Successful implementation of a multi-tiered system of supports (MTSS) and, specifically, intensive intervention through the data-based individualization (DBI) process, demands the collection and analysis of data. As teams consider data collection, challenges may occur with assessment administration, scoring, and data entry (Taylor, 2009). This resource reviews three data collection and entry challenges and strategies to ensure data about risk status and responsiveness accurately represent student performance and minimize measurement errors.
Error message
The page you requested does not exist. For your convenience, a search was performed using the words in the page you tried to access.
Search
Resource Type
DBI Process
Subject
Implementation Guidance and Considerations
Student Population
Audience
Search
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.
This webinar illustrates considerations for implementing data-based individualization (DBI) with English Learners that accounts for their unique academic, social, behavioral, linguistic, and cultural experiences, assets, and needs.
This training module, Using the Taxonomy of Intervention Intensity to Select, Design, and Intensify Intervention, introduces the Taxonomy of Intervention Intensity and describes how it supports the DBI process by helping provide explicit guidance on how to select and evaluate validated intervention programs to best meet students’ needs and intensify or adapt those interventions when students or groups of students do not adequately respond. At the end of the training participants will be able to:
This course collection provides a guide to available NCII courses for those who are newer to the DBI process or interested in learning more about how intensive intervention can support students with severe and persistent learning and/or social, emotional, or behavioral needs.
When a student fails to respond to a validated intervention, teams need to identify why the student is not responding to determine how to adapt the intervention. Diagnostic data can assist teams in this process. They may be used to understand a student’s specific skill deficits and strengths or to identify the environmental events that predict and maintain the student’s problem behavior.
This handout briefly defines the seven dimensions of the Taxonomy of Intervention Intensity for academics and behavior. The Taxonomy of Intervention Intensity was developed based on research to support educators in evaluating and building intervention intensity. The seven dimensions include strength, dosage, alignment, attention to transfer, comprehensiveness, behavior or academic support, and individualization.
This two page handout highlights how to use the Taxonomy of Intervention Intensity when selecting, evaluating, and intensifying interventions for students who are English learners (ELs). Specific considerations for ELs are provided across the dimensions of strength, dosage, alignment. attention to transfer, comprehensiveness, behavioral support, and individualization.
Using multiple data sources, the teacher or team makes a decision to adapt the intervention program to better meet the student’s individual needs. The teacher or team outlines these adaptations in an individual student plan. The plan may include adaptation strategies along several dimensions. These strategies may include quantitative changes, such as providing more opportunities for a student to respond by increasing the length or frequency of the intervention, or decreasing the size of the intervention group.
This brief offers recommendations to support educators to efficiently collect, analyze, and use diagnostic data to adapt or intensify intervention.