Student perceptions of their agency, mathematical identity, and group work experiences in their math class.
Use this measure:
Access a copy of the High-Tech High MAIC Student Agency Survey
Measurement instrument overview
The MAIC Student Agency Survey consists of 17 items, geared toward middle and high school students.
Items are grouped into three dimensions: student agency (further subgrouped into belonging/social comparison, growth mindset, and relevance), mathematical identity, and group work.
Users will need to put the items into an online form or survey platform to administer the survey, or create a paper version of the survey.
Connection to student learning
Students’ dispositions and identities (e.g., “I’m good at mathematics”) come from their prior experiences, including prior math classes, and can shape the ways in which they relate to the discipline for the rest of their lives. Many students develop counterproductive beliefs about themselves in relation to the discipline (e.g., “I’m not a math person”). Teachers may not always fully recognize their students’ individual dispositions or see the various strengths that students bring to math class, making it difficult for them to take this knowledge about their students into consideration as they plan their instruction.
Effective teachers recognize and capitalize on the strengths of all the students in their class and seek to find ways for all students to access the classroom learning opportunities.i This measure solicits information directly from students about their math beliefs and dispositions, which teachers (and other improvers) can use to inform instructional planning that is inclusive of and accessible for all students.
i Boaler, J. (2008). Promoting ‘relational equity’ and high mathematics achievement through an innovative mixed‐ability approach. British Educational Research Journal, 34, 167–194.
Cohen, E., & Lotan, R. (Eds.) (1997). Working for equity in heterogeneous classrooms: Sociological theory in practice. Teachers College Press.
What we know about how well this measure works for its intended use
To develop the MAIC Student Agency Survey, the MAIC network drew from existing survey items related to student agency, mathematical identity, and group work that had been validated by researchers. The survey includes items from the Practical Measurement, Routines, and Representations surveys and the Carnegie Foundation for the Advancement of Teaching’s Student Agency Survey that researchers have shown to be predictive of student outcomes.ii
ii Jackson, K., Henrick, E., Cobb, P., Kochmanski, N., & Nieman, H. (2016). Practical measures to improve the quality of small-group and whole-class discussion [White paper]. https://b07758c2-c00c-4a59-9965-492dff428052.filesusr.com/ugd/3d8a27_85feb0d974ab413097830b1226b9e69a.pdf
Myung, J., & Takahashi, S. (2015, June 11). Measures to Support Improving Student Learning Mindsets. Carnegie Commons Blog. https://www.carnegiefoundation.org/blog/measures-to-support-improving-student-learning-mindsets/
The MAIC survey was implemented three times per year. Survey administration was timed to take place shortly before MAIC convenings, providing participants with baseline, midyear, and end-of-year data to reflect on during convenings.
Measurement routine details
MAIC network members used Airtable, an online database platform, to administer the survey and store responses. When taking the survey, students entered their student ID number, which connected their responses to their school’s student information system and allowed responses to be linked with student demographic data. (Teachers, however, were not able to view individual student responses.)
During the convenings, teachers used the network’s data protocol to review their data reports and networkwide data together to identify patterns, trends, and longitudinal changes. Data review and discussion was coupled with a focus on particular practices and strategies around student math agency and growth mindset that were shared and modeled at MAIC convenings. Teachers were able to bring these strategies back to their classrooms and test them out through a series of Plan, Do, Study, Act (PDSA) improvement cycles.
Data analysis details
The hub of the MAIC network set up an infrastructure for collecting, displaying, and disaggregating data using Airtable and Google Data Studio. Each teacher received an individual report via Google Data Studio showing average responses for each survey item across each survey administration. Filters allowed teachers to toggle between data displays for their classrooms and data for the network as a whole and to disaggregate survey responses by students’ race, ethnicity, and gender.
At the network level, the network hub used survey data from across participating teachers’ classrooms to understand changes across the whole network. The network hub was also able to use the survey data to explore correlations between survey items (e.g., identifying that the more students perceive that the purpose of classroom discussion is to learn different strategies to solve a problem, the more likely they are to believe that “anyone can be a math person”).
Conditions that support use
- Students should be informed as to why teachers are collecting the survey data. Without understanding the purpose of the surveys — especially for a survey that is meant to be given multiple times — students may feel resistant to or disengaged from the survey, leading to less accurate data and reducing students’ sense of agency.
- The MAIC network provided important context and support for educators to analyze survey results and to connect survey data to specific change ideas and instructional strategies.
- The MAIC network developed a survey infrastructure that allowed teachers to administer the surveys using a digital platform, connected individual student responses to the student information system, and generated reports and data visualizations for teachers.
- Students’ mathematical dispositions and identities are often formed long before a particular class and can take time to shift. As a result, instructional changes may not lead to changes in student survey responses right away. In addition, many factors outside of a student’s current math class (including prior teachers or other current teachers) can shape student survey responses. For this reason, some interviewees hypothesized that the survey may be more helpful as a tool to understand changes in student math agency across a school or network over time as a result of concerted, consistent improvement effort rather than as a measure to understand if a particular change idea is working in an individual class.
- The survey is meant to pick up on student beliefs and mindsets, as opposed to student practices and behavior. For example, one interviewee pointed out that while a student may understand what a growth mindset is intellectually, the survey does not indicate whether a student is able to enact that growth mindset when faced with a challenging situation in class.
- Some students may be concerned that providing their ID number would compromise the confidentiality of their survey responses. Accordingly, teachers should explain that they are not able to view responses from individual students.
Other tools and resources to support use
- The MAIC Network’s Digging into Data Protocol provides improvers with norms, roles, and processes to engage in productive dialogue around survey data.
- Information about the specific strategies and practices highlighted in MAIC network convenings can be found on the MAIC Network Convening webpage.
The Math Agency Improvement Network (MAIC) is a network of K–12 schools in Southern California that formed to work on improving students’ mathematical agency and outcomes in middle school and high school mathematics. Network teachers use an improvement science framework to test, adapt, refine, and spread student-centered math practices in their respective contexts.
To understand how student-centered practices support mathematical agency and success, students of MAIC teachers completed the Student Agency Survey at three time points in the academic year.
Teachers appreciated the way the survey data provided insights into student perceptions and needs. Furthermore, when data were disaggregated, teachers were able to focus on subgroups of students who were having adverse experiences or whose needs were not being met as well as others. One teacher explained, “We really tried to visualize data according to very specific target groups of students and to help us unearth our own biases and things we’re bringing to teaching we didn’t realize we had.” This same teacher reviewed the survey data alongside grades and test scores to see if “there were students who were not getting what they needed in my classroom.”
One teacher stressed that the culture of learning within the MAIC network was critical, explaining, “Sometimes you see data and it hurts . . . but because MAIC felt like a learning environment, I felt very comfortable sharing my data and wonderings about it with others. When you come at it with a lens of curiosity . . . that allows the conversation to move and be authentic.”
The MAIC network and convenings provided a supportive infrastructure to explore survey data and connect the data to classroom practice. Through the convenings, teachers were introduced to practices and strategies for increasing student math agency, saw models of these practices, and had the opportunity to experience the new practices as learners. Together, network members shared how the practices were working in their contexts along with adaptations they had made. Through the network, teachers also had the opportunity to engage in anticipatory planning and observe other teachers’ classrooms as they tested change ideas. Since its inception, the MAIC network has ramped up its use of lesson-study strategies to observe, refine, and share practices among educators.
While the Student Agency Survey provided an important periodic gauge of students’ mathematical dispositions across the network, teachers in the network also collected data on student participation, academic language use, and mathematical understanding through ongoing PDSA cycles to better understand how specific instructional changes were working. As one teacher explained, “I was using the surveys to measure progress in response to change ideas, rather than to identify which particular change idea to try…[The survey] data was more about monitoring impact.”
Cate Challen, Improvement Coach and former math teacher, High-Tech High Graduate School of Education
Daisy Sharrock, Director of the CARE Network at the Center for Research on Equity and Innovation, High Tech High Graduate School of Education
Curtis Taylor, Improvement Coach and former math teacher, High Tech High Graduate School of Education