In the busy rush of teaching, we don’t always take the time to look at multiple data points to make decisions about student learning. Yet, using multiple measures to evaluate student learning helps minimize the risk of reading too much into any single piece of information. This is where data triangulation comes in.
Data triangulation is the process of using at least three data points to inform educational decision making—is especially helpful when interpreting assessment results. Triangulation allows teachers to use different sources of information to create a more complete picture of student learning. When all the data points lead to similar conclusions about a student’s needs, we can be more confident in the assessment and the decisions we make to address those needs.
First step… selecting data sources. The good news is that there’s usually a lot of data that’s available; the bad news is that it can be overwhelming. To make the best use of the data, you need to understand what data you have, what it measures, and how it can be used. Here a four student data sources that every teacher has access to:
- Classroom-based data. This can be teacher observations, student classwork and participation, and behavioral measures.
- Formative assessment data. Quizzes, tests, and student projects can make up this data source.
- Summative assessment data. Here we can look at portfolios of student work, end-of-unit tests, as well as end-of-year tests.
- Skills diagnostics and universal screeners. Quite often these are brief curriculum-based assessments of targeted skills.
Armed with student data we get to the second step… data source management. It can be tricky to manage data from many different sources—let alone make meaning of it. To simplify the process, here are three key principles that guide good data management practices:
- Make data easy to access and use. Using one or more of the many data management programs that are available can be a great way to collect and organize various types of learning and assessment data to be readily available when needed. By consistently entering new data into our management systems, we can ensure that we have the most recent information ready at our fingertips when we need to make educational decisions about classroom assessments.
- Present data simply and clearly. It is important for teachers to make sure that the student data we collect is easy to understand and use. Raw data can be difficult to make meaning out of, but by taking the time to develop simple and accurate representations of key data—in the form of charts, graphs and tables—we can more easily understand the meaning of the data we have. Data walls – displays of student data that facilitate collaboration – are also a great way to organize data from multiple sources, compare those data to identify learning trends and define teaching strategies.
- Discuss data with colleagues. Genuine conversations about student data can help teachers benefit from the collective knowledge and experience of our colleagues. Asking other teachers about the strategies and tools they use to collect, organize and interpret data can help you to identify new ways to manage data that might work for you.
Data literacy is an important endeavor and certainly a big part of assessment literacy. For teachers, however, assessment and other student data can often be cumbersome to parse and connect back to instructional strategies. Understanding data triangulation and how to source and manage student data is good place to start.