世界経済・社会統計 = World development indicators

计量经济分析 = Econometric analysis

Preface Chapter 1 The challenge Chapter 2 The nature of the evidence: A synthesis of meta-analyses Chapter 3 The argument: Visible teaching and visible learning Chapter 4: The contributions from the student Chapter 5 The contributions from the home Chapter 6 The contributions from the school Chapter 7 The contributions from the teacher Chapter 8 The contributions from the curricula Chapter 9 The contributions from teaching approaches - I Chapter 10 The contributions from teaching approaches - II Chapter 11: Bringing it all together Appendix A: The 800 meta-analyses Appendix B: The meta-analyses by rank order References

Visible Learning: A Synthesis of Over 800 Meta-Analyses Relating to Achievement

The most commonly used method to test an indirect effect is to divide the estimate of the indirect effect by its standard error and compare the resulting z statistic with a critical value from the standard normal distribution. Confidence limits for the indirect effect are also typically based on critical values from the standard normal distribution. This article uses a simulation study to demonstrate that confidence limits are imbalanced because the distribution of the indirect effect is normal only in special cases. Two alternatives for improving the performance of confidence limits for the indirect effect are evaluated: (a) a method based on the distribution of the product of two normal random variables, and (b) resampling methods. In Study 1, confidence limits based on the distribution of the product are more accurate than methods based on an assumed normal distribution but confidence limits are still imbalanced. Study 2 demonstrates that more accurate confidence limits are obtained using resampling methods, with the bias-corrected bootstrap the best method overall.

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Confidence Limits for the Indirect Effect: Distribution of the Product and Resampling Methods.

The growing interest in Structured Equation Modeling (SEM) techniques and recognition of their importance in IS research suggests the need to compare and contrast different types of SEM techniques so that research designs can be selected appropriately. After assessing the extent to which these techniques are currently being used in IS research, the article presents a running example which analyzes the same dataset via three very different statistical techniques. It then compares two classes of SEM: covariance-based SEM and partial-least-squaresbased SEM. Finally, the article discusses linear regression models and offers guidelines as to when SEM techniques and when regression techniques should be used. The article concludes with heuristics and rule of thumb thresholds to guide practice, and a discussion of the extent to which practice is in accord with these guidelines.

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Structural equation modeling and regression: guidelines for research practice

Considerable controversy surrounds the impact of schools and teachers on the achievement of students. This paper disentangles the separate factors influencing achievement with special attention given to the role of teacher differences and other aspects of schools. Unique matched panel data from the Harvard/UTD Texas Schools Project permit distinguishing between total effects and the impact of specific, measured components of teachers and schools. While schools are seen to have powerful effects on achievement differences, these effects appear to derive most importantly from variations in teacher quality. A lower bound suggests that variations in teacher quality account for at least 7« percent of the total variation in student achievement, and there are reasons to believe that the true percentage is considerably larger. The subsequent analysis estimates educational production functions based on models of achievement growth with individual fixed effects. It identifies a few systematic factors a negative impact of initial years of teaching and a positive effect of smaller class sizes for low income children in earlier grades but these effects are very small relative to the effects of overall teacher quality differences.

Teachers, Schools, and Academic Achievement

N RECENT YEARS, public and professional interest in schools has been heightened by a spate of reports, many of them critical of current school policy.' These policy documents have added to persistent and long-standing concerns about the cost, effectiveness, and fairness of the current school structure, and have made schooling once again a serious public issue. As in the past, however, any renewed interest in education is likely to be short-lived, doomed to dissipate as frustration over the inability of policy to improve school practice sets in. This frustration about school policy relates directly to knowledge about the educational production process and in turn to underlying research on schools. Although the educational process has been extensively researched, clear policy prescriptions flowing from this research have been difficult to derive.2 There exists, however, a consistency to the research findings that does have an immediate application to school policy: Schools differ dramatically in "quality,"

https://www.jstor.org/stable/pdfplus/2725865.pdf

The Economics of Schooling: Production and Efficiency in Public Schools.

This paper disentangles the impact of schools and teachers in influencing achievement with special attention given to the potential problems of omitted or mismeasured variables and of student and school selection. Unique matched panel data from the UTD Texas Schools Project permit the identification of teacher quality based on student performance along with the impact of specific, measured components of teachers and schools. Semiparametric lower bound estimates of the variance in teacher quality based entirely on within-school heterogeneity indicate that teachers have powerful effects on reading and mathematics achievement, though little of the variation in teacher quality is explained by observable characteristics such as education or experience. The results suggest that the effects of a costly ten student reduction in class size are smaller than the benefit of moving one standard deviation up the teacher quality distribution, highlighting the importance of teacher effectiveness in the determination of school quality.

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Direct measures of labor-force quality from international mathematics and science test scores are strongly related to growth. Indirect specification tests are generally consistent with a causal link: direct spending on schools is unrelated to student performance differences; the estimated growth effects of improved labor-force quality hold when East Asian countries are excluded; and, finally, home-country quality differences of immigrants are directly related to U.S. earnings if the immigrants are educated in their own country but not in the United States. The last estimates of micro productivity effects, however, introduce uncertainty about the magnitude of the growth effects.

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Schooling, Labor-Force Quality, and the Growth of Nations

What is the value of an education? Volume 4 of the Handbooks in the Economics of Education combines recent data with new methodologies to examine this and related questions from diverse perspectives. School choice and school competition, educator incentives, the college premium, and other considerations help make sense of the investments and returns associated with education. Volume editors Eric A. Hanushek (Stanford), Stephen Machin (University College London) and Ludger Woessmann (Ifo Institute for Economic Research, Munich) draw clear lines between newly emerging research on the economics of education and prior work. In conjunction with Volume 3, they measure our current understanding of educational acquisition and its economic and social effects. It is the winner of a 2011 PROSE Award Honorable Mention in Economics from the Association of American Publishers. It demonstrates how new methodologies are yielding fresh perspectives in education economics. It presents topics and authors whose data and conclusions attest to the globalization of research. It complements the policy and social outcomes themes of volume 3.

Eric A. Hanushek

Papers

Teachers, Schools, and Academic Achievement

The Economics of Schooling: Production and Efficiency in Public Schools.

Teachers, Schools, and Academic Achievement

Schooling, Labor-Force Quality, and the Growth of Nations

Handbook of the economics of education