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Doing Program Evaluation with Low Quality Special Education Data: Making a Silk Purse Out of a Sow’s Ear. Stephen K. Miller Western Kentucky University Yvonne Anton Kelley Niemann Georgetown College Thomas J. Simmons University of Louisville. PURPOSE.
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Doing Program Evaluation with Low Quality Special Education Data: Making a Silk Purse Out of a Sow’s Ear Stephen K. Miller Western Kentucky University Yvonne Anton Kelley Niemann Georgetown College Thomas J. Simmons University of Louisville
PURPOSE • This research is a partial evaluation of the STEP Grant and focused only on the students who were participants in the grant and their outcomes after graduation. • Paper addresses how to do program evaluation with low-quality special education data.
Demographics Personal Identity Ethnicity: 38 White, 12 Black Gender: 26 Male, 24 Female Disability: MMD – 5 BD – 5 LD – 40
RECOMMENDATIONS • Incorporate evaluation standards into projects or grants from the beginning. • Stress data-based decision making. • Stress connection between program evaluation and data-driven decisions. • Secure commitment to data collection from staff involved
RECOMMENDATIONS • Assign someone to monitor and enforce data collection. • Collect data district-wide so that it can be used in the future. • Collect data from both special education AND regular students so that comparisons can be made. • Plan data collection so that it can be disaggregated. • Analyze missing or removed data for implications.