Every educator knows data is more than mere numbers—it’s a powerful roadmap to understanding student performance, learning trends, and areas in need of improvement. Data literacy is an essential skill for educators because it equips them to make informed decisions that directly impact student success. Join us on a road trip across Wyoming as we explore how we’re helping three districts improve their data literacy to enhance student outcomes!
Data Literacy: “the ability to collect, manage, evaluate, and apply data in a critical manner” (Ridsdale et al., 2015)
Why data literacy matters: Paving the road for student success
For school leaders, data literacy provides the ability to identify patterns, recognize strengths and weaknesses within their schools, and strategically allocate resources where they’re most needed. Principals can pinpoint effective teaching methods, track student progress, and tailor interventions to meet individual needs. Teachers can learn from student assessments, personalize learning experiences, adapt instructional strategies, and provide targeted support to students, fostering a more inclusive and effective learning environment.
In short, data is educators’ GPS, providing them with evidence-based guidance to steer students towards success—but only if they can interpret it accurately.
That’s where we come in: Marzano Research is partnering with the Wyoming Department of Education (WDE) to improve data literacy for districts and educators across Wyoming.
The road so far: How Wyoming districts used the 5D process to put data literacy into action
WDE contracted with Marzano Research to conduct a statewide data literacy review and work with educators to enhance their data literacy skills. As part of that process, last year, three members of our Marzano Research team embarked on a 400-mile road trip across Wyoming to connect with WDE partners, district leaders, and teachers with a shared interest in data literacy and system-wide improvement.
We made several stops to facilitate professional development sessions for groups of district school leaders and educators from across the state. These sessions inspired districts to extend and continue this work in their own schools, some of which we’ll highlight later in this blog series.
The purpose of the sessions was to build educators’ capacity to use results from student data analysis to make informed instructional decisions—all with the end goal of improving students’ educational outcomes.
To achieve this, we used a series of data interpretation protocols called the 5D process: DEFINE, DIG, DISTILL, DISCOVER, DECIDE. These five steps guided the educator teams to make data-informed decisions about next steps, whether action or further inquiry.
DEFINE
Define a focus for inquiry using data or evidence based on the need or problem to be solved. Formulate questions within the focus area whose answers can be informed by data and evidence.
DIG
Dig for data and evidence. Take inventory of available data and evidence that are related to your defined need or question. If you do not have data related to your need, you may need to develop a tool or process to gather the data.
DISTILL
Find the data and evidence that are most relevant to the need or question. Your initial search will likely result in more data or evidence than you can reasonably process or may yield data that need to be cleaned, prepared, or displayed in particular ways based on the need or question. Prioritize spending time with studies or data sources that are most useful in making decisions.
DISCOVER
Discover patterns and findings in the data and evidence you are using. This requires both analysis and interpretation. Analysis is defined in this context as noticing and defining patterns or findings that are in the data. Interpretation is applying experience and professional judgment to make sense of those patterns and findings.
DECIDE
Data interpretation should ultimately yield decisions about next steps—either for action or for further inquiry. When decisions have been made, systematic change processes can be used to act on those decisions.
At each of our stops, participating educator teams started their data interpretation journey with Step 1: DEFINE—narrowing down a focus for inquiry using data. Teams posed questions such as, “Did student achievement scores for ELA, Math and Science differ from 2018 and 2019 (pre-COVID pandemic) to 2022 (post-COVID pandemic)?” or “How do the student achievement data trends in ELA, Math, and Science differ between this school year (2023-2024) and the previous school year?”
Next, in Step 2: DIG, teams began to take inventory of what data sources would help them answer their question, such as Wyoming’s Test of Proficiency and Progress (WY-TOPP) achievement trends and district-wide assessment trends.
For Step 3: DISTILL, teams worked to ensure that the data was prepared and displayed in a way to best help address their question.
Then, armed with a focused inquiry and distilled data set, teams began Step 4: DISCOVER, where they analyzed their data for trends and patterns. Through this analysis, teams identified strengths and challenges reflected in the student achievement data and named a priority challenge as a high-leverage opportunity to greatly impact student outcomes. Specific priority challenges included decreased reading achievement trends in foundational reading skills and vocabulary development, or little math progress in number and operations and algebraic thinking. From there, they tackled interpreting the data using a “5 Whys” protocol—asking “why” five times to dig deeper into each answer. This helped teams pinpoint the root cause of their priority challenge.
Teams then began to make decisions for improvement in Step 5: DECIDE. They developed SMARTER (Specific, Measurable, Achievable, Relevant, Timed, Evaluated, and Reviewed) improvement goals and identified evidence-based strategies to help them answer their focus questions.
Educators not only gained a set of district-specific key focus areas for school-wide teaching and learning improvements, but the skills and tools to easily conduct further data analysis in the future as well.
Participant feedback on the workshops was overwhelmingly positive.
“[What I found most useful was] creating meaningful representations of data to drive actions within the classroom.” —participant
“The process itself helped my team realize the need for changes.” —participant
“Looking at data is difficult, and this training made it accessible to everyone.” —participant
The road ahead: What’s next for Wyoming?
This year, we’re getting ready to hit the road again. We will continue to partner with Wyoming educators to deepen the application of the 5D process to inform continued improvement for all students across the state.
In the meantime, tune in for new posts in this series every week in January!
Interested in how Marzano Research can help your district or school enhance data literacy? Browse our data literacy related services.
This blog is Part 1 of a series about Marzano Research’s partnership with the Wyoming Department of Education to improve literacy and use of data for districts and educators statewide.
References
Ridsdale, C., J. Rothwell, M. Smit, H. Ali-Hassan, M. Bliemel, D. Irvine, D. Kelley, S. Matwin, & B. Wuetherick. (2015). Strategies and Best Practices for Data Literacy Education: Knowledge Synthesis Report. https://dalspace.library.dal.ca/xmlui/handle/10222/64578
