Sentences with phrase «by differences in test scores»

Not exact matches

Studies have shown no statistical difference in test scores of homeschooled children taught by parents who were certified teachers and homeschooled children who were taught by parents without teaching certificates.

He argued that although the drugs make little difference in patients» lives — improving cognitive test scores by only 4 percent — doctors choose to medicate them anyway because it's easy.

The absolute differences in scores were hardly dramatic: On average, the literary group outperformed the popular group by about two questions (out of 36) on the RMET test, and missed one fewer question (out of 18) on the DANVA2 - AF.

Ladner found that the reading and math test scores of 3rd graders were higher in schools that offered all - day kindergarten or pre-K, but by 5th grade the differences had disappeared.

Ferguson noted that the quality of the teacher (as determined by test scores, level of education, and experience) accounts for 43 percent of the difference in math scores of students in grades 3 to 5.

Evaluations led by Harvard's Tom Kane and MIT's Josh Angrist have used this lottery - based method to convince most skeptics that the impressive test - score performance of the Boston charter sector reflects real differences in school quality rather than the types of students charter schools serve.

Despite decades of relying on standardized test scores to assess and guide education policy and practice, surprisingly little work has been done to connect these measures of learning with the measures developed over a century of research by cognitive psychologists studying individual differences in cognition.

This objection also applies to several popular methods of standardizing raw test scores that fail to account sufficiently for differences in test items — methods like recentering and rescaling to convert scores to a bell - shaped curve, or converting to grade - level equivalents by comparing outcomes with the scores of same - grade students in a nationally representative sample.

Murray's earlier books — Losing Ground in 1984, on welfare policy, and The Bell Curve (with Richard Herrnstein) in 1994, on the significance of differences in intelligence as measured by intelligence tests — aroused controversy, because, implicitly or explicitly, they focused attention on black Americans, who play a disproportionate role in welfare policy, and as a group score lower than whites on IQ tests.

Because of the need for nationally standardized achievement tests to provide fine - grained, percentile - by - percentile comparisons, it is imperative that these tests produce a considerable degree of score spread — in other words, plenty of differences among test takers» scores.

We compare the test scores of students in each of the seven categories, taking into account differences in the students» socioeconomic characteristics, including parent schooling, self - reported household income, the number of non-school books in the home, and the quality of the peer groups (calculated by averaging family background and home resources for all students in the classroom).

To refine the comparison, we account for the slight differences in the observable traits, including earlier test scores, that emerged by chance between lotteried - in and lotteried - out applicants.

The first paper, released in July 2009 by Roland Fryer and Steven Levitt, found that while there are no mean differences between boys and girls in math when they start school, girls gradually lose ground, so that the gap between boys and girls after six years of schooling is half as large as the black - white test score gap.

By design, this third approach fully adjusts student test scores for differences in student and school characteristics.

In reading, however, we found no difference in the test - score gains achieved by F schools and low - performing non-F schools, suggesting that regression to the mean could be influencing our results in readinIn reading, however, we found no difference in the test - score gains achieved by F schools and low - performing non-F schools, suggesting that regression to the mean could be influencing our results in readinin the test - score gains achieved by F schools and low - performing non-F schools, suggesting that regression to the mean could be influencing our results in readinin reading.

These and the other scattered marginally significant contrasts in the table seem likely to be chance findings, a conclusion supported by the F statistics at the bottom of each column, which test the joint hypothesis that all differences in baseline test scores and background characteristics in the column are 0.

These findings are consistent with — but not definitive proof of — the argument that systematic differences in the schools attended by white and black children may explain the divergence in test scores.

By year four, there was no statistically significant difference in math test scores between students who remained in private schools and the matched comparison group.

Using data from a variety of sources, including the National Longitudinal Survey of Youth, the High School and Beyond study, and the National Longitudinal Study of the High School Class of 1972, Jacobsen and his colleagues at Mathematica essentially confirm Neal and Johnson's findings, providing additional evidence that most of the remaining wage gap is due to differences in cognitive skills, as measured by test scores.

A key difference between school reviews in England and the United States is that U.S. schools are held accountable primarily through test scores and other quantifiable data, whereas in England, test scores are supplemented by observational data inspectors gather.

Scores for 17 - year - olds, the third age group tested by NAEP, are a point or two higher than they were in the 1970s but the difference is not statistically significant.

Even if we were confident that the test score gains in New Orleans are not being driven by changes in the student population following Katrina (and Doug and his colleagues are doing their best with constrained data and research design to show that), and even if these test score gains translate into higher high school graduation and college attendance rates (which Doug and his colleagues have not yet been able to examine), we still would have no idea whether portfolio management and other high regulations in NOLA helped, hurt, or made no difference in producing these results.

The states differ significantly in the racial or ethnic composition of students and in the characteristics of the families of students, so it would be expected that a significant part of the differences in the NAEP test scores might be accounted for by these differences.

2000 Results began to demonstrate that the changes in Finland's educational system were making a significant difference as demonstrated by scoring third on a global assessment, the Programme for International Student Assessment (PISA), a standardized test given to 15 - year - olds in approximately 40 countries.

The difference in test scores produced by the incentive system was about the same as that detected in earlier studies that measured differences in student performance when kids were taught by great teachers rather than average teachers.

Our school profiles now include important information in addition to test scores — factors that make a big difference in how children experience school, such as how much a school helps students improve academically, how well a school supports students from different socioeconomic, racial and ethnic groups, and whether or not some groups of students are disproportionately affected by the school's discipline and attendance policies.

Few differences existed across groups in 9th grade, but by the end of 10th grade, students» test scores, academic grade point averages, and progress to graduation tended to be better for the students in programs of study (i.e., treatment students) than for control / comparison students.

However, to the dismay of teachers, Governor Cuomo balked at a proposal by legislators to impose a two - year moratorium on the use of Common Core standardized test scores in teacher evaluations, saying, «There is a difference between remedying the system for students and parents and using this situation as yet another excuse to stop the teacher - evaluation process.»

In spite of the many millions of dollars poured into expounding the theory of paying teachers for higher student test scores (sometimes mislabeled as «merit pay»), a new study by Vanderbilt University's National Center on Performance Incentives found that the use of merit pay for teachers in the Nashville school district produced no difference even according to their measure, test outcomes for studentIn spite of the many millions of dollars poured into expounding the theory of paying teachers for higher student test scores (sometimes mislabeled as «merit pay»), a new study by Vanderbilt University's National Center on Performance Incentives found that the use of merit pay for teachers in the Nashville school district produced no difference even according to their measure, test outcomes for studentin the Nashville school district produced no difference even according to their measure, test outcomes for students.

Effect size for the adjusted mean difference between each treatment was calculated by dividing the mean difference in test score by the square root of the within mean square error for the adjusted post-test score.

In addition, this questionnaire presents good test — retest reliability, even for testing after 6 months (correlation coefficients from 0.60 to 0.90, except for bodily pain (0.43)-RRB-.53 Finally, the SF - 36 is sensitive to change, 57 with a difference of 5 points in scale scores being clinically significant, as suggested by Ware et al. In addition, this questionnaire presents good test — retest reliability, even for testing after 6 months (correlation coefficients from 0.60 to 0.90, except for bodily pain (0.43)-RRB-.53 Finally, the SF - 36 is sensitive to change, 57 with a difference of 5 points in scale scores being clinically significant, as suggested by Ware et al. in scale scores being clinically significant, as suggested by Ware et al. 58

A t - test showed significant differences in relationship scores by gender (t = 2.22, p < 0.05), location (urban vs. rural)(t = 3.33, p < 0.01) and family type (single - child family vs. non-single child family)(t = 3.72, p < 0.001).

Differences in the strengths of correlations between boys and girls were tested by converting the two correlations to z - scores, dividing the difference between the z - scores with the standard error of difference between the two correlations, and then testing the significance of the z value of the difference score.