Engaging Special Education Teachers in Data-Driven Decision-Making Through the Use of the KIHd System Effects on Teachers' Use of Evidence-Based Strategies
Date
2015
Authors
Zhang, Dorothy Xuan
Journal Title
Journal ISSN
Volume Title
Publisher
Abstract
Collecting data, making instructional decisions based on data, and implementing evidence-based classroom management and instructional strategies are all important skills for teachers to exercise. However, due to a multitude of barriers and a disconnect between research and practice, these skills may be applied inconsistently across educational settings. This study examined the effect of an intervention involving the self-monitoring and visual performance feedback embedded in a data-collection application (the KIHd system) and self-evaluation of teachers' data-driven decision-making to apply contingent behavior specific praise and group opportunities to respond to academic instructions. Three teachers in a writing class within a postsecondary program for young adults with intellectual or developmental disabilities participated in this study. A single-subject, multiple-probed across participants research design was used to examine the research questions. The results of the study suggested that there was a functional relationship between self-monitoring and visual performance feedback and the use of contingent behavior specific praise and group opportunities to respond to academic instructions. The addition of self-evaluation led to an increase in both target behaviors for one participant, suggesting a possible effect of this intervention component. The social validity interviews supported the practicality and effectiveness of this intervention through the lens of the participants. These study findings suggest that using an electronic data-collection tool for self-monitoring may be an effective and cost efficient way to promote the use of evidence-based classroom management strategies among special education teachers.
Description
Keywords
Educational psychology, Behavior Specific Praise, Data-Driven Decision Making, Evidence-based practices, Opportunity to Respond, Self-monitoring