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No Child Left Behind Act 20011
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Margaret K. Wallace; Jason Jabbari; Yung Chun; Takeshi Terada; Somalis Chy – Annenberg Institute for School Reform at Brown University, 2025
Student mobility that occurs within a school year may be especially disruptive for student outcomes, yet little is known regarding the predictors of within-year mobility. In particular, research has yet to comprehensively examine the role of student achievement in predicting within-year student mobility. Thus, we sought to understand this link by…
Descriptors: Elementary School Students, Middle School Students, Student Mobility, Mathematics Achievement
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Ethan R. Van Norman; Emily R. Forcht – Journal of Education for Students Placed at Risk, 2024
This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…
Descriptors: Data Collection, Predictive Measurement, Predictive Validity, Predictor Variables
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Jaylin Lowe; Charlotte Z. Mann; Jiaying Wang; Adam Sales; Johann A. Gagnon-Bartsch – Grantee Submission, 2024
Recent methods have sought to improve precision in randomized controlled trials (RCTs) by utilizing data from large observational datasets for covariate adjustment. For example, consider an RCT aimed at evaluating a new algebra curriculum, in which a few dozen schools are randomly assigned to treatment (new curriculum) or control (standard…
Descriptors: Randomized Controlled Trials, Middle School Mathematics, Middle School Students, Middle Schools
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Baker, Ryan S.; Berning, Andrew W.; Gowda, Sujith M.; Zhang, Shizhu; Hawn, Aaron – Journal of Education for Students Placed at Risk, 2020
Dropout remains a persistent challenge within high school education. In this paper, we present a case study on automatically detecting whether a student is at-risk of dropout within a diverse school district in Texas. We predict whether a student will drop out in a future school year from data on students' discipline, attendance, course-taking,…
Descriptors: At Risk Students, High School Students, Dropout Prevention, Student Diversity
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West, Stephen G.; Hughes, Jan N.; Kim, Han Joe; Bauer, Shelby S. – Educational Measurement: Issues and Practice, 2019
The Motivation for Educational Attainment (MEA) questionnaire, developed to assess facets related to early adolescents' motivation to complete high school, has a bifactor structure with a large general factor and three smaller orthogonal specific factors (teacher expectations, peer aspirations, value of education). This prospective validity study…
Descriptors: Student Motivation, Educational Attainment, Questionnaires, Adolescent Attitudes
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Berlin, Noémi; Tavani, Jean-Louis; Beasançon, Maud – Education Economics, 2016
We investigate the link between schooling achievement and creativity scores, controlling for personality traits and other individual characteristics. Our study is based on field data collected in a secondary school situated in a Parisian suburb. Four scores of creativity were measured on 9th graders. Verbal divergent thinking negatively predicts…
Descriptors: Creativity, Academic Achievement, Scores, Personality Traits
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Weybright, Elizabeth H.; Caldwell, Linda L.; Xie, Hui; Wegner, Lisa; Smith, Edward A. – South African Journal of Education, 2017
Education is one of the strongest predictors of health worldwide. In South Africa, school dropout is a crisis where by Grade 12, only 52% of the age appropriate population remain enrolled. Survival analysis was used to identify the risk of dropping out of secondary school for male and female adolescents and examine the influence of substance use…
Descriptors: Foreign Countries, Predictor Variables, Predictive Measurement, Secondary School Students
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Peters, S. Colby; Woolley, Michael E. – Children & Schools, 2015
Data from the School Success Profile generated by 19,228 middle and high school students were organized into three broad categories of risk and protective factors--control, support, and challenge--to examine the relative and combined power of aggregate scale scores in each category so as to predict academic success. It was hypothesized that higher…
Descriptors: Academic Achievement, Success, Risk, Risk Assessment
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Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – Grantee Submission, 2015
Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning
Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – International Educational Data Mining Society, 2015
Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning
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Daley, Samantha G.; Willett, John B.; Fischer, Kurt W. – Journal of Educational Psychology, 2014
This study investigated the relationship between emotional responses and reading performance in middle-school students. Although a large number of prior studies have investigated the relationship between emotion and reading, those studies have concentrated primarily on relatively static and distal measures of emotion. In this research, we measured…
Descriptors: Reading Comprehension, Emotional Response, Middle School Students, Grade 7
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Schwartz, Sandra – Contributions to Music Education, 2013
Vocal demands of teaching are considerable and these challenges are greater for choral directors who depend on the voice as a musical and instructive instrument. The purpose of this study was to (1) examine choral directors' vocal condition using a modified Voice Handicap Index (VHI), and (2) determine the extent to which the major variables…
Descriptors: Predictor Variables, Music Activities, Music Education, Music Teachers
Tindal, Gerald; Nese, Joseph F.; Alonzo, Julie – Behavioral Research and Teaching, 2009
In this technical report, data are presented on the predictive and concurrent relation between various student demographic variables (gender, race/ethnicity, special education status, Title 1 status, English language learning status, and economic disadvantage) and three reading easyCBMs (passage reading fluency, vocabulary, and multiple-choice…
Descriptors: Evidence, Reading Fluency, Academic Achievement, Research Reports
Ikegulu, T. Nelson – Online Submission, 2004
Background: The overall goal of the No Child Left Behind Act (NCLB) of 2001 is to close, by the end of the 2013-2014 academic year, "the achievement gap between high- and low- performing students, especially the achievement gap between minority and non-minority students and, between disadvantaged children and their more advantaged peers"…
Descriptors: High Schools, Ethnicity, Middle Schools, Equal Education