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Showing 1 to 15 of 41 results Save | Export
Lily An; Zach Branson; Luke Miratrix – Annenberg Institute for School Reform at Brown University, 2024
Sometimes a treatment, such as receiving a high school diploma, is assigned to students if their scores on two inputs (e.g., math and English test scores) are above established cutoffs. This forms a multidimensional regression discontinuity design (RDD) to analyze the effect of the educational treatment where there are two running variables…
Descriptors: Hierarchical Linear Modeling, English Language Learners, English (Second Language), Second Language Learning
Neba Afanwi Nfonsang – ProQuest LLC, 2022
This study used a propensity score approach to estimate treatment effects in a multilevel setting. The propensity score approach involves the estimation of propensity scores for covariate balancing and the estimation of treatment effects. This study aimed at understanding how propensity scores estimated through a simple logistic regression compare…
Descriptors: Hierarchical Linear Modeling, Scores, High School Students, Grade 10
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Forrow, Lauren; Starling, Jennifer; Gill, Brian – Regional Educational Laboratory Mid-Atlantic, 2023
The Every Student Succeeds Act requires states to identify schools with low-performing student subgroups for Targeted Support and Improvement or Additional Targeted Support and Improvement. Random differences between students' true abilities and their test scores, also called measurement error, reduce the statistical reliability of the performance…
Descriptors: At Risk Students, Low Achievement, Error of Measurement, Measurement Techniques
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Regional Educational Laboratory Mid-Atlantic, 2023
This Snapshot highlights key findings from a study that used Bayesian stabilization to improve the reliability (long-term stability) of subgroup proficiency measures that the Pennsylvania Department of Education (PDE) uses to identify schools for Targeted Support and Improvement (TSI) or Additional Targeted Support and Improvement (ATSI). The…
Descriptors: At Risk Students, Low Achievement, Error of Measurement, Measurement Techniques
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Regional Educational Laboratory Mid-Atlantic, 2023
The "Stabilizing Subgroup Proficiency Results to Improve the Identification of Low-Performing Schools" study used Bayesian stabilization to improve the reliability (long-term stability) of subgroup proficiency measures that the Pennsylvania Department of Education (PDE) uses to identify schools for Targeted Support and Improvement (TSI)…
Descriptors: At Risk Students, Low Achievement, Error of Measurement, Measurement Techniques
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Bicer, Ali; Capraro, Robert M.; Capraro, Mary M. – International Journal of Mathematical Education in Science and Technology, 2018
The purpose of this paper is to demonstrate Hispanic students' mathematics achievement growth rate in Inclusive science, technology, engineering, and mathematics (STEM) high schools compared to Hispanic students' mathematics achievement growth rate in traditional public schools. Twenty-eight schools, 14 of which were Texas STEM (T-STEM) academies…
Descriptors: Hispanic American Students, STEM Education, Mathematics Achievement, Achievement Gains
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Townsend, Lisa; Musci, Rashelle; Stuart, Elizabeth; Ruble, Anne; Beaudry, Mary B.; Schweizer, Barbara; Owen, Megan; Goode, Carly; Johnson, Sarah L.; Bradshaw, Catherine; Wilcox, Holly; Swartz, Karen – Journal of School Health, 2017
Background: Although school climate is linked with youth educational, socioemotional, behavioral, and health outcomes, there has been limited research on the association between school climate and mental health education efforts. We explored whether school climate was associated with students' depression literacy and mental health stigma beliefs.…
Descriptors: Educational Environment, Depression (Psychology), Mental Health, Social Bias
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Allen, Jeff – Applied Measurement in Education, 2017
Using a sample of schools testing annually in grades 9-11 with a vertically linked series of assessments, a latent growth curve model is used to model test scores with student intercepts and slopes nested within school. Missed assessments can occur because of student mobility, student dropout, absenteeism, and other reasons. Missing data…
Descriptors: Achievement Gains, Academic Achievement, Growth Models, Scores
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Powers, Jeanne M.; Pivovarova, Margarita – Educational Policy, 2017
The 2016 Presidential election and the first months of the Trump administration have propelled immigration to the center of U.S. political debates. We use data from the Programme for International Student Assessment (PISA) 2012 to provide insights into the school experiences of high school-age immigrants and their U.S.-born peers. Our findings…
Descriptors: Immigrants, Academic Achievement, International Assessment, High School Students
McVey, Jill E. – ProQuest LLC, 2016
This study examined the development of noncognitive skills in a sample of 4,769 Hispanic/Latino students as they went through middle school and the first year of high school using ACT Engage 6-9, an assessment designed to predict student outcomes by measuring students' behaviors and psychosocial attributes. The scales of Academic Discipline,…
Descriptors: Middle School Students, Hispanic American Students, Student Development, High School Freshmen
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Westine, Carl D. – American Journal of Evaluation, 2016
Little is known empirically about intraclass correlations (ICCs) for multisite cluster randomized trial (MSCRT) designs, particularly in science education. In this study, ICCs suitable for science achievement studies using a three-level (students in schools in districts) MSCRT design that block on district are estimated and examined. Estimates of…
Descriptors: Efficiency, Evaluation Methods, Science Achievement, Correlation
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Weston, Jennifer L.; McNamara, Danielle S. – Grantee Submission, 2013
Intelligent tutoring systems yield data with many properties that render it potentially ideal to examine using multi-level models (MLM). Repeated observations with dependencies may be optimally examined using MLM because it can account for deviations from normality. This paper examines the applicability of MLM to data from the intelligent tutoring…
Descriptors: Intelligent Tutoring Systems, Hierarchical Linear Modeling, Correlation, Writing Instruction
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Pazzaglia, Angela M.; Clements, Margaret; Lavigne, Heather J.; Stafford, Erin T. – Regional Educational Laboratory Midwest, 2016
This study used administrative data from Wisconsin Virtual School to identify patterns of student engagement in online courses (defined as the amount of time students were logged in to their course each week and how this varied over time). The study also examined whether the patterns were associated with course outcomes (defined as the percentage…
Descriptors: Learner Engagement, Online Courses, Outcomes of Education, Virtual Classrooms
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Güvendir, Emre – Education Research and Perspectives, 2015
This study examines how student and school characteristics are related to Turkish students' English language achievement in Evaluation of Student Achievement Test (ÖBBS) of 2009. The participants of the study involve 43707 ninth year students who were required to take ÖBBS in 2009. For data analysis two level hierarchical linear modeling was…
Descriptors: Student Characteristics, Institutional Characteristics, English (Second Language), Language Skills
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West, John; Miller, Mary Lou; Myers, Jim; Norton, Timothy – Administrative Issues Journal: Connecting Education, Practice, and Research, 2015
Purpose, Scope, and Method of Study: The purpose of this study was to determine if a correlation exists between grade span for ninth grade and gains in math achievement test scores in 10th grade and 12th grade. A quantitative, longitudinal, correlational research design was employed to investigate the research questions. The population was high…
Descriptors: High School Students, Grade 9, Mathematics Achievement, Grouping (Instructional Purposes)
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