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The Predictive Validity of Information From Clinical Practice Lessons: Experimental Evidence From Argentina

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2015-05-17

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Ganimian, Alejandro Jorge. 2015. The Predictive Validity of Information From Clinical Practice Lessons: Experimental Evidence From Argentina. Doctoral dissertation, Harvard Graduate School of Education.

Abstract

A growing number of teacher preparation programs require trainees to practice teaching. Yet, there is almost no evidence on whether the performance of individuals during clinical practice lessons predicts how they fare once they enter the school system.
We address this question by taking advantage of the fact that an alternative pathway into teaching in Argentina requires admitted applicants to complete two weeks of clinical practice. We collect information both during clinical practice and the school year. During clinical practice, we measure the performance of teaching trainees using classroom observations and student surveys. During the school year, we measure their performance using classroom observations, student surveys, and principal surveys. We find that the overall performance of trainees during clinical practice predicts their overall performance during the school year, but this prediction is only statistically under certain model specifications. The performance of these individuals during clinical practice predicts their ratings on classroom observations during the school year. This relationship remains statistically significant even when we account for how trainees fare on the application and selection processes of the alternative pathway. We also find that the performance of trainees on a brief demonstration lesson, delivered during the selection process, predicts their performance on classroom observations during the school year. The predictive effect is smaller than that of clinical practice lessons, but it raises the question of whether the additional effort required to collect information during clinical practice is worth the improved predictive validity.

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Economics, Labor

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