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How to Measure a Teacher: The Influence of Test and Nontest Value-Added on Long-Run Student Outcomes. Working Paper No. 270-0423-2

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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
FullText Text:
  Availability: 0
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  Data: 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
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– Name: Abstract
  Label: Abstract
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  Data: 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.
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  Data: ED628004
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    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 65
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      – SubjectFull: Teacher Effectiveness
        Type: general
      – SubjectFull: Teacher Evaluation
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      – SubjectFull: Outcomes of Education
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      – SubjectFull: Learning Trajectories
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      – SubjectFull: Value Added Models
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      – SubjectFull: Tests
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      – SubjectFull: College Attendance
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      – SubjectFull: Selective Admission
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      – SubjectFull: Prediction
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      – SubjectFull: Correlation
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      – TitleFull: How to Measure a Teacher: The Influence of Test and Nontest Value-Added on Long-Run Student Outcomes. Working Paper No. 270-0423-2
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