Data and Formative Assessment in Math Interventions

Best Practices and Tools

An important part of intervention is progress monitoring, and the most important aspect of that is data collection. Any decisions made for the educational or general well-being of students should be evaluated using efficacy evidence, in other words, data. Data is the way to answer the essential questions around intervention:

  • Who needs additional instruction?
  • What is their present level of performance?
  • What is the performance target?
  • Have we met the target?
  • Where do we go from here?

The use of data in instructional decision-making has been shown to lead to improved student performance (Wohlstetter, Datnow, & Park, 2008). Since there is no single source or type of data that can reveal everything that’s needed to make balanced, well-informed instructional decisions, it’s important to use more than one data source and collect multiple types of information.

Three sources of data are:

  • Curriculum Based Measures (CBM): Student performance in basic skills or content knowledge
  • Formative Assessment: Occur through the learning and teaching process
  • Summative Assessment: Occur at the end of a project, unit, course, semester, program, or school year

But to improve instruction and learning, it’s not the sheer quantity of the data that matters, but what you do with the information (Hamilton et al., 2009).

Data and formative assessment best practices. Adjusting instruction in math or any other subject using data and formative assessment takes patience, training, and support. Here are some characteristics of a successful math formative assessment program that makes use of data to keep in mind:

  • Develop meaningful, timely feedback loops. Effective math formative assessment provides ongoing data that changes what both the teacher and the learner are doing.
  • Independent learning. Ideally,blended learning is employed so that students are able to engage in some informative assessing activities independent of the teacher. This is how students learn self-assessment and gain confidence.
  • Personalized learning. Personalized learning and individualized instruction are crucial elements of student-centric teaching that foster real progress and achievement.
  • Collaborative implementation. A team effort, involving educational leaders at all levels across the school district, is required for successful implementation in an effective assessment culture. This effort includes sufficient resources (human resources, materials, and funding), ongoing teacher professional growth, and community engagement in developing the vision and plans for implementation.

Student Progress Monitoring Tool

Dr. Kearns, Assistant Professor of Special Education of Educational Psychology and Research Scientist, Center for Behavioral Education and Research at the University of Connecticut has created an easy-to-use Excel-based progress monitoring tool to help educators (easily) gather academic progress monitoring data (Kearns, 2016). The tool can store data for multiple students across multiple measures, graph student progress, and set individualized goals for a student on specific measures. Click here to open the Progress Monitoring Tool and get started!

If you need more background, the training module Using Academic Progress Monitoring for Individualized Instructional Planning is helpful in understanding the uses of progress monitoring in formative assessment.

Check Out More Resources

DreamBox has a wealth of intervention information you can look to for ideas, tools, and best practices to help your students deepen their math understanding and achievement.

References:

Hamilton, L., Halverson, R., Jackson, S., Mandinach, E., Supovitz, J., & Wayman, J. (2009). Using student achievement data to support instructional decision making (NCEE 2009-4067).

Kearns, D. M. (August, 2016). Student progress monitoring tool for data collection and graphing [computer software]. Washington, DC: U.S. Department of Education, Office of Special Education Programs, National Center on Intensive Intervention.

Wohlstetter, P., Datnow, A., & Park, V. (2008). Creating a system for data-driven decision-making: Applying the principal-agent framework. School Effectiveness and School Improvement, 19(3), 239–259.

Thera Pearce

teacher | mother | learner | friend | Raleigh, NC

Latest posts by Thera Pearce (see all)