The Effectiveness of Video Self-Modeling on Increasing and Sustaining Teacher Use of Behavior-Specific Praise in the Alternative Classroom
Year: 2015
Type: dissertation
Abstract: Increases in teacher use of behavior-specific praise statements (BSPS) have been associated with positive outcomes for students, including reductions in student problem behavior, improvements in student on-task behavior, and positive interactions between students and teachers.This is particularly relevant for students with behavior support needs who receive educational services in alternative settings, a population that has an increased need for such efforts.Additionally, there is a need to support the range of effective interventions available to improve as well as sustain teacher use of effective classroom management strategies, such as behavior-specific praise.Video self-modeling (VSM) has been found to produce rapid, positive, sustained behavioral changes for a wide variety of skills, including communication, social interaction, and vocational skills.Following the model of Hawkins and Heflin (2011), this study utilized a single-subject multiple baseline design to examine whether VSM would increase and sustain use of behavior-specific praise across four classroom teachers who provide educational services to students with emotional behavioral disabilities and positive behavioral support needs in an alternative setting.Although examination of relative mean changes suggested the possibility of increased use of behavior-specific praise across participants, effects were not consistent across other aspects of visual and statistical analysis (data overlap, trend, effect size) which suggest inconclusive findings.Additionally, sustained improvements O were not noted at follow-up.Study limitations and implications for research and practice are presented.
Author: Natalie R. Starling
Language: English
Subfield: Developmental and Educational Psychology
Field: Psychology
Domain: Social Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W812763835
