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An Empirical Framework for Analyzing Teacher Candidate Performance Assessment Data

Sun, April 30, 2:15 to 3:45pm, Henry B. Gonzalez Convention Center, Floor: Ballroom Level, Hemisfair Ballroom 1

Abstract

Teacher candidate performance assessments allow teacher preparation programs to determine candidate readiness and inform evidence-based reforms. As programs become replete with performance assessment data the critical question becomes: how can programs leverage performance assessment scores into actionable data for improvement? This paper presents a two-pronged empirical framework—using latent class analysis and predictive validity analyses—programs may use to inform improvement efforts.

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