Learning to Be a Responsive, Authoritative Teacher: Effects of Experience and Age on Teachers’ Interactional Styles

2020 ◽  
pp. 1-12
Author(s):  
Bruce Torff ◽  
Kathleen Kimmons
Keyword(s):  
Teacher Effects

scholarly journals Teacher Effects on Chilean Children’s Achievement Growth: A Cross-Classified Multiple Membership Accelerated Growth Curve Model

2018 ◽  
Vol 40 (3) ◽  
pp. 473-501 ◽  
Author(s):  
Lorena Ortega ◽  
Lars-Erik Malmberg ◽  
Pam Sammons
Keyword(s):  
Student Achievement ◽  
Growth Curve ◽  
Growth Models ◽  
Teacher Effects ◽  
Combined Use ◽  
Achievement Growth ◽  
Children's Achievement ◽  
Accelerated Growth ◽  
Multiple Membership ◽  
Achievement Trajectories

We investigated teacher effects (magnitude, predictors, and cumulativeness) on primary students’ achievement trajectories in Chile, using multilevel cross-classified (accelerated) growth models (four overlapping cohorts, spanning Grades 3 to 8; n = 19,704 students, and 851 language and 812 mathematics teachers, in 156 schools). It was found that teacher effects on achievement growth are large, exceeding school effects. Also, the contribution of teachers to student achievement growth was found to accumulate over time. The study advances the field by exploring teacher effects in the context of an emerging economy, contributing further evidence on the properties of teacher effects on student achievement growth and demonstrating the combined use of accelerated longitudinal designs, growth curve approaches, and cross-classified and multiple membership models.

How Large Are Teacher Effects?

2004 ◽  
Vol 26 (3) ◽  
pp. 237-257 ◽  
Author(s):  
Barbara Nye ◽  
Spyros Konstantopoulos ◽  
Larry V. Hedges
Keyword(s):  
Student Achievement ◽  
Mathematics Achievement ◽  
Low Socioeconomic Status ◽  
Variance Components ◽  
Selection Effects ◽  
Teacher Effects ◽  
Low Socioeconomic ◽  
Achievement Gains ◽  
Teacher Effect ◽  
Teachers And Students

It is widely accepted that teachers differ in their effectiveness, yet the empirical evidence regarding teacher effectiveness is weak. The existing evidence is mainly drawn from econometric studies that use covariates to attempt to control for selection effects that might bias results. We use data from a four-year experiment in which teachers and students were randomly assigned to classes to estimate teacher effects on student achievement. Teacher effects are estimated as between-teacher (but within-school) variance components of achievement status and residualized achievement gains. Our estimates of teacher effects on achievement gains are similar in magnitude to those of previous econometric studies, but we find larger effects on mathematics achievement than on reading achievement. The estimated relation of teacher experience with student achievement gains is substantial, but is statistically significant only for 2nd-grade reading and 3rd-grade mathematics achievement. We also find much larger teacher effect variance in low socioeconomic status (SES) schools than in high SES schools.

Research on Teacher Effects: Uses and Abuses

1988 ◽  
Vol 89 (1) ◽  
pp. 3-21 ◽  
Author(s):  
Jere Brophy
Keyword(s):  
Teacher Effects

TEACHER EFFECTS ON HIGH SCHOOLACADEMIC ACHIEVEMENT SCORES: A CASE STUDY OF BUSIA COUNTY, KENYA

2021 ◽  
pp. 131-139
Author(s):  
Julius Maiyo ◽  
Manasi Echaune
Keyword(s):  
Academic Achievement ◽  
Hierarchical Linear Modeling ◽  
Teacher Commitment ◽  
Achievement Scores ◽  
Linear Modeling ◽  
Teacher Effects ◽  
Education Production Function ◽  
Education Production ◽  
Descriptive Survey

ABSTRACT This study sought to analyze teacher effects on high school academic achievement scores in Busia County, Kenya. The study was based on the education production function theory. A descriptive survey research design was employed. A sample of 236 teachers and 755 students was used. Self administered questionnaires were used to collect data and test re-test was used to ascertain reliability of the instrument. Descriptive statistics namely; percentages, frequencies, mean, and standard deviations were used to carry out preliminary data analysis. Inferential statistics specifically correlation and regression coefficients were then used to test hypotheses. Hierarchical linear modeling was used to model effect of selected teacher variables on school academic achievement scores. Findings of the study were presented in tables and figures. Findings of the study suggested that the number of teachers, teacher commitment and teachers covering missed lessons had statistically significant effects on school academic achievement scores. Key words: Teacher Variables, Academic Achievement Scores, Kenya

Impact Evaluation Using Analysis of Covariance With Error-Prone Covariates That Violate Surrogacy

2019 ◽  
Vol 43 (6) ◽  
pp. 335-369
Author(s):  
J. R. Lockwood ◽  
Daniel F. McCaffrey
Keyword(s):  
Measurement Error ◽  
Measurement Errors ◽  
Ordinary Least Squares ◽  
Analysis Of Covariance ◽  
Asymptotic Results ◽  
Teacher Effects ◽  
Intervention Effects ◽  
Ols Regression ◽  
Ancova Model

Background: Analysis of covariance (ANCOVA) is commonly used to adjust for potential confounders in observational studies of intervention effects. Measurement error in the covariates used in ANCOVA models can lead to inconsistent estimators of intervention effects. While errors-in-variables (EIV) regression can restore consistency, it requires surrogacy assumptions for the error-prone covariates that may be violated in practical settings. Objectives: The objectives of this article are (1) to derive asymptotic results for ANCOVA using EIV regression when measurement errors may not satisfy the standard surrogacy assumptions and (2) to demonstrate how these results can be used to explore the potential bias from ANCOVA models that either ignore measurement error by using ordinary least squares (OLS) regression or use EIV regression when its required assumptions do not hold. Results: The article derives asymptotic results for ANCOVA with error-prone covariates that cover a variety of cases relevant to applications. It then uses the results in a case study of choosing among ANCOVA model specifications for estimating teacher effects using longitudinal data from a large urban school system. It finds evidence that estimates of teacher effects computed using EIV regression may have smaller bias than estimates computed using OLS regression when the data available for adjusting for students’ prior achievement are limited.

scholarly journals Teacher Effects on Student Achievement and Height: A Cautionary Tale

2019 ◽  
Author(s):  
Marianne Bitler ◽  
Sean Corcoran ◽  
Thurston Domina ◽  
Emily Penner
Keyword(s):  
Student Achievement ◽  
Cautionary Tale ◽  
Teacher Effects
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