Screen Twice, Cut Once: Assessing the Predictive Validity of Teacher Selection Tools. Working Paper 120
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| Title: | Screen Twice, Cut Once: Assessing the Predictive Validity of Teacher Selection Tools. Working Paper 120 |
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| Language: | English |
| Authors: | Goldhaber, Dan, Grout, Cyrus, Huntington-Klein, Nick, National Center for Analysis of Longitudinal Data in Education Research (CALDER) at American Institutes for Research |
| Source: | National Center for Analysis of Longitudinal Data in Education Research (CALDER). 2014. |
| Availability: | National Center for Analysis of Longitudinal Data in Education Research. American Institutes for Research, 1000 Thomas Jefferson Street NW, Washington, DC 20007. Tel: 202-403-5000; Fax: 202-403-5454; e-mail: inquiry@caldercenter.org; Web site: http://www.caldercenter.org |
| Peer Reviewed: | N |
| Page Count: | 74 |
| Publication Date: | 2014 |
| Sponsoring Agency: | Institute of Education Sciences (ED) |
| Contract Number: | R305H130030 R305A060018 R305C120008 |
| Document Type: | Reports - Research |
| Education Level: | Elementary Secondary Education |
| Descriptors: | Teacher Selection, Predictive Validity, Selection Tools, Public Schools, Public School Teachers, Job Applicants, Academic Achievement, Teacher Attendance, Faculty Mobility, Value Added Models, Elementary Secondary Education |
| Geographic Terms: | Washington |
| Abstract: | Evidence suggests that teacher hiring in public schools is ad hoc and often fails to result in good selection among applicants. Some districts use structured selection instruments in the hiring process, but we know little about the efficacy of such tools. In this paper, we evaluate the ability of applicant selection tools used by the Spokane Public Schools to predict three outcomes: measures of teachers' value-added contributions to student learning, teacher absence behavior, and attrition rates. We observe all applicants to the district and are therefore able to estimate sample selection-corrected models, using random tally errors in selection instruments and differences in the quality of competition across job postings. These two factors influence the probability of being hired by Spokane Public Schools but are unrelated to measures of teacher performance. We find that the screening instruments predict teacher value added in student achievement and teacher attrition but not teacher absences. A one-standard-deviation increase in screening scores is associated with an increase of between 0.03 and 0.07 standard deviations in student achievement and a decrease in teacher attrition of 2.5 percentage points. The following are appended: (1) Tables and Figures; (2) Screening Rubrics and Generation of Applicant Data; and (3) Supplemental Descriptive and Regression Tables. |
| Abstractor: | As Provided |
| IES Funded: | Yes |
| Entry Date: | 2015 |
| Accession Number: | ED560673 |
| Database: | ERIC |
| Abstract: | Evidence suggests that teacher hiring in public schools is ad hoc and often fails to result in good selection among applicants. Some districts use structured selection instruments in the hiring process, but we know little about the efficacy of such tools. In this paper, we evaluate the ability of applicant selection tools used by the Spokane Public Schools to predict three outcomes: measures of teachers' value-added contributions to student learning, teacher absence behavior, and attrition rates. We observe all applicants to the district and are therefore able to estimate sample selection-corrected models, using random tally errors in selection instruments and differences in the quality of competition across job postings. These two factors influence the probability of being hired by Spokane Public Schools but are unrelated to measures of teacher performance. We find that the screening instruments predict teacher value added in student achievement and teacher attrition but not teacher absences. A one-standard-deviation increase in screening scores is associated with an increase of between 0.03 and 0.07 standard deviations in student achievement and a decrease in teacher attrition of 2.5 percentage points. The following are appended: (1) Tables and Figures; (2) Screening Rubrics and Generation of Applicant Data; and (3) Supplemental Descriptive and Regression Tables. |
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