| Title: |
How to Measure a Teacher: The Influence of Test and Nontest Value-Added on Long-Run Student Outcomes. Working Paper No. 270-0423-2 |
| Language: |
English |
| Authors: |
Backes, Ben; Cowan, James; Goldhaber, Dan; Theobald, Roddy; National Center for Analysis of Longitudinal Data in Education Research (CALDER) at American Institutes for Research (AIR) |
| Source: |
National Center for Analysis of Longitudinal Data in Education Research (CALDER). 2023. |
| Availability: |
National Center for Analysis of Longitudinal Data in Education Research. American Institutes for Research, 1000 Thomas Jefferson Street NW, Washington, DC 20007. Tel: 202-403-5796; Fax: 202-403-6783; e-mail: info@caldercenter.org; Web site: https://caldercenter.org |
| Peer Reviewed: |
N |
| Page Count: |
65 |
| Publication Date: |
2023 |
| Sponsoring Agency: |
Institute of Education Sciences (ED) |
| Contract Number: |
R305S210012 |
| Document Type: |
Reports - Research; Numerical/Quantitative Data |
| Education Level: |
Higher Education; Postsecondary Education |
| Descriptors: |
Teacher Effectiveness; Teacher Evaluation; Outcomes of Education; Learning Trajectories; Value Added Models; Academic Achievement; Tests; College Attendance; Selective Admission; Prediction; Correlation; Evaluation Methods; Educational Theories |
| Abstract: |
This paper examines how different measures of teacher quality are related to students' long-run educational trajectories. We estimate teachers' "test-based" and "nontest" value-added (the latter based on contributions to student absences, suspensions, grade progression, and grades) and assess how these predict various student postsecondary outcomes. We find that both types of value-added have positive effects on student outcomes. Test-based teacher quality measures have more explanatory power for outcomes relevant for students at the top of the achievement distribution, such as attending a more selective college, while nontest measures have more explanatory power for whether students enroll in college at all. |
| Abstractor: |
As Provided |
| IES Funded: |
Yes |
| Entry Date: |
2023 |
| Accession Number: |
ED628004 |
| Database: |
ERIC |