This webinar models how practitioners can use data-based individualization (DBI) to develop and implement specially designed instruction (SDI) for students with disabilities.
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DBI Process
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Implementation Guidance and Considerations
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The purpose of this module, Behavior Basics: Understanding Principles of Behavior, is to gain foundational knowledge of what behavior is, how behavior is defined, and what environmental factors influence behavior. This foundational knowledge is core to understanding behavior, supporting students with challenging behavior, and later, diagnosing function of behavior and developing effective behavioral interventions.
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 collection of training materials can be used to provide an overview of the Taxonomy of Intervention Intensity for selecting, evaluating, and intensifying interventions or to provide specific examples in reading, mathematics, and behavior. The training materials include presentation slides with suggested speaker notes and workbooks with application activities. The modules are intended to be delivered by a trained, knowledgeable professional.
Within a multi-tiered system of supports (MTSS), intensive intervention, also known as Tier 3, is designed to support students with the most severe and persistent learning and/or behavior difficulties. This document highlights some common misconceptions about intensive academic and behavior interventions that experts from the Center on Positive Behavioral Interventions and Supports and NCII have observed in supporting the implementation of intensive intervention within the context of MTSS.
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.
This training module 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 behavior intervention programs to best meet students’ needs and intensify or adapt those interventions when students or groups of students do not adequately respond.
At-home learning requires increased independence for students. With no bells signaling the beginning or end of class and no teacher leading the class for each subject, students must follow a virtual schedule. Within these schedules, students are responsible for accessing the appropriate links to class sessions and work activities. In addition, students often must populate usernames and passwords—most of which are unique for each different site or task.
This activity was developed by Krysta Muspratt a Reading/Language Arts Specialist at Downtown Denver Expeditionary School. In this example, she illustrates the virtual implementation of EL Education’s Decoding and Spelling assessments. This collection includes a tip sheet and a video example. While this resource was developed using EL Education’s Decoding and Spelling assessments, these tips may be applicable for other assessments. Tip Sheet for Virtually Administering Decoding and Spelling Assessment using EL Education EL Education Foundations Remote Assessment Tutorial This video provides an example of how to administer the EL Education Foundations Assessment with students virtually.
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.