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Eric.ed.gov – Assessing the Determinants and Implications of Teacher Layoffs. Working Paper 55

eric.ed.gov har udgivet:

Over 2000 teachers in the state of Washington received reduction-in-force (RIF) notices in the past two years. The authors link data on these RIF notices to a unique dataset that includes student, teacher, school, and district variables to determine the factors that predict the likelihood of a teacher receiving a RIF notice. They find a teacher’s seniority is the greatest predictor, but (all else equal) teachers with a master’s degree and teachers credentialed in the “high-needs areas” of math, science, and special education were less likely to receive a RIF notice. Value-added measures of teacher effectiveness can be calculated for a subset of the teachers and these show no relationship between effectiveness and the likelihood of receiving a RIF notice. Finally, simulations suggest that a very different group of teachers would be targeted for layoffs under an effectiveness-based layoff scenario than under the seniority-driven system that exists today. (Contains 3 figures, 7 tables and 68 footnotes.)

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Troels Gannerup Christensen

Jeg er ansat som adjunkt hos Læreruddannelsen i Jelling, hvor jeg underviser i matematik, specialiseringsmodulet teknologiforståelse, praktik m.m. Jeg har tidligere været ansat som pædagogisk konsulent i matematik og tysk hos UCL ved Center for Undervisningsmidler (CFU) i Vejle og lærer i udskolingen (7.-9. klasse) på Lyshøjskolen i Kolding. Jeg er ejer af og driver bl.a. hjemmesiderne www.lærklokken.dk og www.iundervisning.dk, ggbkursus.dk og er tidligere fagredaktør på matematik på emu.dk. Jeg går ind for, at læring skal være let tilgængelig og i størst mulig omfang gratis at benytte.

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