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Analyzing Student Performance Metrics

Updated: Jun 26

How to Leverage State Performance Data for Strategic Improvement: A Guide for the Data-Based Leader

Data-based leaders analyze student performance, not only to pinpoint specific areas where students excel and struggle, but to also influence several other areas of strategic improvement. While identifying strengths and weaknesses of student performance is vital, the analysis of assessment results impacts many other potential areas, such as:

  • Streamlined Instructional Practices: Understanding the nuances of student performance data allows educators to tailor their teaching methods to better meet the needs of their students. Data-driven instruction leads to more effective teaching and, consequently, improved student outcomes.

  • Resource Allocation: Schools have limited resources, and it’s important to allocate them where they can have the greatest impact. By thoroughly analyzing data, school leaders can make informed decisions about where to invest time, money, and personnel to support student achievement.

  • Compliance and Accountability: Both state and federal education systems require schools to meet certain performance standards. By aligning improvement strategies with these standards, schools not only enhance their performance, but also ensure compliance with educational regulations and policies.

  • Fostering Equity: A meticulous approach to data analysis helps identify achievement gaps among different demographic groups. This is essential for developing targeted interventions that promote equity and ensure all students have the opportunity to succeed.

In this article, I share research-based practices for analyzing state assessment data, from decoding results and prioritizing themes to establishing actionable strategies that lead to whole-school improvement. By analyzing these metrics with the time and attention it deserves, leaders can make school and district based decisions with more confidence.

Coding for Themes Year by Year and Grade by Grade

To begin, school leaders should closely examine the percentages of students falling into various proficiency levels across both English Language Arts (ELA) and Math. These levels may reflect something like:

  • Not Meeting Expectations

  • Partially Meeting Expectations

  • Approaching Expectations

  • Meeting Expectations

  • Exceeding Expectations

Comparing these percentages to data from previous years provides holistic insight into trends and progress. For instance, if a higher percentage of students moved from "Partially Meeting Expectations" to "Meeting Expectations," over the course of one school-year, it indicates a positive trend. Comparison of yearly progress is great for determining overarching positive and negative patterns. Use data visualization tools like line graphs and bar charts to highlight changes in proficiency levels over time. 

Many leaders tend to focus solely on the yearly data. Grade-Level Analysis allows leaders to identify specific grades that may need more support. Like you do for the year-to-year progress, the grade-by-grade report should be similar, breaking down performance for each grade to be compared across years. As opposed to looking at data through a “yearly” lens, this will give you grade-based student trends that allows teachers to revise curriculum from a more individualized standpoint. 

Performance on individual test items, known as item-level an analysis, should also be conducted, as some questions might be more challenging than others or may be administered to some students and not to others. Analyze item-level data to identify specific content topics where students struggle, and share these findings with teachers for targeted instruction. For example, analysis of questions may reveal that questions focused on content at the end of each unit plan tend to underperform, compared to questions related to standards covered at the beginning of a unit. 

Additionally, it’s crucial to disaggregate the data to identify demographic trends. This involves analyzing performance among various subgroups such as:

  • Multi-Language Learners (MLLs)

  • Students with Disabilities

  • Economically Disadvantaged Students

  • Racial/Ethnic Groups

Understanding how different student groups perform relative to one another and to state averages provides an equity focus, shedding light on disparities and areas requiring targeted support. This analysis can highlight, for example, that English Learners may need more focused interventions in reading comprehension. Leaders can develop specific action plans that include measurable goals and timelines for addressing these gaps. Simultaneously, identified achievement gaps within and across grade-levels allow leaders to emphasize the importance of planned interventions to support underperforming groups within Tier 1 Instruction and interventional programming.

Use tools like pivot tables to easily compare subgroup data across different dimensions. 

With that in mind, there are two important considerations:

  1. Students often belong to multiple subgroups. For example, a student could be economically disadvantaged, an MLL, and from a marginalized community with low socioeconomic status. Brooke Baldizzone, an Assistant Principal at Highland Park School District, has analyzed these numbers extensively. She explains, "When examining subgroup data, a child who falls into more than one subgroup cannot be overlooked, as their scores may be counted multiple times. If the data is categorized by Black, Hispanic, low-income, MLL, and Special Education, that child will appear in all those categories in reporting."

  2. The total number of students in each subgroup should be considered in data analysis. For instance, a third-grade class may have 88 students, while a fourth-grade class at the same school may have 120. Percentages may appear similar, but the actual number of students reported affects the weight of the percentage. This should be considered when comparing percentages.

Analyzing Student Performance Metrics
Analyzing Student Performance Metrics

Beyond the Numbers: Understanding Growth and Mobility

While standardized assessments provide a snapshot of student performance at a specific point in time, the true power of this data lies in its ability to reveal growth and achievement mobility. By looking beyond static scores, school leaders can gain valuable insight into the effectiveness of instructional strategies and personalize learning experiences to propel each student forward.

Imagine a student who moved from "Partially Meeting Expectations" to "Meeting Expectations" in Math over the past year. This positive shift signifies growth – a crucial metric that paints a clearer picture than a single test score. Growth analysis delves into student progress year-over-year, focusing on how many students are transitioning between proficiency levels. This analysis can be powered by tools like growth percentile scores and value-added models, quantifying the progress made by individual students and groups.

Achievement mobility concentrates on the larger movement of students across proficiency levels. How many students are consistently advancing to higher levels? Conversely, how many are regressing? By tracking these mobility patterns through longitudinal data reports, school leaders can identify factors that contribute to both positive and negative movement. Cohort analysis – comparing mobility trends across different student groups – becomes particularly insightful. Imagine a school where English Learners are consistently showing lower mobility rates. This pinpoints an area where targeted interventions are needed to support their growth journey.

Leveraging Assessment Interpretation for Actionable Steps

By analyzing these metrics, schools can

  • Set Strategic Planning Goals. Goals set for the school-community should be a reflection of student performance metrics. 

  • Target Teacher Training and Support. By identifying areas where students are struggling to achieve significant growth, schools can equip teachers with the necessary tools and strategies to address those specific challenges.

  • Targeted Student Interventions: Growth and mobility data pinpoint where targeted interventions are most needed. Imagine a school identifying a particular grade level or subject where students consistently struggle to move from "Not Meeting Expectations" to "Partially Meeting Expectations." This data becomes a powerful justification for implementing targeted interventions, such as after-school programs or interventional programming, to support those students.

  • Build Student-Centered Approach: Growth and mobility analysis shifts the focus to individual student progress. By understanding how each student is performing and moving through the achievement levels, schools can personalize learning experiences to meet their specific needs. This ensures that no student gets left behind.

Decoding state assessment data, analyzing lateral and longitudinal patterns, and identifying growth and achievement level mobility are essential steps in driving targeted improvement efforts. By leveraging data to inform decision-making and aligning strategies with state objectives, school leaders can maximize the impact of the assessment and foster equitable outcomes for all students. This structured approach ensures that every student has the opportunity to succeed and that resources are used efficiently to support student learning and growth.

And let me leave you with this. While state assessment data is critical, it is also important to triangulate this data against other records such as attendance, behavioral reports, and additional formative and summative assessments. This comprehensive analysis provides a fuller picture of student progress and informs more holistic and effective interventions.

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