Data-Based personnel decisions: Baker Middle’s Intensive Support List

UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
Kimberly Kappler Hewitt, Assistant Professor (Creator)
The University of North Carolina at Greensboro (UNCG )
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Abstract: Focused on the use of teacher evaluation data, this case was designed for use in two principal licensure courses, one on data literacy and the other on supervision and personnel. The principal of Baker Middle School has been instructed by the superintendent to use data from the state’s new teacher evaluation system to determine which teachers should be placed on the district’s Intensive Support List (ISL). Those on the list receive additional support but are subject to termination proceedings if they do not evidence sufficient growth. Students must analyze available data, identify which teachers should be on the ISL, and defend their decisions or alternatively craft an advocacy plan in objection to the ISL.

Additional Information

Journal of Cases in Educational Leadership, 18(1), 39-52
Language: English
Date: 2015
Multiple-measures teacher evaluation system, data-driven decision-making, value-added

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