Eric Taylor (email@example.com) is a doctoral student at Stanford University, and a Spencer Dissertation Fellow for 2014-15. Eric studies labor and personnel economics in the education sector, and applied econometric methods. His job market paper “New Technology and Teacher Productivity” examines how new instructional computer technology affects classroom teachers’ productivity and job decisions. Eric’s previous research has been published in the American Economic Review, Journal of Human Resources, and Journal of Public Economics. His research on teacher evaluation has been featured in Slate, Time, The Washington Post, and Education Week. In 2013 Eric was recognized for Excellence in Teaching and Mentoring by the Stanford GSE, and in 2006 he received the Chancellor’s Service Award at UCLA. Prior to Stanford, Eric worked at Harvard’s Center for Education Policy Research.
Research Interests: Personnel Economics, Labor Economics, Economics of Education, Applied Econometrics
- Stanford University, Ph.D., Economics of Education, expected June 2015
- Stanford University, M.A., Economics, 2014
- UCLA, M.P.P., 2006
- Brigham Young University, B.S., Economics, 2004
I study the effects of a labor-replacing computer technology on the productivity of classroom teachers. In a series of field-experiments, teachers were provided computer-aided instruction software for use in their classrooms—CAI provides individualized tutoring and practice to students one-on-one. In math classes, CAI reduces by one-fifth the variance of teacher productivity, as measured by student test score gains. The smaller variance comes both from productivity improvements for otherwise low-performing teachers, but also losses among high-performers. The change in productivity partly reflects changes in teachers’ level of work effort and teachers’ decisions about how to allocate class time. How computers affect teacher decisions and productivity is immediately relevant to both ongoing education policy debates about teaching quality and the day-to-day management of a large workforce.
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