With the closure of schools due to the COVID-19 pandemic, educators and administrators need to rethink how they collect and analyze progress monitoring data in a virtual setting. This collection of frequently asked questions is intended to provide a starting place for consideration.
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These resources were created by Patricia Maxwell from Coventry Public Schools in Rhode Island to help with virtual mathematics instruction and intervention. The long-term goal is for students to fluently and automatically know addition facts. Manipulatives, including fingers, help students to be accurate, which is a precursor of fluency and automaticity. To meet this goal, students use manipulatives and learn strategies on how to put together numbers, which improves their “number sense.” The handouts below cover the use of ten frames, number lines, and rekenreks. Example videos are linked in the resource.
This webinar highlights strategies schools should consider in relationship to their implementation of social-behavioral supports across the continuum of tiers in a multi-tiered system of support framework as they return to school during COVID-19 restrictions.
This tool is designed to help educators collect and graph academic progress monitoring data across multiple measures as a part of the data-based individualization (DBI) process. This tool allows educators to store data for multiple students (across multiple measures), graph student progress, and set individualized goals for a student on specific measures.
This presentation provides an overview of the Direct Behavior Rating (DBR). DBR is a method for collecting data on student behavior that merges a rating scale approach and direct observation. The presentation describes: (a) considerations before using the DBR, (b) completing the DBR and (c) using the DBR to monitor progress and evaluate behavior.
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.
Goals are essential for making decisions regarding whether a student is demonstrating adequate progress in the intervention program or determining whether an instructional change is needed. These goals support teams in designing and implementing the progress monitoring plan aligned to the student’s intervention plan.
NCII, through a collaboration with the University of Connecticut, developed a set of course modules focused on developing educators’ skills in using explicit instruction. These course modules are designed to support faculty and professional development providers with instructing pre-service and in-service educators who are developing and/or refining their implementation of explicit instruction.
The 2017 Supreme Court decision Endrew F. v. Douglas County School District highlighted the importance of monitoring students’ progress toward appropriately challenging individualized educational program (IEP) annual goals and making changes to students’ educational programs when needed. In this guide, we explain how educators can establish IEP goals that are measurable, ambitious, and appropriate in light of the student's circumstances.
Data teams serve multiple roles in the data-based individualization (DBI) process and across a multi-tiered system of supports (MTSS). Although schools may have multiple teams that review different types of data across a multi-tiered system of supports (MTSS), the intensive intervention or DBI team is focused on the needs of individual students who are not making progress in their current intervention or special education program. It is critical that these meetings are driven by data, occur regularly, and use an efficient, consistent process that allows participants to review progress and make intervention decisions for students. NCII has created a series of tools to help teams establish efficient and effective individual student data meetings.