Creating Actionable Human Capital Analytics for Studying School-Level Teacher Retention
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| Title: | Creating Actionable Human Capital Analytics for Studying School-Level Teacher Retention |
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| Language: | English |
| Authors: | Robert Meyer, Anthony Milanowski, Ryan Veiga, Jessica Doherty |
| Source: | Journal of Education Human Resources. 2025 43(2):390-421. |
| Availability: | University of Toronto Press. 5201 Dufferin Street, Toronto, ON M3H 5T8, Canada. Tel: 416-667-7810; Fax: 800-221-9985; Fax: 416-667-7881; e-mail: journals@utpress.utoronco.ca; Web site: https://www.utpjournals.press/loi/jehr |
| Peer Reviewed: | Y |
| Page Count: | 32 |
| Publication Date: | 2025 |
| Sponsoring Agency: | Office of Elementary and Secondary Education (OESE) (ED) |
| Contract Number: | 537A120095 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Teacher Persistence, Faculty Mobility, School Districts, Human Capital, Data Analysis, Educational Environment, Teaching Conditions, Administrator Attitudes, Evaluation Methods, Institutional Characteristics, Differences, Educational Policy, Educational Practices |
| Geographic Terms: | Florida |
| DOI: | 10.3138/jehr-2023-0063 |
| ISSN: | 2562-783X |
| Abstract: | One potentially fruitful application for human capital analytics is to support policies and practices that might reduce undesirable teacher turnover. Teacher turnover can be harmful to student achievement and faculty cohesiveness and can exacerbate teacher shortages. This article describes an attempt to build a human capital analytics tool to help a school district better identify schools with problems retaining teachers as well as schools that are doing an especially good job of retaining them. It describes the theory of action for the school-level retention analytics tool, the models used to estimate persistent school effects and predict which schools would continue to have retention problems, and the features of a web-based tool developed to help district staff gain insights about the degree of variation among schools and likely contributing factors. We found that there were reliable differences in schools' persistent rates of teacher retention, the differences persisted after controlling for student demographics, teachers at different levels of effectiveness and experience have different predicted levels of retention, and there were substantial differences among schools in their ability to retain teachers at different levels of experience and effectiveness. Finally, we describe the initial reactions of the users for whom we designed the tool and what we learned about developing a retention analytic tool for use by school district administrators. |
| Abstractor: | As Provided |
| Entry Date: | 2025 |
| Accession Number: | EJ1467146 |
| Database: | ERIC |
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| Abstract: | One potentially fruitful application for human capital analytics is to support policies and practices that might reduce undesirable teacher turnover. Teacher turnover can be harmful to student achievement and faculty cohesiveness and can exacerbate teacher shortages. This article describes an attempt to build a human capital analytics tool to help a school district better identify schools with problems retaining teachers as well as schools that are doing an especially good job of retaining them. It describes the theory of action for the school-level retention analytics tool, the models used to estimate persistent school effects and predict which schools would continue to have retention problems, and the features of a web-based tool developed to help district staff gain insights about the degree of variation among schools and likely contributing factors. We found that there were reliable differences in schools' persistent rates of teacher retention, the differences persisted after controlling for student demographics, teachers at different levels of effectiveness and experience have different predicted levels of retention, and there were substantial differences among schools in their ability to retain teachers at different levels of experience and effectiveness. Finally, we describe the initial reactions of the users for whom we designed the tool and what we learned about developing a retention analytic tool for use by school district administrators. |
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| ISSN: | 2562-783X |
| DOI: | 10.3138/jehr-2023-0063 |
