In this video, Dr. Lynn Fuchs, Nicholas Hobbs Professor of Special Education and Human Development at Vanderbilt University and Senior Advisor to the National Center on Intensive Intervention, shares considerations for adapting interventions when the validated intervention program wasn’t successful.
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In this video, Dr. Lynn Fuchs, Nicholas Hobbs Professor of Special Education and Human Development at Vanderbilt University and Senior Advisor to the National Center on Intensive Intervention, shares advice about selecting and using progress monitoring measures to support intensive intervention.
This fourteen minute video shares Wyoming’s journey in building the capacity of educators to implement data-based individualization (DBI) to improve academic and behavior outcomes for students with disabilities as part of their state systemic improvement plan (SSIP). Wyoming administrators, teachers, parents and students from Laramie County School District # 1 and preschool sites share how DBI implementation impacted teacher efficacy, team meetings, quality of services, student confidence, and state and local collaboration.
In this video, Amy McKenna, a special educator in Bristol Warren Regional School District shares her experience with data-based individualization (DBI). Amy discusses how she learned about DBI, the impact her use of the DBI process had on students she worked with, and how DBI helped changed her practice as a special educator.
This video shows how to use the set model to represent the fraction 3/4 with two-colored counting chips and clips. Individual chips within the set, represent the fractional parts. It is important that students be exposed to the set model because fractions in real-world settings are often represented this way.
This video demonstrates how to use fraction circles to help students compare the value of several fractions with different numerators and denominators. The use of direct modeling with concrete manipulatives, such as fractions circles, allows students to develop conceptual understanding of fractions before they attempt to compare fractions without concrete manipulatives or pictorial representations. After students have had multiple opportunities to practice comparing fractions with concrete manipulatives, they may be ready to use other strategies such as mental images and reasoning strategies.
This video demonstrates how to use the lattice division strategy. The lattice division strategy eliminates the requirement to use automatic recall of facts, such as in the partial quotient strategy, but this strategy requires that students follow a very specific set of steps. Careful use of the lattice is required. The lattice strategy partitions numbers into smaller parts and it may not be an efficient strategy for students to use if they do not understand how division works. To use this strategy, students should have a solid understanding of place value and dividing large quantities in equal groups.
This video shows how to use the traditional division algorithm. Unlike other traditional algorithms used with addition, subtraction, and multiplication, the traditional algorithm used for division requires that students move left to right. The traditional division algorithm is very efficient to use and can be used with numbers of varying digit length. Although efficient, correct use of the traditional algorithm requires that students have strong basic fact recall (i.e., with multiplication facts and subtraction) and that students have a firm understanding of place value. Related Resources View other videos in this series.
This module is a continuation of behavioral theory from Module 1. By the end of this module, you should be able to: Define and identify elements of the four-term contingency Define and describe procedures involved with teaching: shaping, chaining, prompting, stimulus control and phases of learning
This module discusses how to define, measure and monitor behavior. By the end of the module you should be able to: Select an appropriate target behavior Write an operational definition for a target behavior Identify relevant dimensions of behavior Choose a measurement system based on relevant dimensions of behavior Use graphing conventions to create meaningful visual displays of data
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