Date of Conferral
Steven G. Little
A significant percentage of US students are not reaching expected proficiency on mathematics content. As a response, educators have been urged to use more evidence-based practices; however, due to the lack of readily available strategies, these efforts have been thwarted. In related fields, video modeling (VM) has been successful in teaching behavioral skills through edited video clips that allow target populations to observe models successfully performing featured tasks. Stemming from Bandura's social learning theory, the intent of VM is to increase the frequency of the modeled behavior through observational learning. Despite the many studies that have shown success with VM, it continues to be overlooked in education because of the lack of support surrounding its ability to teach educational content and the related technology components. The purpose of this research project was to use a single subject multiple baseline design to examine the impact of VM on the math achievement of students. The sample included 3 students, ages 16-17, and used visual analysis, percentage of nonoverlapping data points (PND), and effect sizes (ES) to analyze the results and identify significance in the outcomes. Results of the study revealed that VM had a significant impact on 1 participant after treatment and on 2 participants after maintenance. Social validity was measured through modified behavior intervention rating scales, which demonstrated that while the teacher participant did not find the treatment to be acceptable, all of the student participants did. Contribution to social change was established within this study by analyzing an effective technology-based strategy that can be used to both increase math achievement among US students and assist them to become contributing and competitive professionals in society.