NCII partnered with Project STAIR (Supporting Teaching of Algebra: Individual Readiness) to host a series of three webinars focused on implementing data-based individualization (DBI) with a focus on mathematics during COVID-19 restrictions.
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In this Voices from the Field post, we archive the presentations from day 3 of the NCII 10-year celebration of the implementation of intensive intervention. On this day, panelists shared stories focused on improving outcomes for students through DBI implementation.
The purpose of this document is to provide an overview of the Center’s accomplishments and to highlight a set of lessons learned from the 26 schools that implemented intensive intervention while receiving technical support from the Center.
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.
English learners (ELs), as defined by the Elementary and Secondary Education Act, are individuals enrolled in school between the ages of 3 and 21 whose native language is not English. Although ELs are categorized under a single, homogeneous label, they represent a diverse population of students with wide-ranging cultural experiences, native and second-language proficiencies, and varying degrees of subject matter knowledge (Vaughn et al., 2019). Delivering intensive intervention for ELs involves consistent attention to students’ language development, culture, and academic and behavioral needs throughout the DBI process. Supporting ELs with intensive needs depends on an educator’s
This brief reviews provides considerations for creating readiness to implement DBI to support successful implementation and scale-up in schools.
This brief offers recommendations to support educators to efficiently collect, analyze, and use diagnostic data to adapt or intensify intervention.
This is part 2 of the module, “Informal Academic Diagnostic Assessment: Using Data to Guide Intensive Instruction.” This part includes examples of graphed data and is intended to provide participants with guidance for reviewing progress monitoring data to determine if the instructional plan is working or if a change is needed.
This report from Jobs for the Future and Authored by Sharon Vaughn, Lou Danielson, Rebecca Zumeta Edmonds, and Lynn Holdheide, 1) reviews previous efforts to promote better educational outcomes for students with disabilities, 2) describes research-based instructional strategies that can support them and other struggling learners, and 3) shares the kinds of policies and local resources needed to ensure that all young people have meaningful opportunities to learn deeply and become truly prepared to succeed in college, careers, and civic life.
To support English Learners (ELs) with intensive intervention needs it is important to (a) deliver instruction that represents culturally and linguistically sustaining best practices, and (b) distinguish the needs and assets of learners to improve progress (i.e., second-language acquisition, culture, learning challenges). This brief illustrates considerations for implementing data-based individualization (DBI) with ELs that accounts for their unique academic, social, behavioral, linguistic, and cultural experiences, assets, and needs.