Exploring Systematic Relationships of Evaluation Data for a Reduced Model of Evaluation
Abstract
The purpose of this study was to investigate systematic relationships among various types of evaluation data with the goal of identifying a reduced model of evaluation. Meaningful evaluation requires considerable resources and expertise that often are not planned for or are not available. Evaluation models that provide meaningful results and utilize fewer resources will help researchers and practitioners better understand how to conduct meaningful and efficient evaluation. Based on the research and practice of others in evaluation, this study examined the relationships among various types of evaluation data used to assess and report the effectiveness of a series of training/development workshops. Participants in this study were technical teachers and faculty from across the United States who participated in professional development workshops with the goal of increasing disciplinary knowledge that could be implemented into curricula at their home institutions. Specifically, this study found that trainees' plans to implement what they learn in training and perceptions of knowledge/skills gained for use on the job correlate significantly with transfer. In a predictive model, these factors account for roughly 30% of the variance in reported transfer. These results are discussed in terms of implications for future research and practice.
Degree
Ph.D.
Advisors
Ertmer, Purdue University.
Subject Area
Higher education|Business education|Teacher education|Philosophy|Social research|Communication|Education
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