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.

Kindergarteners’ Achievement on Geometry and Measurement Units That Incorporate a Gifted Education Approach

2016 ◽  
Vol 61 (1) ◽  
pp. 52-72 ◽  
Author(s):  
Tutita M. Casa ◽  
Janine M. Firmender ◽  
M. Katherine Gavin ◽  
Susan R. Carroll
Keyword(s):  
Hierarchical Linear Modeling ◽  
Gifted Education ◽  
Mathematics Curriculum ◽  
Intervention Group ◽  
Opportunity To Learn ◽  
Response Assessment ◽  
Linear Modeling ◽  
Primary Level ◽  
Comparison Groups ◽  
Measurement Units

This research responds to the call by early childhood educators advocating for more challenging mathematics curriculum at the primary level. The kindergarten Project M2 units focus on challenging geometry and measurement concepts by positioning students as practicing mathematicians. The research reported herein highlights the features of the kindergarten units and reports on student achievement, including the differences between the intervention and comparison groups. Hierarchical linear modeling results indicate that students in the intervention group ( n = 210) outperformed those in the comparison group ( n = 196) on the Iowa Tests of Basic Skills Mathematics subscale ( p < .01; d = 0.25), and an open-response assessment ( p < .001; d = 2.68) encompassing performance-based, verbal, and written components. These results suggest that kindergarteners can achieve at high levels of mathematical understanding when given the opportunity to learn from more challenging curriculum.

Raising Math Scores among Children in Low-Wealth Households: Potential Benefit of Children’s School Savings

2014 ◽  
Author(s):  
O.F. Hamouda
Keyword(s):  
Hierarchical Linear Modeling ◽  
Potential Benefit ◽  
Household Wealth ◽  
Policy Implications ◽  
Linear Modeling ◽  
Regression Methods ◽  
Math Scores ◽  
The Relationship

Recent findings using traditional regression methods show that children’s school savings is associated with higher math scores. We build on this research by using hierarchical linear modeling (HLM). Moreover, we suggest children’s school savings may have a stronger association with children’s math scores than either household wealth or children’s savings that is not designated for school. We find children with school savings have higher math scores than those without school savings. Further, we find evidence that children’s school savings mediates the relationship between household wealth and math scores. Policy implications for children living in low-wealth households discussed.

Curriculum and Implementation Effects on High School Students' Mathematics Learning From Curricula Representing Subject-Specific and Integrated Content Organizations

2013 ◽  
Vol 44 (2) ◽  
pp. 416-463 ◽  
Author(s):  
Douglas A. Grouws ◽  
James E. Tarr ◽  
Óscar Chávez ◽  
Ruthmae Sears ◽  
Victor M. Soria ◽  
...  
Keyword(s):  
High School ◽  
High School Students ◽  
Hierarchical Linear Modeling ◽  
Integrated Curriculum ◽  
Mathematics Learning ◽  
Opportunity To Learn ◽  
Teaching Experience ◽  
Linear Modeling ◽  
School Students ◽  
Subject Specific

This study examined the effect of 2 types of mathematics content organization on high school students' mathematics learning while taking account of curriculum implementation and student prior achievement. The study involved 2,161 students in 10 schools in 5 states. Within each school, approximately 1/2 of the students studied from an integrated curriculum (Course 1) and 1/2 studied from a subject-specific curriculum (Algebra 1). Hierarchical linear modeling with 3 levels showed that students who studied from the integrated curriculum were significantly advantaged over students who studied from a subject-specific curriculum on 3 end-of-year outcome measures: Test of Common Objectives, Problem Solving and Reasoning Test, and a standardized achievement test. Opportunity to learn and teaching experience were significant moderating factors.

Children's Active Engagement in Public School Language Therapy Relates to Greater Gains

2020 ◽  
Vol 29 (3) ◽  
pp. 1505-1513
Author(s):  
Mary Beth Schmitt
Keyword(s):  
Public Schools ◽  
Hierarchical Linear Modeling ◽  
Language Impairment ◽  
Active Engagement ◽  
Linear Modeling ◽  
Language Therapy ◽  
Significant Component ◽  
Usual Therapy ◽  
Business As Usual ◽  
Therapy Sessions

Purpose The current study examined children's engagement as an active ingredient of language therapy in public schools and considered the potential interplay between engagement and dose on outcomes. Method Participants included 135 children with language impairment receiving business-as-usual therapy from 70 speech-language pathologists. Two videotaped therapy sessions from each participating child were coded for children's level of engagement and time in language-focused therapy (dose). Results Hierarchical linear modeling was used for analyses; children's level of engagement (i.e., active engagement) was significantly, positively related to children's language gain and was not moderated by dose. Conclusion Findings suggest that children's active participation in therapy sessions is a significant component to effective language therapy and underscores the need for further research.

scholarly journals Charter Schools and Mathematics Achievement in the State of Georgia

2017 ◽  
Vol 7 (1) ◽  
pp. 96
Author(s):  
Raymond D. Mooring
Keyword(s):  
Public Schools ◽  
Charter Schools ◽  
Charter School ◽  
Hierarchical Linear Modeling ◽  
Math Achievement ◽  
Analysis Of Covariance ◽  
Linear Modeling ◽  
Traditional Public Schools ◽  
And Gender ◽  
And Mathematics

This study uses hierarchical linear modeling (HLM) and factorial analysis of covariance (ANCOVA) to investigate the relationship between a school’s charter status and Math achievement. After accounting for school gender and ethnicity effects, charter school status is associated with Math achievement. Specifically, the initial status of Math achievement varies depending on ethnicity and gender, but the growth rate does not. Furthermore, district characteristics help to explain the charter school effect on Math achievement. Charter schools outperform traditional public schools when they receive an average amount of instructional funds. To this end, the charter gap in Math achievement decreases over time in districts that spend on instruction and have a substantial amount of minorities. When compared to traditional public schools with similar characteristics, charter schools with high percentages of Black students and/or low percentages of females outperformed their matched traditional public school counterparts. 

Cannabis Prevalence and National Drug Policy in 27 Countries: An Analysis of Adolescent Substance Use

2018 ◽  
Vol 63 (7) ◽  
pp. 1082-1099 ◽  
Author(s):  
Marijana M. Kotlaja ◽  
Jennifer V. Carson
Keyword(s):  
Hierarchical Linear Modeling ◽  
Rational Choice Theory ◽  
Choice Theory ◽  
Control Policy ◽  
Policy Implications ◽  
Self Report ◽  
Prevalence Rates ◽  
Linear Modeling ◽  
Country Level ◽  
Cannabis Policy

Prior research that assesses the relationship between cannabis policy and prevalence rates has yielded mixed results, perhaps due to the varying rigor of these investigations. Addressing some of these issues in rigor and informed by a rational choice theory (RCT), we hypothesize that those policies on the more punitive end of McDonald and colleagues’ classification will be most effective. Examining legislation in 27 countries utilizing the Second International Self-Report Delinquency Study (ISRD-2) through hierarchical linear modeling (HLM) models with both individual- and country-level controls, we find little support for these hypotheses. Instead, results from our analysis largely indicate that the variation in country prevalence rates from 2005 to 2007 was not significantly related to cannabis control policy. We comment on possible policy implications for these preliminary results.

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.

Using Hierarchical Linear Modeling to Examine How Individual SLPs Differentially Contribute to Children's Language and Literacy Gains in Public Schools

2015 ◽  
Vol 24 (3) ◽  
pp. 504-516 ◽  
Author(s):  
Kelly Farquharson ◽  
Sherine R. Tambyraja ◽  
Jessica Logan ◽  
Laura M. Justice ◽  
Mary Beth Schmitt
Keyword(s):  
Public Schools ◽  
Hierarchical Linear Modeling ◽  
Language Impairment ◽  
Language Intervention ◽  
Language And Literacy ◽  
Linear Modeling ◽  
Word Decoding ◽  
School Based ◽  
The Individual ◽  
Academic Year

Purpose The purpose of this study was twofold: (a) to determine the unique contributions in children's language and literacy gains, over 1 academic year, that are attributable to the individual speech-language pathologist (SLP) and (b) to explore possible child- and SLP-level factors that may further explain SLPs' contributions to children's language and literacy gains. Method Participants were 288 kindergarten and 1st-grade children with language impairment who were currently receiving school-based language intervention from SLPs. Using hierarchical linear modeling, we partitioned the variance in children's gains in language (i.e., grammar, vocabulary) and literacy (i.e., word decoding) that could be attributed to their individual SLP. Results Results revealed a significant contribution of individual SLPs to children's gains in grammar, vocabulary, and word decoding. Children's fall language scores and grade were significant predictors of SLPs' contributions, although no SLP-level predictors were significant. Conclusions The present study makes a first step toward incorporating implementation science and suggests that, for children receiving school-based language intervention, variance in child language and literacy gains in an academic year is at least partially attributable to SLPs. Continued work in this area should examine the possible SLP-level characteristics that may further explicate the relative contributions of SLPs.

Raising Math Scores Among Children in Low-Wealth Households: Potential Benefit of Children's School Savings

2011 ◽  
Author(s):  
William Elliott III ◽  
Hyunzee Jung ◽  
Terri Friedline
Keyword(s):  
Hierarchical Linear Modeling ◽  
Potential Benefit ◽  
Household Wealth ◽  
Policy Implications ◽  
Linear Modeling ◽  
Regression Methods ◽  
Math Scores ◽  
The Relationship

Recent findings using traditional regression methods show that children's savings designated for school are associated with higher math scores. We build on this research by using Hierarchical Linear Modeling (HLM) to confirm that children with school savings have higher math scores than those without school savings. Moreover, we suggest children's school savings may have a stronger association with children's math scores than with either household wealth or children's savings not designated for school. Further, we find evidence that children's school savings mediates the relationship between household wealth and math scores. Policy implications for children living in low-wealth households are discussed.

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