scholarly journals Mathematics Achievement by Immigrant Children

2000 ◽  
Vol 8 ◽  
pp. 25
Author(s):  
Gary G. Huang
Keyword(s):  
Hierarchical Linear Modeling ◽  
Science Achievement ◽  
English Language ◽  
The United States ◽  
Immigrant Children ◽  
Math Performance ◽  
Linear Modeling ◽  
Language Background ◽  
Indigenous Groups ◽  
Math And Science

In this study, I examined academic achievement of immigrant children in the United States, Canada, England, Australia, and New Zealand. Analyzing data from the Third International Mathematics and Science Study (TIMSS), I gauged the performance gaps relating to the generation of immigration and the home language background. I found immigrant children's math and science achievement to be lower than the others only in England, the U.S., and Canada. Non-English language background was found in each country to relate to poor math and science learning and this disadvantage was stronger among native-born children—presumably children of indigenous groups—than among immigrant children. I also examined the school variation in math performance gaps, using hierarchical linear modeling (HLM) to each country's data. The patterns in which language- and generation-related math achievement gaps varied between schools are different in the five countries.

scholarly journals A Partial Simulation Study of Phantom Effects in Multilevel Analysis of School Effects: The Case of School Socioeconomic Composition

2021 ◽  
pp. 004912412098619
Author(s):  
Hao Zhou ◽  
Xin Ma
Keyword(s):  
Academic Achievement ◽  
Hierarchical Linear Modeling ◽  
Science Achievement ◽  
International Student ◽  
Student Assessment ◽  
The United States ◽  
Linear Modeling ◽  
Real World Data ◽  
International Student Assessment ◽  
School Ses

Hierarchical linear modeling (HLM) is often used to estimate the effects of socioeconomic status (SES) on academic achievement at different levels of an educational system. However, if a prior academic achievement measure is missing in a HLM model, biased estimates may occur on the effects of student SES and school SES. Phantom effects describe the phenomenon in which the effects of student SES and school SES disappear once prior academic achievement is added to the model. In the present analysis, partial simulation (i.e., simulated data are used together with real-world data) was employed to examine the phantom effects of student SES and school SES on science achievement, using the national sample of the United States from the 2015 Programme for International Student Assessment. The results showed that the phantom effects of student SES and school SES are rather real. The stronger the correlation between prior science achievement and (present) science achievement, the greater the chance that the phantom effects occur.

A Novel Intervention for System-Involved Intimate Partner Violence Survivors: Changes in Parenting

2017 ◽  
Vol 29 (3) ◽  
pp. 268-280
Author(s):  
Christopher J. Wretman ◽  
Cynthia Fraga Rizo ◽  
Rebecca J. Macy ◽  
Shenyang Guo ◽  
Dania Ermentrout
Keyword(s):  
Intimate Partner Violence ◽  
Hierarchical Linear Modeling ◽  
Partner Violence ◽  
Parenting Practices ◽  
The United States ◽  
Preliminary Evidence ◽  
Intimate Partner ◽  
Future Research ◽  
Court System ◽  
Linear Modeling

Purpose: A growing subpopulation of intimate partner violence (IPV) victims comprises mothers who have been mandated to services by either the court system or child protective services (CPS). Two human service agencies in the United States developed a 13-week novel intervention to address these women. All participants were assigned to the intervention, which featured group psychoeducation sessions, social events, and childcare. Method: This quasi-experimental study gathered preliminary evidence regarding whether the intervention promoted participants’ ( N = 70) parenting practices. Specifically, growth curve analyses using hierarchical linear modeling examined outcomes at completion (3 months) and follow-up (6 months). Results: Participants reported statistically significant improvements on key parenting practices at both postintervention time points. Conclusions: This study provides preliminary support for engaging court- and CPS-involved female IPV survivors in specialized, group-based interventions such as that investigated herein. Future research should investigate similar programs using larger samples and more robust designs.

scholarly journals The Effects of Performance Budgeting and Funding Programs on Graduation Rate in Public Four-Year Colleges and Universities

2004 ◽  
Vol 12 ◽  
pp. 22 ◽  
Author(s):  
Jung-cheol Shinn ◽  
Sande Milton
Keyword(s):  
Graduation Rates ◽  
Hierarchical Linear Modeling ◽  
Graduation Rate ◽  
Program Effectiveness ◽  
The United States ◽  
Institutional Performance ◽  
Linear Modeling ◽  
Performance Budgeting ◽  
Funding Programs ◽  
Study Population

This study was conducted to determine whether states with performance budgeting and funding (PBF) programs had improved institutional performance of higher education over the five years (1997 through 2001) considered in this study. First Time in College (FTIC) graduation rate was used as the measure of institutional performance. In this study, the unit of analysis is institution level and the study population is all public four-or-more-year institutions in the United States. To test PBF program effectiveness, Hierarchical Linear Modeling (HLM) growth analysis was applied. According to the HLM analysis, the growth of graduation rates in states with PBF programs was not greater than in states without PBF programs. The lack of growth in institutional graduation rates, however, does not mean that PBF programs failed to achieve their goals. Policy-makers are advised to sustain PBF programs long enough until such programs bear their fruits or are proven ineffective.

A Multi-Level Examination of Organizational Context on Adult Probation Officer Attitudes Toward Evidence-Based Practice

2016 ◽  
Vol 62 (5) ◽  
pp. 1331-1356 ◽  
Author(s):  
Jill Viglione
Keyword(s):  
Organizational Climate ◽  
Hierarchical Linear Modeling ◽  
Organizational Context ◽  
The United States ◽  
Organizational Characteristics ◽  
Evidence Based ◽  
Linear Modeling ◽  
Adoption And Implementation ◽  
Using Data ◽  
Officer Attitudes

Currently, both researchers and criminal justice agencies recognize the need to consider evidence-based practices (EBPs) as means to provide effective supervision and reduce recidivism rates. Research documents the importance of organizational characteristics in relation to EBP adoption and implementation, including organizational climate, commitment to the organization, and cynicism for change. Using data collected through surveys of 251 probation staff nested within 12 probation agencies in the United States, the current study utilizes Hierarchical Linear Modeling to examine the association of these important organizational characteristics with probation staff reported attitudes toward EBPs. These findings are critical for understanding how probation staff perceptions relate to the transportability of EBPs and which/how contextual factors influence attitudes toward best practices.

The Relationship Between Reciprocal School-to-School Collaboration and Student Academic Achievement

2021 ◽  
pp. 174114322110644
Author(s):  
Huang Wu ◽  
Jianping Shen ◽  
Patricia Reeves ◽  
Yunzheng Zheng ◽  
Lisa Ryan ◽  
...  
Keyword(s):  
Hierarchical Linear Modeling ◽  
The United States ◽  
School Outcomes ◽  
Student Academic Achievement ◽  
Linear Modeling ◽  
Collaborative Relationships ◽  
Reciprocal Relationships ◽  
Proficiency Level ◽  
School Collaboration ◽  
The Relationship

Despite the appeal of promoting and forming collaborative relationships between schools, empirical evidence for an association between school-to-school collaboration and school outcomes is still somewhat lacking. This study utilized data from 76 schools nested within 56 districts in the United States to examine the association between a school's reciprocal relationships and school outcomes by employing social network analysis and hierarchical linear modeling (HLM). After controlling for school and district demographic characteristics, we found the indices of reciprocal collaboration are associated with the school's 2018 student proficiency level in both math and reading and the growth in proficiency level between 2017 and 2018. The implications and limitations were discussed.

Opportunity to Learn: The Impacts and Policy Implications

1998 ◽  
Vol 20 (3) ◽  
pp. 137-156 ◽  
Author(s):  
Jia Wang
Keyword(s):  
Public Schools ◽  
Los Angeles ◽  
Hierarchical Linear Modeling ◽  
Test Scores ◽  
Science Achievement ◽  
Opportunity To Learn ◽  
Policy Implications ◽  
Linear Modeling ◽  
Hands On ◽  
Written Test

This study investigated the relationship between students’ opportunity to learn (OIL) and their science achievement. The data are of 623 8th-graders enrolled in five public schools in Los Angeles, California. Hierarchical linear modeling was used to analyze OTL variables at two levels of instructional processes: the classroom level and the student level. Students’ science test scores are based on a written test and a hands-on test. OTL effects on these two test scores were studied to see whether the effects differ depending on how science achievement is measured. It was found that OTL variables were significant predictors of both written and hands-on test scores even after students’ general ability level, ethnicity, and gender were controlled. The OTL effects varied by test format (written test and hands-on test). Content exposure was the most significant predictor of students’ written test scores, and quality of instructional delivery was the most significant predictor of the hands-on test scores. In conclusion, OTL variables are not unitary constructs; they are multidimensional, and different dimensions of OTL should be measured simultaneously to properly document the OTL-achievement relation.

Relative and Absolute Deprivation’s Relationship With Violent Crime in the United States: Testing an Interaction Effect Between Income Inequality and Disadvantage

2017 ◽  
Vol 64 (4) ◽  
pp. 542-560 ◽  
Author(s):  
Bert Burraston ◽  
James C. McCutcheon ◽  
Stephen J. Watts
Keyword(s):  
Income Inequality ◽  
Violent Crime ◽  
Hierarchical Linear Modeling ◽  
Interaction Effect ◽  
Significant Interaction ◽  
Regression Models ◽  
Relative Deprivation ◽  
The United States ◽  
Linear Modeling ◽  
Using Data

Relative deprivation and absolute deprivation both have effects on crime. Although these two concepts are often treated as separate, some scholarship has suggested that the two may be complementary. The current study assesses whether the effects of relative and absolute deprivation interact statistically in their effect on violent crime by testing an interaction effect between income inequality and disadvantage. Using data from U.S. counties, hierarchical linear modeling (HLM) regression models show that there is a significant interaction between relative and absolute deprivation predicting violent crime rates. The plot of this interaction shows that when absolute deprivation is high, there is less violence in high inequality counties than in counties with medium levels of inequality. The implication of this finding is discussed.

Sign in / Sign up

Export Citation Format

Share Document