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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
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Ivcevic, Zorana; Hoffmann, Jessica D. – Journal of Creative Behavior, 2022
In a sample of high school students (preliminary study: N = 224; main study: N = 235 and 194 at two time points in the beginning and the end of the school year), we developed and tested a self-report measure of attitudes toward creativity. Exploratory factor analyses identified and replicated one factor of positive attitudes toward…
Descriptors: Creativity, High School Students, Student Attitudes, Value Judgment
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Thompson, Aaron M.; Huang, Francis; Smith, Tyler; Reinke, Wendy M.; Herman, Keith C. – School Mental Health, 2021
The purpose of this paper is to confirm the factor structure, examine the invariance, and investigate the predictive validity using disciplinary data for 5262 high school students who completed the Early Identification System--Student Response (EIS-SR). The development and theory of the EIS-SR is discussed along with prior work. Building off of…
Descriptors: Factor Structure, Factor Analysis, Predictive Validity, Identification
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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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da Cunha Moreira, Thaline; Ambiel, Rodolfo A. M. – International Journal for Educational and Vocational Guidance, 2018
This study aimed to test a theoretical model of self-efficacy applied to the context of professional choice, verifying the sources of self-efficacy as predictors of self-efficacy beliefs and self-efficacy beliefs as antecedents of vocational exploratory behavior. A total of 388 high school students from public and private schools in the state of…
Descriptors: Foreign Countries, Self Efficacy, Career Choice, Predictor Variables
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Alkushi, Abdulmohsen; Althewini, Abdulaziz – International Education Studies, 2020
Admission criteria can be used to predict Saudi student performance in college, but significant differences across several studies exists. This study explores the predictive power of admission criteria for college assignment using King Saud bin Abdulaziz University for Health Sciences as a model. Scores from high school and standardized tests were…
Descriptors: Predictive Validity, Admission Criteria, College Admission, Grades (Scholastic)
Holzman, Brian; Duffy, Horace – Houston Education Research Consortium, 2020
Part II of the Houston Longitudinal Study on the Transition to College and Work (HLS) examined potential indicators of college enrollment school and district staff might use to identify and support students at risk of not attending college. The study used administrative data from the Houston Independent School District (HISD) and tracked two…
Descriptors: Enrollment, At Risk Students, Urban Schools, Predictor Variables
Holzman, Brian; Duffy, Horace – Houston Education Research Consortium, 2020
This report examined three potential indicators of college enrollment school and district staff might use to identify and support students at risk of not attending college: (1) Chicago: Designed to predict high school graduation; based on earning six course credits--the minimum to advance to the next grade in HISD--and having at most one semester…
Descriptors: Enrollment, At Risk Students, Urban Schools, Predictor Variables
Holzman, Brian; Duffy, Horace – Houston Education Research Consortium, 2020
These are the appendices for "Transitioning to College and Work. Part 2: A Study of Potential Enrollment Indicators," which examined potential indicators of college enrollment school and district staff might use to identify and support students at risk of not attending college. The study used administrative data from the Houston…
Descriptors: Enrollment, At Risk Students, Urban Schools, Predictor Variables
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Kostal, Jack W.; Sackett, Paul R.; Kuncel, Nathan R.; Walmsley, Philip T.; Stemig, Melissa S. – Educational Measurement: Issues and Practice, 2017
Previous research has established that SAT scores and high school grade point average (HSGPA) differ in their predictive power and in the size of mean differences across racial/ethnic groups. However, the SAT is scaled nationally across all test takers while HSGPA is scaled locally within a school. In this study, the researchers propose that this…
Descriptors: College Entrance Examinations, Scaling, Grade Point Average, Differences
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Garcia, Narciso; Jones, Don; Challoo, Linda; Mundy, Marie-Anne; Isaacson, Carrie – Research in Higher Education Journal, 2018
This mixed methods study involved a two phase analysis of how Early College High Schools influence students who graduate with <19 college credit hours, 20-39 college credit hours, or >40 college credit hours in obtaining a Bachelor's Degree. The research incorporated an explanatory sequential mixed methods design that involved collecting…
Descriptors: High School Students, College Bound Students, Academic Persistence, Mixed Methods Research
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Cimen, Osman; Yilmaz, Mehmet – International Electronic Journal of Environmental Education, 2016
This study aims to determine the variables that predict high school students' recycling behaviors. The study was designed as survey model. The study's sample consists of 203 students at a high school in Ankara. A recycling behavior scale developed by the researchers was used as a data collection tool. The scale has 3 dimensions: recycling…
Descriptors: Predictor Variables, High School Students, Recycling, Student Behavior
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Burnes, Jennifer J.; Martin, James E.; Terry, Robert; McConnell, Amber E.; Hennessey, Maeghan N. – Career Development and Transition for Exceptional Individuals, 2018
We conducted an exploratory study to investigate the relation between nonacademic behavior constructs measured by the "Transition Assessment and Goal Generator" (TAGG) and postsecondary education and employment outcomes for 297 high school leavers who completed the TAGG during their high school years. Four of eight TAGG constructs…
Descriptors: Correlation, Postsecondary Education, Educational Attainment, Employment Level
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Aydin, Solmaz – Journal of Education and Training Studies, 2016
This study aimed to analyze the relationship between high school students' self-efficacy perceptions regarding biology, the metacognitive strategies they use in this course and their academic motivation for learn biology. The sample of the study included 286 high school students enrolled in three high schools who attended a biology course in Kars,…
Descriptors: Self Efficacy, Metacognition, High School Students, Biology
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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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