Employment of Data Analysis and Evidence in Creating Supportive, Diverse, Equitable,

and Inclusive School Environments

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Secondary Mathematics Comprehensive Exam

Question #3
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Question #3
In today’s world of education, integrating evidence-based practices and data analysis is

essential for ensuring equity within the classroom. Utilizing the skills I have learned through my

coursework at Alabama A&M University and my experiences from my few years of teaching, I

have learned how to use data-driven decision-making to identify inequalities, implement

inclusive instructional strategies, and monitor student progress. This essay explores how various

data types have informed my practice, how equity gaps were addressed, and the ethical

responsibilities of using student data effectively and respectfully.

In education, data analysis refers to systematically examining student performance,

demographic information, and classroom observations to inform instruction and improve

learning outcomes (Lee, 2025). In my classroom, I use formative and summative assessment

data, such as test scores, to adjust my instructional pacing and identify students needing

additional support. Additionally, data analysis goes beyond looking at my students’ test scores.

It’s paying close attention to their answers during group discussions, reading the expressions on

their faces when solving problems, and even noticing who gets excited or shuts down when

given a new topic. For example, in my Algebra 1 class, some of my English Language Learners

(ELL) students did not perform well on a pre-assessment. During the unit, I could tell that those

students did not participate much during the group discussions and seemed frustrated during

instruction. I then collaborated with the ELL instructional teacher at our school to give those

students extra support. We started using more visuals and simplified language while working

with the students. As a result, their post-assessment scores and all assessments moved forward

significantly.

I also use demographic data to evaluate the diversity and inclusion within the classroom.

During my Geometry workshop class, I did an informal assessment about classroom

during classroom discussions. This made me reevaluate the dynamics in the classroom and put in

place fair turn-taking procedures and organized group responsibilities. These adjustments aligned

with research showing that intentional participation structures promote equity and engagement

(McLaughlin, 2016).

Equity gaps often develop in ways that are not obvious. In my classroom, I frequently use

grade-level assessment analysis to pinpoint where specific groups of students are struggling. For

example, when analyzing a district-wide diagnostic assessment for 9th graders, I noticed that

Hispanic students underperformed in probability compared to other ethnic groups. This gap was

due to a lack of contextual relevance in the problem scenarios. Diving deeper into it, I realized

that the curriculum often presents problems dealing with contexts many students may be

unfamiliar with. For example, ask a student the probability of pulling a heart out of a deck of

cards. To some, this question is simple. To others, it is difficult because they are unfamiliar with

a deck of cards. To address this issue, I incorporate culturally relevant examples, such as

analyzing sports statistics from athletes they watch or creating business models based on their

community. In addition, I use attendance records and behavioral data to identify resource access

gaps. For instance, chronic absenteeism among low-income students often correlated with

incomplete homework and lower quiz performance.

The strategies I use within my classroom are centered around evidence-based practices

that promote inclusive learning environments. Differentiated instruction was a crucial strategy. I

use learning stations and tiered assignments to accommodate the different levels of my students

while ensuring I am still following the standards. I also use culturally responsive teaching by

creating math questions based on students' cultural backgrounds and inviting them to express
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how they apply the math in their daily lives. Continuous data monitoring is essential for

measuring progress and adapting strategies. To gather real-time data on student knowledge, I

employ a series of formative evaluations that range from brief exit tickets to more in-depth

problem-solving projects. This makes me versatile in my classes, providing immediate

reteaching or enrichment as needed. For example, if an exit ticket reveals a widespread

misperception regarding slope, I can address it at the start of the following class rather than

waiting for a summative assessment.

The continued data collection created significant ethical concerns. Ethically, I was careful

not to label students or make inferences based solely on data. I used data as a beginning point for

research, not a definitive assessment of competence. Confidentiality was critical; thus, I always

anonymized data during joint planning sessions. Furthermore, I realized the dangers of deficit

thinking, especially when working with underprivileged student populations. Rather than

interpreting data as proof of what students lacked, I framed it as insight into how the educational

system could better serve their strengths and needs.

Data analysis and evidence-based techniques have been critical in my reflective,

equitable mathematics instructor development. By gathering and analyzing data methodically, I

uncovered equity gaps, created responsive educational strategies, and tracked student progress

with precision and empathy. The intentional use of data—guided by ethical values and culturally

relevant strategies—has enabled me to build a classroom environment where all students may

succeed. As I advance professionally, I am determined to use data not as a measure of student

merit but as a guide to creating a more inclusive and equitable mathematical learning

environment.
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References:

Lee, S. (2025, May 24). Unlocking insights in education. Number Analytics // Super Easy Data
analysis tool for Research. https://www.numberanalytics.com/blog/ultimate-guide-data-
analysis-educational-assessment

McLaughlin, T., Aspden, K., & Snyder, P. (2016). Intentional teaching as a pathway to equity in
early childhood education: Participation, quality, and equity. New Zealand Journal of
Educational Studies, 51(2), 175–195. https://doi.org/10.1007/s40841-016-0062-z