school assessment data

How Adopting Emerging Technologies Facilitates Learning, Simplifies Progress Monitoring, and Improves Student Outcomes

A version of this article originally appeared in District Administration Magazine.

As we approach the midpoint of this school year, students are learning via a variety of instructional modalities, including face-to-face, virtual and hybrid instruction.  As COVID-19 cases, hospitalizations and deaths are rising again, schools are shifting between instructional models to flex with changing health safety guidelines and local community dynamics. Educational pedagogy such as “synchronous” and “asynchronous learning” are becoming household terms. And, educators at all levels are making Herculean efforts to keep up with these challenges and to provide the best possible instruction for students.

In this oscillating climate, educators must pivot quickly to adapt—guided by data—to have the greatest impact on student learning. The ability to rapidly access, analyze and evaluate data—across multiple assessments and platforms (along with other types of data)—is critical to making decisions about instruction, programming and interventions.

The Continuing Impact COVID-19 Will Have on Students this Fall

A recent study conducted in partnership between NWEA, Brown University and University of Virginia (EdWorkingPaper 20-226) projects that “Students are likely to return in fall 2020 with approximately 63-68% of the learning gains in reading relative to a typical school year, and with 37-50% of the learning gains in math.” The study goes on further to state, “We estimate that losing ground during the COVID-19 school closures would not be universal, with the top third of students potentially making gains in reading.” 

In short, not every student will be impacted in the same way, nor to the same degree. Equity plays a large role in the learning gaps between individual students resulting from a variety of elements including prior achievement, socioeconomic factors, access to technology and internet, teacher training on virtual instruction, support within the home, and more. 

Dynamic reporting tools can help educators to look at trends, past and present, and disaggregate trends easily by filtering at various levels.

Why is Data-Driven Instruction More Important Than Ever?

While assessments can be powerful tools to identify student needs or monitor student progress/growth, assessments are only powerful when the data is analyzed and applied to drive instruction, programming and interventions. Educators must use data to take action for data to have any utility. Otherwise, it’s just more test data.

In Paul Bambrick Santayo’s book, Driven by Data, he writes that schools need to change their focus from, “what is taught” to “what is learned.”  The impact of the pandemic on student learning and the ongoing transitioning of learning environments escalates the necessity of this shift in focus.

Bambrick-Santayo goes on to identify that there are four fundamental building blocks to data driven instruction: assessment, analysis, action and culture.

  • Assessments must be standards-aligned, with varying levels of questions for depth of knowledge and understanding and provide data that not only informs instruction but helps to compare students with their peers. 
  • Analysis is the key to using the data to identify areas of student need so that action can be taken. 
  • Educators must understand how to apply the conclusions from their data analysis to take appropriate actions that have the greatest impact.
  • Finally, educational leaders must create a culture in which data-driven instruction will thrive.  This includes providing and following an assessment calendar, providing time for deep data analysis and discussion, and encouraging/supporting educators in using the data to guide actions taken.
Dynamic reporting tools in data analytics systems allow educators to quickly analyze trends over multiple assessment periods, and aggregate/disaggregate data using filters.

The greatest barrier to moving from assessment to action is the deep and meaningful analysis of assessment data. Analysis requires the “systematic examination of assessment data to thoroughly determine students’ strengths and weaknesses, then taking the necessary steps to address their needs,” states Bambrick-Santayo.

How to Optimally Get from Assessment to Action

According to Bambrick-Santayo, the first core driver of analysis includes “user-friendly reports.” Time is the new premium. There isn’t the time, nor resources, available to build complex spreadsheets to facilitate comparing data across multiple assessment platforms. The skill level at which educators can analyze data varies as greatly as the instructional levels among students, and many educators may not have the technical skills to create and manage the elaborate spreadsheets needed for meaningful data analysis. Time to teach these new skills is severely limited or not available.  Furthermore, safety protocols, preparation for virtual learning classes, and the new logistics/daily routines of instruction have removed any “extra” time that was once nominally available.

Educators need tools that help analyze data across multiple platforms—quickly, easily and seamlessly. They want tools that provide easy-to-read reports, where computerized systems “crunch the numbers for them.” These tools should rapidly disaggregate or aggregate student assessment data at the student, class, grade, building or district level—by subject, standard or objective—all within a few clicks…not hours or days.

Dynamic reporting tools can help educators easily group students by proficiency and skill/goal area for targeted instruction/intervention.

Dynamic platforms empower educators to change views rapidly in order to identify trends, gaps and areas of need. They help educators filter different types of student data, including achievement, attendance, behavior, demographic and perception data, so that schools and districts are able to analyze the needs of the whole child. In a perfect world, this should be available in one online platform (not multiple systems with different logins that require manual massaging of data between platforms). Data must be accessible anytime, anywhere, to adapt to changing school environments.

Dynamic reporting tools can help educators easily identify significant gaps among different groups of students, help drive data-based decisions on interventions, programming and resource allocation.

A “New Normal” Guided by Data

Perhaps COVID-19 will accelerate the implementation of data-driven instruction to permeate more substantially in everyday educational practice. The easier data analysis is, the more it frees educators to spend their time taking meaningful action with students. For Data Driven practices to take root, educational leaders must also purposefully set aside time to infuse deep and meaningful data analysis, planning and action into the school culture. 

It’s not that educators don’t have enough access to data. It’s that educators need to easily convert that data into intelligence…and intelligence into action. Only then, can educators focus their time, energy, expertise and passion on what they do best—educating and developing today’s learners!

Linda Kraft is Director of Customer Experience with Munetrix, a Michigan-based data analytics and management firm serving school districts and municipalities across the country. She can be reached at linda@munetrix.com. Learn more at munetrix.com.

References 

Bambrick-Santayo, Paul.  Driven by Data 2.0: A Practical Guide to Improve Instruction.  Jossey-Bass, 2019.

Dorn, Emma, Bryan Hancock, Jimmy Sarakatsannis, and Ellen Virelug. (2020)., COVID-19 and student learning in the United States: The hurt could last a lifetime.  Retrieved from Fresno State University: https://fresnostate.edu/kremen/about/centers-projects/weltycenter/documents/COVID-19-and-student-learning-in-the-United-States-FINAL.pdf

Kuhfeld, Megan, James Soland, Beth Tarasawa, Angela Johnson, Erik Ruzek, and Jing Liu. (2020). Projecting the potential impacts of COVID-19 school closures on academic achievement. (EdWorkingPaper: 20-226). Retrieved from Annenberg Institute at Brown University: https://doi.org/10.26300/cdrv-yw05

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