQUIP (Equity Quantified in Participation) tool can be accessed through the EQUIP website.
Measurement instrument overview
This online observation tool is typically used while viewing video recordings of teaching sessions. Through the tool, instructors can create a roster with demographic information for each student and then create a record for all student discourse during class.
The tool is fully customizable to allow users to choose which student characteristics or aspects of classroom discourse they want to track. Users have the option of collecting data to track the following seven dimensions of classroom discourse:
Discourse type (e.g., discourse related to academic content or classroom norms and rules)
Manner of teacher solicitation (e.g., how, what, why)
Solicitation method (e.g., student called on/not called on)
Length of talk (e.g., a few words, one or two or more sentences)
Manner of student talk (e.g., how, what, why)
Nature of teacher response (e.g., revoice/elevate, evaluate)
Explicit evaluation (e.g., teacher evaluation of an idea vs. leaving the correctness of the idea open)
Reports are generated to help teachers understand trends in their classroom.
Connection to student learning
Research has shown that participation in classroom discourse is closely linked to issues of equity in mathematics education.i The EQUIP tool builds on previous equity-focused discourse work by enabling users to collect and disaggregate data on who participates, what the nature of that participation is, and how teachers support that participation. By documenting the frequency and nature of student talk and student–teacher interactions, the EQUIP tool allows teachers to identify patterns of more and less equitable participation within and across lessons.ii
i Herbel-Eisenmann, B., Choppin, J., Wagner, D., & Pimm, D. (Eds.). (2011). Equity in discourse for mathematics education: Theories, practices, and policies. Springer.
Moschkovich, J. N. (2011). How equity concerns lead to attention to mathematical discourse. In B. Herbel-Eisenmann, J. Choppin, D. Wagner, & D. Pimm (Eds.), Equity in discourse for mathematics education: Theories, practices, and policies (pp. 89–105). Springer.
ii Shah, N., Ortiz, N., Christensen, J., Stroupe, D., & Reinholz, D. (2021). Who Participates? Educational Leadership, 78(6), 41–46.
What we know about how well this measure works for its intended use
The seven dimensions of classroom discourse tracked through EQUIP were identified based on research showing their relevance to equity issues in classrooms. These dimensions were also selected, in part, because they are relatively straightforward to observe and require minimal inference to code.iii
iii Reinholz, D. L., & Shah, N. (2018). Equity analytics: A methodological approach for quantifying participation patterns in mathematics classroom discourse. Journal for Research in Mathematics Education, 49(2), p. 161.
The EQUIP tool can be used to capture data with whatever frequency (daily, weekly, monthly, or by semester) best supports improving instructional practice.
Measurement routine details
EQUIP users make decisions about which of the seven discourse dimensions to use to focus the observation.
Teachers can record video of their instruction and use the tool to code the discourse occurring in their classroom, or support personnel (e.g., coaches) can code in real time or by watching recordings.
Most trained coders can code all interactions in approximately 1.2 times the length of the observation. However, some trained coders can code discourse in real time.
The EQUIP tool generates analytics that teachers (in conjunction with other teachers and/or support personnel) can use to improve their practice.
Data analysis details
The EQUIP platform generates charts visualizing the observation data according to the discourse dimension/s that were the focus of coding. The visualizations take many forms, including bar charts showing disaggregated data (known as an interactive report), line graphs showing aspects of observations over time (a timeline report), and heat maps showing the frequency of participation by demographics over multiple observations (a heat map report). See the screenshots below to see a sample of each of these three reports.
Heat map report
The data visualizations use a metric called the equity ratio:iv
“The equity ratio is defined as the ratio of actual participation to expected participation for a group of students along a particular dimension of classroom discourse. Actual participation is determined by classroom observation using EQUIP. Expected participation is what one would predict based on a group’s demographic representation in a classroom. The equity ratio can fall into three categories: greater than 1, equal to 1, or less than 1. A ratio greater than 1 means that the actual participation of a group exceeds what one would predict in an ‘equal’ classroom (i.e., the group’s participation is overrepresented along that dimension). A ratio equal to 1 means that actual and expected participation are the same. Finally, a ratio less than 1 means that a group’s participation is less than what one would predict in an ‘equal’ classroom or that the group’s participation is underrepresented along that dimension.
iv Reinholz & Shah, 2018
Unless coding in real time, EQUIP requires that lessons must be captured on video, which can be a technological challenge. Coding classroom observations can be time-consuming and requires some level of training or experience before being able to do it quickly. Additionally, teachers may need support in understanding their data and turning their insights into actionable next steps.
In addition to these challenges, the creators of the tool acknowledge the limitations of the tool: it does not (and cannot) prescribe what resource distributions would be equitable, and it does not capture a student’s subjective perceptions of equity in the classroom.v
Teachers may find the data that emerge from the use of EQUIP to be sensitive in nature and may feel uncomfortable sharing their data with others. Having norms of trust and transparency and an improvement orientation (rather than using data primarily to judge or evaluate) can support teachers to use the data to reflect on their practice and identify next steps for improvement.
v Reinholz & Shah, 2018
Other tools and resources to support use
The EQUIP tutorial site has extensive resources about inputting student information, recording observations, and analyzing data.
Dean Hanton, a White middle school math teacher in East Lansing, had been working in collaboration with faculty from Michigan State University for several years on improving equity of student discourse in his classroom. He had found that certain student groups, including African American males and Hispanic/Latinx females, were less likely to have chances to engage in powerful and productive discussion in his class. To support adjusting his teaching practices and measuring change, Dean and several of his colleagues began using EQUIP to measure the quantity and quality of student discourse.
In his first year of collecting data with EQUIP, classes were videotaped weekly and a graduate student from Michigan State University was able to help Dean and his team with both videotaping and coding the data. In subsequent years, Dean’s team did not have the help of a graduate student, so they scaled back and collected data biweekly. Instead of having someone videotape the classroom (and focus on who is speaking), Dean put a video camera in the back of the classroom. He found that coding discourse took about two times the amount of recorded time (but he got quicker over time). He also found that multiple students speaking at the same time and not being able to tell who was speaking were challenges in coding accurately and quickly.
In using EQUIP, Dean was focused on looking at student discourse during whole class discussion. He was particularly interested in gathering data on four elements of class discussion: the kinds of questions being asked, the student being asked the questions, the kinds of responses the student gave (e.g., why, what, how), and how long of a response the student gave. For each student in his class, Dean input names, race/ethnicity, gender, and perceived level of mathematical background (on a scale of one to four). Another teacher on his team input students’ free and reduced lunch status.
After data was coded, Dean used the data visualizations in the EQUIP platform to understand student participation patterns. For examples, a couple of his takeaways from looking at the data were that he was often asking only “what” questions of his African American students, and students in the middle of the classroom were participating more. Based on these findings, Dean purposefully planned to call on specific students from minoritized groups during the next lesson, and he shuffled the seating chart to move marginalized students to the middle of the classroom. Dean met monthly with other teachers on his team to look at longitudinal trends in their EQUIP data.
Dean found that the EQUIP tool provided critical insights to help him understand and improve his teaching practices. He found that two factors made his use of EQUIP particularly successful. First, he focused on using EQUIP to work on specific elements of his teaching practice. Trying to track everything using the tool can be overwhelming, so it was important that he came into the work with a refined focus. Second, he found that collaborating with his school team (as well as Michigan State) was invaluable in both collecting and analyzing his data.
Niral Shah, Associate Professor, University of Washington
Dean Hanton, Math Teacher (retired) MacDonald Middle School