This handout provides an overview of three common decision rules educators can use to analyze academic progress monitoring data. These options include the four-point analysis method, trend line analysis method, and median of the last three data points method.
Have you ever looked at a progress monitoring graph and groaned because you weren’t sure how to interpret it? Or wondered whether a student was making enough growth? You’re not alone—progress monitoring can sometimes feel unclear or overwhelming.
Progress monitoring is the repeated measurement of student performance using tools with strong reliability and validity to assess a student's performance, quantify a student's rate of improvement or responsiveness to instruction or intervention and to evaluate the effectiveness of instruction. This infographic summarizes key features of progress monitoring tools and the progress monitoring processes, as well as ways to analyze growth.
Progress monitoring is the repeated measurement of student performance over time. It requires reliable and valid tools and a clear process to monitor the necessary students with fidelity. Data from progress monitoring is used to assess student performance, quantify improvement or responsiveness to intervention and instruction, and evaluate the effectiveness of instruction, interventions, and supports. This infographic illustrates key features of progress monitoring at the elementary and secondary grades and considerations for progress monitoring tools and processes.
Sites implementing MTSS use different sources of data to answer a variety of questions. This infographics highlights four types of data and the specific questions teams can answer with each data type.
The pandemic has disrupted and, in many cases hindered, learning for all students – most particularly for our most vulnerable populations. Data literacy is key to understanding and tailoring instructional decisions to address students’ varying needs. In this webinar panelists discuss strategies and frameworks to ensure educators are data literate and understand how data literacy can help districts and schools address learning opportunity gaps.
Innovation configurations (ICs) are designed to evaluate current teacher preparation and professional development (PD) by determining the extent to which EBPs are taught, observed, and applied within teacher preparation and PD programs. This IC can serve as a foundation for strengthening existing preparation programs so that educators exit with the ability to use various forms of assessment to make data-based educational and instructional decisions within an MTSS.
The purpose of this guide is to provide an overview of behavioral progress monitoring and goal setting to inform data-driven decision making within tiered support models and individualized education programs (IEPs).
In this guide, we explain how educators can establish IEP goals that are measurable, ambitious, and appropriate in light of the student's circumstances. Four important steps are required for setting a valid goal for individual student performance: selecting a measure, establishing baseline performance, choosing a strategy for setting the goal, and writing a measurable goal. Although this guide presents the steps that educators can take to set appropriate IEP goals, all members of the IEP team, including families, should be involved in discussions about setting the goal.
This webinar, led by Dr. Lynn Fuchs of Vanderbilt University and Dr. Lee Kern of Lehigh University, addresses a challenge faced by many teachers: feeling inundated by data while struggling to find useful information to guide intervention decision-making. The webinar focuses on: (a) common progress monitoring measures in academics and behavior, (b) key considerations for optimizing data collection, and (c) structured questions for analyzing graphed progress monitoring data patterns.