Meka N. McCammon, Katie Wolfe, Ruiqin Gao, Angela Starrett
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Training Preservice Teachers to Make Data-Based Decisions: A Comparison of Two Interventions
Data-based decision-making, which involves evaluating students’ progress and making instructional decisions, is an integral competency for preservice teachers. Several studies have found that visual aids, such as decision-making models, may be an effective way to train preservice teachers to make instructional decisions. The purpose of this study was to investigate the effects of a decision-making model, with and without supplemental online instruction, on preservice teachers’ accuracy in identifying data patterns and making data-based decisions. Results showed that participants in both the decision-making model only and online training plus decision-making model groups had greater accuracy compared with participants who received no training. However, there were no significant differences between the two treatment groups, suggesting that the decision-making model may stand alone as an effective intervention to train preservice teachers to identify a data-based decision. Implications for research and practice are discussed.
期刊介绍:
Remedial and Special Education (RASE) is devoted to the discussion of issues involving the education of persons for whom typical instruction is not effective. Emphasis is on the interpretation of research literature and recommendations for the practice of remedial and special education. Appropriate topics include, but are not limited to, definition, identification, assessment, characteristics, management, and instruction of underachieving and exceptional children, youth, and adults; related services; family involvement; service delivery systems; legislation; litigation; and professional standards and training.