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Using Group Video Self-Modeling in the Classroom to Improve Transition Speeds with Elementary Students
Abstract
Video self-modeling has been proven to be an effective intervention for individuals with a variety of disabilities and behavioral issues. Very few studies have addressed the impact of video modeling on behaviors that are displayed by groups of students and no studies have tackled the issue of group behaviors with video self-modeling as an intervention. This study focused on analyzing the effects of video self-modeling on students in an elementary classroom in order to increase the speed at which the students lined up and transitioned. Further, the study addressed the question of whether the intervention had a differential impact on students who exhibited varying speeds of transitioning, by grouping them into fast, medium or slow groups determined during baseline. The study employed a single-subject research design but employed groups, rather than individuals as the subjects. The results revealed that the entire class showed immediate and significant gains in the speed at which they lined up and transitioned. The results also showed that both the medium and slow groups gained enough speed by using this intervention that the groups transitioned and lined up with similar speeds as the fast group. Implications of this study showed that group video self-modeling may be an intervention that can be used to positively influence global behavior change in the regular education classroom. This intervention may be a valuable asset for educators to improve classroom management by efficiently improving student behavior, and may assist them to increase the fidelity of student responses when teaching positive classroom behaviors to students.
Subject Area
Behavioral psychology|Educational psychology|Special education
Recommended Citation
McNiff, Matthew T, "Using Group Video Self-Modeling in the Classroom to Improve Transition Speeds with Elementary Students" (2015). ETD collection for University of Nebraska-Lincoln. AAI3737766.
https://digitalcommons.unl.edu/dissertations/AAI3737766