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ERIC Number: EJ956816
Record Type: Journal
Publication Date: 2012-Mar
Pages: 13
Abstractor: As Provided
Reference Count: 24
ISSN: ISSN-0162-3737
Using Subject Test Scores Efficiently to Predict Teacher Value-Added
Lefgren, Lars; Sims, David
Educational Evaluation and Policy Analysis, v34 n1 p109-121 Mar 2012
This article develops a simple model of teacher value-added to show how efficient use of information across subjects can improve the predictive ability of value-added models. Using matched student-teacher data from North Carolina, we show that the optimal use of math and reading scores improves the fit of prediction models of overall future teacher value-added by up to a third for reading and a tenth for a composite measure (math and reading combined). Efficiency gains are greatest when value-added must be calculated on only 1 or 2 years of data. The methods employed are flexible and can be expanded to incorporate information from other subject or subitem test metrics. (Contains 4 tables and 4 notes.)
SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail:; Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: Elementary Education; Higher Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: North Carolina
IES Cited: ED544673; ED544674