Students commonly engage in problem behaviors, yet teachers report handling difficult behavior as their biggest challenge. Some research over the last few decades has used functional analyses (FAs) to determine the function of student’s problem behavior and then developed functional-based interventions based on the FA findings. Despite the success of the studies, research has indicated traditional FA methodologies are not always feasible for teachers and/or schools. Therefore, a need still exists to develop better and more efficient ways to train teachers how to conduct FAs in the classroom. Thus, the purpose of the current study was to evaluate the effectiveness of using virtual video models to train future teachers how to conduct trial based functional analyses (TBFAs). Additionally, the current study sought to assess if the participants could generalize their skills learned virtually to an in person setting. Three future teachers enrolled in education courses at a southeastern university participated in the study and watched video models of each of the TBFA conditions (attention, demand, tangible, and ignore). After watching the videos, participants were then asked to conduct each trial virtually, and then complete each trial the following day in person. A multiple baseline design across participants was used, and results indicated the videos were effective at teaching the participants to conduct a TBFA. Specifically, all three future teachers successfully conducted every trial of a TBFA with high procedural integrity virtually. The virtual training then generalized well into an in person setting, with only one participant needing additional feedback. Additionally, results indicate the virtual intervention was socially valid for all participants. Limitations and directions for future research are also discussed.
Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-6548 |
Date | 09 August 2022 |
Creators | Sorrell, Jasmine R |
Publisher | Scholars Junction |
Source Sets | Mississippi State University |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Theses and Dissertations |
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