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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
Jeremiah T. Stark – ProQuest LLC, 2024
This study highlights the role and importance of advanced, machine learning-driven predictive models in enhancing the accuracy and timeliness of identifying students at-risk of negative academic outcomes in data-driven Early Warning Systems (EWS). K-12 school districts have, at best, 13 years to prepare students for adulthood and success. They…
Descriptors: High School Students, Graduation Rate, Predictor Variables, Predictive Validity
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
Yamamoto, Scott H.; Alverson, Charlotte Y. – Autism & Developmental Language Impairments, 2022
Background and Aims: The fastest growing group of students with disabilities are those with Autism Spectrum Disorder (ASD). States annually report on post-high school outcomes (PSO) of exited students. This study sought to fill two gaps in the literature related to PSO for exited high-school students with ASD and the use of state data and…
Descriptors: Autism Spectrum Disorders, Students with Disabilities, High School Graduates, Outcomes of Education
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
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
Austin, Bruce; French, Brian; Adesope, Olusola; Gotch, Chad – Journal of Experimental Education, 2017
Measures of variability are successfully used in predictive modeling in research areas outside of education. This study examined how standard deviations can be used to address research questions not easily addressed using traditional measures such as group means based on index variables. Student survey data were obtained from the Organisation for…
Descriptors: Predictor Variables, Models, Predictive Measurement, Statistical Analysis
Leckie, George; Goldstein, Harvey – British Educational Research Journal, 2017
Since 1992, the UK Government has published so-called "school league tables" summarising the average General Certificate of Secondary Education (GCSE) "attainment" and "progress" made by pupils in each state-funded secondary school in England. While the headline measure of school attainment has remained the percentage…
Descriptors: Foreign Countries, Achievement Rating, Academic Achievement, Secondary School Students
Alkharusi, Hussain – Electronic Journal of Research in Educational Psychology, 2016
Introduction: Students are daily exposed to a variety of assessment tasks in the classroom. It has long been recognized that students' perceptions of the assessment tasks may influence student academic achievement. The present study aimed at predicting academic achievement in mathematics from perceptions of the assessment tasks after controlling…
Descriptors: Academic Achievement, Predictive Measurement, Predictor Variables, Learning Strategies
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
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
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
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
Legewie, Joscha; DiPrete, Thomas A. – Sociology of Education, 2014
Despite the striking reversal of the gender gap in education, women pursue science, technology, engineering, and mathematics (STEM) degrees at much lower rates than those of their male peers. This study extends existing explanations for these gender differences and examines the role of the high school context for plans to major in STEM fields.…
Descriptors: High School Students, Gender Differences, Achievement Gap, Educational Environment
Northrop, Laura; Kelly, Sean – Urban Education, 2018
This study investigates whether adequate yearly progress (AYP) status, locale, and sector--common variables used to judge the quality of schools--accurately signal true differences in instructional practices in high school mathematics and science. Using data from the High School Longitudinal Study (HSLS), we find the school-to-school variation in…
Descriptors: Instructional Effectiveness, Intermode Differences, Federal Programs, Educational Indicators