Data Literacy as a Tool for Program Improvement
I was listening to a podcast recently on which a host and a guest had widely different perspectives on a current topic. As they debated, I realized that part of the communication problem they faced, and we face in our nation, stems from a lack of understanding of how the science of information gathering works. Too often, we argue about which scientist has the most expertise, whose solution has the best anecdotal evidence, and who knows the most about a subject area based on personal experience. Unfortunately, these arguments have as much value as a single car crash has to understanding vehicle safety.
In the September 2022 issue of AMSTATNEWS (the membership magazine for the American Statistical Association), authors M.S. Goodman and J.J. Dias provided an article called “Data Literacy as a Tool for Community Health and Social Justice.” In the article, they concluded that data is one of the world’s most valuable resources and an important tool for understanding the complexity of many issues today. Two examples to support their claim focused on our understanding of health during the COVID crises and the challenging discussions this country is having around social justice. Indeed, data is critical for forming our opinions and making decisions; therefore, it is important we use accurate data.
Trying to understand how to improve student academic interest and performance in science, technology, engineering, and mathematics (STEM) and specifically career and technical education (CTE) courses, programs, and careers is not easy because of the exhaustive number of variables involved. Students and their experiences, culture, caregivers, adolescent development, prior education (or access), language development, socioeconomic factors, employment options, class, gender, race, community life (and more) all add data to the education equation we are trying to solve. It may seem simpler to choose heuristic “models” in an attempt to solve what we cannot easily or fully understand. However, data literacy tells us that we need to implement a slow, careful process to consider how best to benefit our students. In other words, we need a rigorous process that involves a variety of voices and quality data.
Taking the time to gather critical information from multiple sources needs to be the first step in gathering quality data. Here is why;
Data collection requires a process that is carefully thought out and followed in an iterative way both to increase strategies that achieve your goals and to eliminate strategies that fail to support your goals and instead overtax your teachers’ time.
Training and equipping educators within your school community to be data literate means they have the language and skills to understand, interpret, design, collect, and share data. This may mean engaging an external stakeholder to provide training or consulting to help. Universities or statistical networks may be able to suggest retired volunteers with time (and interest) to help.
Allowing a diverse group of students and teachers to be part of goal development and data collection and analysis will ensure that data can be analyzed and interpreted in ways beyond what one or two people may see.
Making data gathering and analysis part of the learning process for school improvement and for student learning will support understanding of school-based decisions and the iterative process that supports change.
Without inclusive data gathering and interpretation, understanding is limited and less likely to lead to sustained improvement.
Data literacy is required because change is a constant. As schools better gather and correctly use this most valuable resource and important tool, we can better serve our changing student populations, their families, and our communities.