Variance In Student Achievement Research Articles

School size, student achievement, and the "power rating" of poverty: Substantive finding or statistical artifact?

The proportion of variance in student achievement that is explained by student SES-"poverty's power rating," as some call it-tends to be lower among smaller schools than among larger schools. Smaller schools, many claim, are able to somehow disrupt the seemingly axiomatic association between SES and student achievement. Using eighth-grade data for 216 public schools in Maine, I explored the hypothesis that this in part is a statistical artifact of the greater volatility (lower reliability) of school-aggregated student achievement in smaller schools. This hypothesis received no support when reading achievement served as the dependent variable. In contrast, the hypothesis was supported when the dependent variable was mathematics achievement. For reasons considered in the discussion, however, I ultimately concluded that the latter results are insufficient to affirm the statistical-artifact hypothesis here as well. Implications for subsequent research are discussed.

Leadership as Accountability for Learning: The Effects of School Poverty, Teacher Experience, Previous Achievement, and Principal Preparation Programs on Student Achievement

In the current era of accountability for achievement, school principals play the pivotal role of instructional leader. In a high-stakes testing environment, leadership preparation programs in universities and school districts need to be positively related to academic outcomes. The purpose of this study was to examine the relationship between school leadership preparation programs and student achievement in urban settings. Because leadership is contingent on the setting, school contextual factors and their impact on student achievement framed this study. Regression techniques were employed to construct a conceptual model with predictors of criterion and norm-referenced student achievement scores. Confirming previous research findings, student poverty, teacher experience, and previous achievement were the strongest predictors and accounted for a significant amount of variance in student achievement; however, university and district preparation programs were not significant predictors. Implications for policy, practice, and future research are discussed.

Using educational effectiveness research to design international comparative studies: turning limitations into new perspectives

This paper argues that Educational Effectiveness Research (EER) could be a foundation upon which studies of the International Association of the Evaluation of Education (IEA) could be based, both in terms of their design and in terms of data analysis. First, it is supported that multilevel modelling techniques, some of the most frequently used statistical techniques in the domain of EER, offer a wider spectrum in analysing IEA data. An illustrative example is used to provide support for this argument. Specifically, TIMSS 1999 data concerning student self-perceptions and achievement in both mathematics and science were analysed using single- and multilevel analyses. While single-level analysis resulted in positive correlations at the micro-level and negative correlations at the macro-level, the findings of multilevel analysis did not support such contradictious relationships. Second, the paper argues that the design of international comparative studies could be based on the theoretical models of EER that attempt to explain the variation in student achievement by taking into account variables at different levels. To support this argument a large number of variables taken from the student, teacher and school questionnaires of TIMSS 1999 associated with the comprehensive model of educational effectiveness were added to a multilevel model. Implications for the design of comparative studies are drawn.

Bridging or buffering?

PurposeRational and open system theories offer divergent sets of tactics on how best to deal with factors outside the boundary of the school. This study compared two competing strategies that emerge from these theories: bridging and buffering. The impact of how schools interact with their environments was examined in relation to student achievement.Design/methodology/approachThe competing theories were operationalized into two survey measures that tapped teacher perceptions of their schools’ orientations toward the environment. Using schools as the unit of analysis, two competing perspectives were contrasted together with their relative impact on student achievement on standardized tests.FindingsMultiple regression was used to assess the relative weight of each of these constructs in explaining the variance in student achievement. Bridging strategies explained a greater proportion of the variance than buffering.Research limitations/implicationsData were limited to teacher perceptions of the strategies employed by their schools to relate to the external environments. Enactments of these strategies are generally conceived and initiated by school administrators. Schools are dependent on their environments for survival. If the community is perceived as a threat, school leaders will attempt to insulate the technical core of teaching by buffering teachers from environmental disturbances. If, however, the community is perceived as a potential resource, school leaders will attempt to build bridges and create a symbiotic interdependence. Findings suggest that the latter is a more productive strategy for school administrators to employ.Originality/valueTo date, little research has been done on these competing strategies that would guide the practice of school leaders in how to best invest their energies in relation to their external environments.

Trends of School Effects on Student Achievement: Evidence from Nls:72, Hsb:82, and Nels:92

The impact of schools on student achievement has been of great interest for the last four decades. This study examines trends of school effects on student achievement employing three national probability samples of high school seniors: NLS:72, HSB:82, and NELS:92. Hierarchical linear models are used to investigate school effects. The findings reveal that the substantial proportion of the variation in student achievement lies within schools not between schools. There is also considerable between school variation in achievement, which becomes larger over time. Schools are more diverse and more segregated in the 1990s than in the 1970s. In addition, school characteristics such as school region, school SES, and certain characteristics of the student body of the school, such as students' daily attendance, students in college preparatory classes, and high school graduates enrolled in colleges are important predictors of average student achievement. The school predictors explained consistently more than 50% of the variation in average student achievement across surveys. We also find considerable teacher heterogeneity in achievement within schools, which suggests important teacher effects on student achievement. Teacher heterogeneity in student achievement was larger than school heterogeneity, which may indicate that teacher effects have a relatively larger impact on mathematics and science student achievement than school effects.

Classroom and School Factors Affecting Mathematics Achievement: A Comparative Study of Australia and the United States Using TIMSS

Recent work on differences in mathematics achievement has highlighted the importance of classroom, teacher and school factors. The present study used data from the Third International Mathematics and Science Study (TIMSS) to look at student, classroom and school factors influencing mathematics achievement in Australia and the United States (US). It found that classroom differences account for about one-third of the variation in student achievement in the US and over one-quarter in Australia. Most of the classroom variation in both countries was due to compositional and organisational factors, very little of it due to differences between teachers. This has important implications for policy regarding the improvement of mathematics achievement. It suggests that school systems may gain little by targeting teachers only, and need to give consideration to the role of pupil grouping practices and the effects of tracking and streaming on classroom learning environments.

Design, validation, and use of an evaluation instrument for monitoring systemic reform

AbstractOver the past decade, state and national policymakers have promoted systemic reform as a way to achieve high‐quality science education for all students. However, few instruments are available to measure changes in key dimensions relevant to systemic reform such as teaching practices, student attitudes, or home and peer support. Furthermore, Rasch methods of analysis are needed to permit valid comparison of different cohorts of students during different years of a reform effort. This article describes the design, development, validation, and use of an instrument that measures student attitudes and several environment dimensions (standards‐based teaching, home support, and peer support) using a three‐step process that incorporated expert opinion, factor analysis, and item response theory. The instrument was validated with over 8,000 science and mathematics students, taught by more than 1,000 teachers in over 200 schools as part of a comprehensive assessment of the effectiveness of Ohio's systemic reform initiative. When the new four‐factor, 20‐item questionnaire was used to explore the relative influence of the class, home, and peer environment on student achievement and attitudes, findings were remarkably consistent across 3 years and different units and methods of analysis. All three environments accounted for unique variance in student attitudes, but only the environment of the class accounted for unique variance in student achievement. However, the class environment (standards‐based teaching practices) was the strongest independent predictor of both achievement and attitude, and appreciable amounts of the total variance in attitudes were common to the three environments. © 2001 John Wiley & Sons, Inc. J Res Sci Teach 38: 646–662, 2001

Accounting for Variation in Science and Mathematics Achievement: A Multilevel Analysis of Australian Data Third International Mathematics and Science Study (Timss)

One of the most consistent themes evident in the literature dealing with rural education is that of rural disadvantage. Much research and literature indicates that students from rural schools receive an education that is inferior to that of students from larger urban or suburban schools. Of the matrix of factors reported to lead to that disadvantage, geographical isolation and the extent to which it restricts access is reported to result in rural schools not having the same standard of resource allocation as urban schools where access is not a problem. This study addresses the issue of resource availability in rural and urban Australian schools and includes the variables: students' attitudes towards science and mathematics and career aspirations of these students. The analysis includes socioeconomic status and gender of these students and investigates how these variables relate to student achievement. Do students in rural schools have the same educational opportunity as students in urban schools? In this study a multilevel model is used which takes into account the classroom level variance in student achievement as well as individual variance and school level variance.

Social and Psychological Factors in the Academic Achievement of Children of Immigrants: A Cultural History Puzzle

The influence of various factors in immigrant students' school achievement was examined in informing broader discourses on schooling, inequality, and related conceptual issues. The ways in which different types of predictors of school achievement behave in context with factors related to adolescence and cultural adaptation in a sample of children of immigrants were explored. The influence of cultural background remains enigmatic and could not be disaggregated entirely by key demographic and sociopsychological factors considered in this study. The latter explained almost 40% of the variation in student achievement. The two groups found to excel in American schools (Asian and Cuban) have more established inroads in the community and may be able to provide greater social and cognitive support. The lowest achievers were from groups that have the least support, encounter language problems in school, and felt most unwelcomed by the mainstream. The cultural compatibility between each group and the school context appears to vary in systematic ways and is addressed in a model proposed in the article.

Variation in Effectiveness Between Private and Public Schools: The Impact of School and Family Networks*

Abstract Building upon the assumption that cohesion between different levels of the school is essential to the schools’ effectiveness, the hypothesis is tested that a close kinship between school and parental community causes a positive effect on student outcomes in primary schools. Recent theories regarding the effects of ‘functional communities’ on academic achievement mainly focus on the characteristics of the parental community that surrounds a school. Recognizing, however, that schools differ regarding their responsiveness to the role of parents and other actors around the school, our expectation is that a definition of functional community which comprises interactions between characteristics of the parental network around the school and the governance structure of the school offers a better explanation of variation in student achievement. Based on a national sample of 90 schools for primary education in the Netherlands, our analysis shows that the differences in math achievement for public and private primary schools are mediated by characteristics at both the family and the institutional level. It also indicates that characteristics at the institutional level are conditional for the effects of parental networks around schools.

The impact of educational policy reforms on the distribution of educational outcomes in developing countries: The case of Botswana

After half a decade of concerted government efforts to provide equal educational opportunity through comparable educational provisions, Botswana's basic education system is atypical of those studied in such developing countries as India, Swaziland, Nigeria, Egypt, Chile, Brazil and Thailand. The system defies conclusions of studies previously conducted in developing countries that, compared to student characteristics, school characteristics account for a relatively higher proportion of the variance in student achievement. Using the organizational approach, and the variance components analytical approach (Hierarchial Linear Models) to the study of school effects, the partitioning of the variance between the school and student characteristics resembles that reported in the United States and Britain. Up to 88% of the variance in achievement lies within schools, while only 12% lies between schools.

Methodological Issues in Educational Performance and School Effectiveness Research: A Discussion with Worked Examples

There has been a growing awareness among educational researchers of the consequences of using data-analytic models that fail to account for the inherent clustered or hierarchical sampling structure of the data typically obtained. Such clustering poses special analytic problems related to levels of analysis, aggregation bias, heterogeneity of regression and parameter mis-estimation, with important implications for the correct interpretation of effects. This paper compares the results obtained from fitting single-level and multilevel models to two hierarchically structured data sets designed to explain variation in student achievement. Emphasis is given to the crucial importance of fitting models commensurate with the sampling structure of the data to which they are applied.

Stability of school effects in dutch secondary education: The impact of variance across subjects and years

This chapter reports the results of an investigation into the stability across both years and subjects of school effects in Dutch secondary education. What distinguishes the present study from previous ones dealing with the stability of school effects is the fact that two types of instability have been investigated simultaneously. Not only the instability across years and subjects has been established, but also their interaction. This interaction effect should be interpreted as follows: a school may produce outstanding results with respect to a certain subject one year, while the next year the same school may reveal rather poor results for the same subject. The following specific research questions were addressed: (1) What percentage of the total variance in student achievement per subject can be attributed to differences between schools and to what extent are these effects stable across years? (2) To what extent are school effects stable across subjects? (3) To what extent does the instability across years interact with the instability across subjects? The school effects per subject were found to be fairly stable across years, but schools appeared to produce remarkably divergent results across subjects. A substantial interaction effect of instability across years and subjects was detected as well. The findings largely corroborate the conclusions of recent studies stressing the important role of departments in secondary schools. The general differences between schools with respect to student achievement turned out to be very modest, making up no more than 4% of the total variance in student achievement.

The association between student ratings of specific instructional dimensions and student achievement: Refining and extending the synthesis of data from multisection validity studies

This synthesis extends part of Peter Cohen's well-known examination of the association between student ratings of instruction and student achievement. The results of increasing the number of specific instructional dimensions considered and of preserving more of the information in the evaluations by multiple coding into these dimensions are compared with Cohen's findings. Extending the analysis further by changing the unit of analysis and the method of averaging correlations generally decreases the size of the associations. The instructor's preparation and organization, clarity and understandableness, stimulation of interest, motivation of students to reach high standards, encouragement of discussion and openness to others' opinions, and elocutionary skills consistently explain 10% or more of the variance in student achievement regardless of the method of averaging or the unit of analysis used. The size of the association between an instructional characteristic and student achievement, as one indicator of the characteristic's importance, is compared with three other indicators (extent to which students say the characteristic is important, extent to which faculty say it is important, and size of its correlation with the overall evaluation of the instructor).

Teaching quality and student achievement in Africa: The case of Nigeria and Swaziland

This paper uses ordinary regression and multi-level analytic techniques to examine the effects of schools, teachers, and teaching processes on enhancing grade 8 mathematics achievement in Nigeria and Swaziland. A significant proportion of variance in student achievement (24% in Nigeria and 16% in Swaziland) was attributable to between-classroom/school factors. School size, class size, and length of the school year had no effect on student achievement, but teaching processes were important in both countries. However, patterns of effects differed between the two countries, suggesting caution be taken in making generalizations about the nature of effective mixes of inputs.

The Influence of Learning and Teaching Styles on Student Attitudes and Achievement in the Introductory Economics Course: A Case Study

Research on the impact of learning style preferences is very rare in economic education. This article reports the results of a project in which the student's preferred learning style and the instructor's teaching style were included as variables in a regression model. Those favoring independent styles achieved significantly more than students favoring dependent styles. Changes in student attitudes towards economics were also taken into account. The researchers assert that the addition of these variables also “greatly increases the power of the model to explain variation in student achievement and attitudes concerning economics.”

What do effective teachers of inner-city children have in common?

This paper investigates the extent to which variables describing the classroom behavior of teachers and variables describing teachers' backgrounds and training explain differences in the effectiveness of teachers in improving the vocabulary skills of inner-city black children in four elementary grade levels. The results indicate that both types of variables explain significant portions of the variation in student achievement. In other words, teachers' choices of techniques matter; and the characteristics of teachers provide some information about their effectiveness. However, the pattern of results indicates that great care must be taken in interpreting individual coefficients. The paper concludes with an interpretation of the results and with suggestions for new directions for research on teaching that follow from this interpretation.

A replication study of unique and joint contributions to variance in student achievement.

A replication study of unique and joint contributions to variance in student achievement.

A replication study of unique and joint contributions to variance in student achievement.

A replication study of unique and joint contributions to variance in student achievement.

Educational Need and Its Application to State School Finance

This article reports the results of an effort to use local school personnel to gather socioeconomic data on students that would be highly predictive of educational achievement, and to use the information so gathered as the basis for a formula that would distribute state school aid to schools on the basis of their educational need. School secretaries in 45 New York elementary schools, using only written instructions, gathered data for a sample of students on six socio-economic variables: ethnic background, broken homes, welfare, overcrowded housing, student mobility, and parents' education. In a multiple regression, using the school as the unit of analysis, these variables explain 75 percent of the variation in student achievement. Based on the regression equation, the article defines as a unit of educational need the Need Weighted Average Daily Attendance (NWADA) and shows how this unit may be used in a state school-support formula.