(Note to readers: This is part three in a series of columns written about Iowa ASCD’s current focus on supporting curriculum leadership across the state.)
In the last column, I proposed curriculum leads consider getting their feet wet and engaging teachers in a collaborative process to understand the nexus between standards, instruction and assessment in all content areas. This week, we’ll be taking a closer look at what it means to be a leader of data analysis.
According to our organization, curriculum leads “assure all educators’ ability to use data to inform, implement, monitor, and evaluate results-based decisions.” At first glance, this function may seem like it’s all about spreadsheets, databases, crunching numbers and creating elaborate reports filled with pie charts. Sure, there’s a time and a place for disaggregating data to reveal gaps across subgroups. Without a doubt, curriculum leads should be providing assessment and other data in formats staff, parents and community members can easily understand. Our job is to use data to inform others. It is equally as important to “tell the story” about the data for the purpose of generating a solution or next steps than it is to merely crunch the numbers. Let’s be clear: our positions do not require an advanced degree in statistics or mathematics! Our ability to communicate through written language will directly impact our capacity to be leaders of data analysis. Here’s an example. Consider FAST (an early literacy assessment) scores in an elementary building indicating only 65% of students had met grade level benchmarks. If, during the previous school year, 45% of students had met benchmark, this year’s scores would be a huge celebration! On the contrary, comparing this data to the state’s healthy indicators for differentiated accountability (80% or more meeting benchmark is the universal target), the numbers may seem bleak. Clearly communicating these contextual comparisons can be helpful in sharing progress and next steps to stakeholders.
We live in an era with more than enough educational data to fill weeks of endless number crunching. As a former high school math teacher, I naturally bend towards looking at the numbers in isolation rather than figuring out if there’s a bigger picture to consider. Instead, our job is to look at the data in its context, and ask (ourselves and others) compelling questions, such as “Is there anything else we need to know about these data points?” An example of this in my life happened last year when we noted a small drop in Iowa Assessment scores in several grades. It would have been easy to suggest our instruction or curriculum materials needed a boost, however after a closer look, we realized the areas we could most notably improve upon would require us teaching to the test rather than the grade-level standards (which is not something we were willing to do). Investigating the context around these data points lead us to a completely different next step.
Using data to monitor and evaluate is important, too. At a recent AEA curriculum directors’ meeting, a few of us discussed program evaluation and the struggles that go along with effectively and efficiently evaluating various programs in our districts. Realizing program evaluation data does not always need to solely involve test scores was a helpful reminder. For example, my district uses several self-audits and continuums to identify our current level of implementation. We have a continuum to assess each team’s current progress towards our professional learning philosophy (i.e. power standard development, common assessments, data analysis, and action planning) that has informed professional learning and team goal setting during the past several years. Asking questions such as “To what degree are we implementing this practice with fidelity” may be a precursor to concluding the degree to which an initiative or classroom practice is impacting the expected outcomes.
In closing, curriculum leaders are relentlessly building capacity in the school system to use data as a driver of informing, implementing, monitoring, and evaluating results and corresponding decisions. This function does not require advanced training in spreadsheets or mathematics! Leading data analysis does involve summarizing and formatting data in a meaningful way that will allow others to draw conclusions from the information in order to address a specific problem or challenge.
Resources to further learning as a leader of data analysis:
- Partnering with Parents to ask the Right Questions by Luz Santana, Dan Rothstein, and Agnes Bain (2016, ASCD)
- Root Cause Analysis: The Core of Problem Solving and Corrective Action by Duke Okes (2009, ASQ Quality Press)
- Data Analysis for Continuous School Improvement, 4th Edition by Victoria Bernhardt (2017, Routledge)