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Examining teacher effectiveness using data from the Florida Education Data Warehouse

Pupil Learning Project. Examining teacher effectiveness using data from the Florida Education Data Warehouse. Introduction. FAMU Professional Education Unit (PEU) Overview of Project Descriptive Exploratory Study

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Examining teacher effectiveness using data from the Florida Education Data Warehouse

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  1. Pupil Learning Project Examining teacher effectiveness using data from the Florida Education Data Warehouse

  2. Introduction • FAMU Professional Education Unit (PEU) • Overview of Project • Descriptive Exploratory Study • What is the relationship between the pupil learning growth of FAMU PEU graduates and selected pre-service variables of FAMU PEU graduates? • Assessment of Program Effectiveness • Data Sources • Florida Education Data Warehouse (EDW) • FAMU Enterprise Information Technology (EIT) • FAMU Center for Teacher Preparation • FAMU Office of Student Teaching • FAMU National Board Resource Center • Ongoing FAMU TNE data collection activities • Project database to merge data sets

  3. Data Flow Florida EDW Data COE Office of Student Teaching Program/Department Data FAMU Office of Institutional Research FAMU Center for Teacher Preparation FAMU TNE Project Data COE Office of Information Management and Assessment FAMU National Board Resource Center FAMU EIT Data

  4. Data Flow Florida EDW Data Teacher Characteristics FAMU TNE Project Database FAMU TNE Project Data Pupil Performance FAMU EIT Data

  5. Pupils/Candidates Demographics Enrollment Courses Test Scores Financial Aid Awards Employment Florida EDW Data • Educational Curriculum • Staff • Demographics • Certifications • Instructional Activities • Educational Institutions

  6. Progress • Preliminary Findings • Challenges • Identifying the appropriate courses for aggregation and disaggregation • Course titles • Mixed grade level courses • Small class sizes (n=1) • Incomplete data • Value-added Challenges • Residual effect of previous teachers • Attribution of gains among multiple teachers • Value-added/Hierarchical Linear Model analyses

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