Date Available

4-22-2019

Year of Publication

2019

Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation

College

Education

Department/School/Program

Early Childhood, Special Education, and Rehabilitation Counseling

First Advisor

Dr. Jennifer Grisham-Brown

Abstract

Progress monitoring and data analysis are essential skills needed by classroom teachers within the implementation of multi-tiered systems of support for making data-based decisions about student progress and instruction. Within the early childhood MTSS research, consideration of teacher-collected progress monitoring data followed by data-based decision-making is rare. To provide teachers with a robust progress monitoring strategy, I trained preschool teachers of inclusive classrooms to use direct behavioral observations to collect data and inform their instruction.

The project experimentally evaluated teachers’ generalization of acquired behaviors within the context of a single-case research design. The project’s independent variable, teacher training, consisted of a video-based multimedia presentation and in-vivo feedback. The primary dependent variable was teachers’ implementation of teacher-directed behavior observation procedures. Results indicate that teacher training was effective for three teachers, as evidenced by teachers reaching criterion levels of performance across consecutive days and sessions. Data on the durations of teacher training activities indicate that an average of 21 minutes of in-vivo feedback was provided to the teachers throughout training. Social and ecological validity data suggest that teachers perceived the training activities to be relatively non-intrusiveness and that the target progress monitoring strategies were of value to the teachers. A functional relation was established between training and teachers’ implementation of direct behavioral observation procedures.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2019.068

Funding Information

Funding was provided through the University of Kentucky’s Blackhurst Student Research Fund and the Arvle and Ellen Thacker Research Fund.

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