scholarly journals Examining equity in an elementary school computer science intervention using component-based research

2021 ◽  
Vol 5 (1) ◽  
pp. 16-34
Author(s):  
Kaitlyn Ferris ◽  
Jeanne Century ◽  
Huifang Zuo
Keyword(s):  
Elementary School ◽  
Computer Science ◽  
Hierarchical Linear Modeling ◽  
Student Outcomes ◽  
The United States ◽  
Broward County ◽  
Linear Modeling ◽  
Demographic Groups ◽  
School Day ◽  
Quasi Experimental

This article reports on implementation of a problem-based learning intervention developed with the intention of finding time for computer science (CS) in the elementary school day. This study investigated differences in effects on students in particular socio-demographic groups using a quasi-experimental design. We first provide an overview of the perennial problem of group differences or “gaps” in student outcomes. Then we illustrate how, using component-based research (CBR), we moved beyond the question of whether the intervention worked, to focus on which parts of the intervention worked, for whom, and under what conditions. Using hierarchical linear modeling, this study draws from a sample of 16 elementary schools with 321 teachers and 5791 students in Broward County, Florida, the sixth largest school system in the United States. This study complements a previous paper (Authors, 2020), which examined associations between intervention components and student outcomes by investigating how outcomes differ for students in different socio-demographic groups and whether the presence of particular intervention components amplify or reduce differences. Through CBR, our work illustrates that CS interventions which may appear to benefit students overall, may be less beneficial or even detrimental to particular groups.

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.

Achievement Differences Between Students in Single-Sex Schools and Students in Coeducational Schools

2020 ◽  
pp. 317-337
Author(s):  
John K. Rugutt ◽  
Caroline C. Chemosit
Keyword(s):  
Computer Science ◽  
Hierarchical Linear Modeling ◽  
Teaching And Learning ◽  
Educational Experiences ◽  
Linear Modeling ◽  
Science Courses ◽  
Computer Science Courses ◽  
Single Sex ◽  
Teaching And Learning Environment ◽  
School Status

This study used hierarchical linear modeling (HLM) approach to investigate relationships between student achievement and single-sex school status with a sample of 57,041 students in 996 secondary schools in Kenya. An ANOVA was conducted to compare achievement levels of student enrolled in computer science courses and those who are not. The results showed that students enrolled in computer science courses achieved at a higher level whether in single-sex or coeducational schools. Students in single-sex schools achieved at a significantly higher level than those in co-education schools across all counties studied and across all subjects. The study concluded with a discussion of the importance of the study findings and call for the education stakeholders to be cognizant of the contribution the variables discussed in this study make to teaching and learning environment so that they are fully involved in providing the kinds of educational experiences that promote student learning.

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.

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.

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 From copper to steel: Police militarization at the end of the 20th century.

2016 ◽  
Author(s):  
Zach Baumgart
Keyword(s):  
Hierarchical Linear Modeling ◽  
Crime Control ◽  
Public Awareness ◽  
The United States ◽  
Three Dimensions ◽  
Linear Modeling ◽  
Working Paper ◽  
Military Equipment ◽  
Nationally Representative ◽  
Paper Abstract

WORKING PAPER. ABSTRACT: By 2016, ongoing police shootings of unarmed black men had increased public awareness of policing processes; chief among those was militarization. Prior researchers explored this relatively new process, but very few had systematically analyzed it. In this paper, I conceptualize, operationalize, and describe police militarization across the United States. I transformed publicly available data, the Law Enforcement and Administrative Statistics (LEMAS) dataset, into a panel of over 4,000 police departments over an eighteen-year period. I then constructed an index based on each of three dimensions of militarization: (1) increased stock of military equipment; (2) increased usage of paramilitary tactics; and (3) increased focus on military-style policing. I explain the indicators within each sub dimension, and describe their unique trend across time. Using both this Absolute LEMAS Militarization Index (ALMI) and a summary analysis of each indicator, I describe militarization between 1990 and 2007 using hierarchical linear modeling. Among key findings are three trends. First, I provide nationally representative evidence of an increasing trend in police militarization across most departments, despite statistical controls. I also found that larger departments were both more militarized and militarized faster over time than smaller departments. Finally, I found that diverse departments (either proportionately more women or more black officers) militarized at a slower rate over the period. This paper provides the theoretical and methodological basis for follow-up analyses of processes affecting militarization, including variations in crime control, organizational characteristics and racial dynamics.

scholarly journals Distancing the socially distanced: Racial/ethnic composition’s association with physical distancing in response to COVID-19 in the U.S.

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251960
Author(s):  
Joseph Gibbons
Keyword(s):  
Hierarchical Linear Modeling ◽  
The United States ◽  
Grocery Stores ◽  
Linear Modeling ◽  
Social Distancing ◽  
Healthy Behaviors ◽  
Mobility Data ◽  
Point Increase ◽  
Black Populations ◽  
Racial Ethnic

Social distancing prescribed by policy makers in response to COVID-19 raises important questions as to how effectively people of color can distance. Due to inequalities from residential segregation, Hispanic and Black populations have challenges in meeting health expectations. However, segregated neighborhoods also support the formation of social bonds that relate to healthy behaviors. We evaluate the question of non-White distancing using social mobility data from Google on three sites: workplaces, grocery stores, and recreational locations. Employing hierarchical linear modeling and geographically weighted regression, we find the relation of race/ethnicity to COVID-19 distancing is varied across the United States. The HLM models show that compared to Black populations, Hispanic populations overall more effectively distance from recreation sites and grocery stores: each point increase in percent Hispanic was related to residents being 0.092 percent less likely (p< 0.05) to visit recreational sites and 0.127 percent less likely (p< 0.01) to visit grocery stores since the onset of COVID-19. However, the GWR models show there are places where the percent Black is locally related to recreation distancing while percent Hispanic is not. Further, these models show the association of percent Black to recreation and grocery distancing can be locally as strong as 1.057 percent (p< 0.05) and 0.989 percent (p< 0.05), respectively. Next, the HLM models identified that Black/White residential isolation was related to less distancing, with each point of isolation residents were 11.476 percent more likely (p< 0.01) to go to recreational sites and 7.493 percent more likely (p< 0.05) to visit grocery stores compared to before COVID-19. These models did not find a measurable advantage/disadvantage for Black populations in these places compared to White populations. COVID-19 policy should not assume disadvantage in achieving social distancing accrue equally to different racial/ethnic minorities.

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