Teachers and schools generate reams of student data, from state-mandated testing, periodic benchmarks, unit exams and quizzes, and even daily exit tickets. The emphasis on data collection tends to be so overwhelming that the purpose of the data, and how to manage and learn from that data efficiently and effectively, can be overlooked. This strategy provides you with a structure to create user-friendly data sets and student action plans to put your student data to good use.
These steps presume that a structure is in place to re-teach, intervene, and/or advance students. If not, this is the first step.
Collect school-level data for key subjects and for each grade level (start with one subject in elementary). See Coach Tips about which data to select.
Set the purpose for the data analysis.
Aggregate the data and organize or sort it by criteria that you develop (i.e., Advanced, Proficient, Needs Improvement, Warning, or however your district/state labels these four categories).
Analyze the data.
Look at the data by student. Sort the data by score, and keep in mind the students who fall close to the cut-off.
Look at trends by standard, question, or topic. Which questions/standards did the class do well on, and which did they struggle with?
Determine the re-teaching, intervention, or advancement cycle that you plan to use with your students to help them to master the skills based on their data results. See Coach Tips to learn more about the re-teaching, intervention, or advancement cycle.
Prioritize based on greatest needs and/or objective for data analysis.
Create action plans. Action plans can be made for individual students or groups of students. To learn more about action plans, consult the resources below. Make sure to assign action plans for implementation.
Implement action plans and collect data to determine the impact of the re-teaching, intervention, or advancement.
Begin the cycle again by updating student data, modifying action plans, and continuing to re-teach, intervene, or advance students as necessary.
A data display is a visual way to show student data. Often this data is organized by class and then, by using color coding, grouped by performance. Data displays keep data at the heart and center of planning. Teachers and those who support them can easily see who is growing and who is not. Review the resources below for different types of data displays as well as templates, examples, and descriptions of data displays in two school districts.
Giving students the opportunity to monitor and reflect on their own data changes the classroom dynamic from teacher- to student-owned. Teachers can display whole-class data (anonymously) or provide individual data to students.
Collecting student data doesn't always mean preparing a lengthy test or quiz. In fact, by using faster, more frequent data collection strategies, you can measure student understanding and pivot your instruction in the moment - a win for students and teachers alike!
Take a look at the artifacts below to find tips and tricks for collecting data on the spot. Whatever device works best for you - a tablet, a laptop, or a trusty pen and notebook - you'll be able to start gathering and using data in no time.
Utilizing data to inform instruction is an excellent way to support students with disabilities by more specifically identifying individual needs and helping to target remediation and reteaching. Depending on the level and amount of need in a classroom setting, analyzing data for students with disabilities can be overwhelming and thus difficult to use as a tool to action plan if not used thoughtfully. To best use data from students with disabilities to inform instruction consider the following modifications:
Teachers should think carefully about the approach of quality over quantity when analyzing data on learners with disabilities. For the most targeted support. focus should be on a deep analysis of performance on the highest leverage tasks of an assessment. This may look like only analyzing deeply three out of six open response questions or analyzing the results of learners with disabilities on one type of question on an assessment.
Teacher knowledge of students’ disabilities is a key tool for effectively analyzing data. l Teachers should ensure they are clear on IEP goals and requirements and how they interface with student performance data. Some teachers may consider additional data analysis specifically around student IEP goals and progress.
Additional teachers or support staff for students with disabilities should be directly included in the data analysis process for grouping learners to build team accountability and classroom cohesion in support of all students. See “Coaching Special Education Teachers to Use Data for Student Success” in the resource section below for more information.
1. Keep the assessment/data analysis cycle short. Frequent assessment provides actionable data on who is growing and who isn't. Also, research shows that frequent small assessments help students with retention.
2. Keep the assessments short and be highly selective in choosing the means or questions. Although there is a great deal of free material, as well as textbook material, to choose from, it is quite possible that some questions are not aligned to what students are supposed to be learning or not aligned to standards. See the Tech Tools section below for some high-quality question sources.
3. Advanced students need opportunities to learn and grow, too. However, analyzing performance data can be done for specific, more narrow purposes and initiatives for improvement and advancement can be run separately but concurrently. For example, a teacher might pull data from only those students who are a few points away from proficient and/or a few points into proficient or pull data from all students who are in the warning and/or needs improvement categories.
4. The key to making data part of daily teaching is to keep it "visible" for teachers. Administrators can do this by setting up and supporting a data display system (as this can be labor intensive, and the time involved impacts how teachers feel about it), and by meeting with teachers to look at the data and discuss what they are doing, and if they need assistance. Administrators are thereby in a great position to bring back to the entire community instructional practices that are found to be highly effective, which can be modeled during faculty or professional learning meetings. An effective way to do this is to make data walls. Another way is to use different colored sticky notes inside of a manila folder.