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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
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
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
Cratty, Dorothyjean – Economics of Education Review, 2012
Nineteen percent of 1997-98 North Carolina 3rd graders were observed to drop out of high school. A series of logits predict probabilities of dropping out on determinants such as math and reading test scores, absenteeism, suspension, and retention, at the following grade levels: 3rd, 5th, 8th, and 9th. The same cohort and variables are used to…
Descriptors: At Risk Students, Dropouts, High School Students, Probability
Flores, Raymond; Inan, Fethi; Lin, Zhangxi – Journal of Computers in Mathematics and Science Teaching, 2013
In this study, the National Educational Longitudinal Study (ELS:2002) dataset was used and a predictive data mining technique, decision tree analysis, was implemented in order to examine which factors, in conjunction to computer use, can be used to predict high or low probability of success in high school mathematics. Specifically, this study…
Descriptors: Educational Technology, Computer Uses in Education, Longitudinal Studies, Predictor Variables
Cawthon, Stephanie W.; Caemmerer, Jacqueline M.; Dickson, Duncan M.; Ocuto, Oscar L.; Ge, Jinjin; Bond, Mark P. – Applied Developmental Science, 2015
Social skills function as a vehicle by which we negotiate important relationships and navigate the transition from childhood into the educational and professional experiences of early adulthood. Yet, for individuals who are deaf, access to these opportunities may vary depending on their preferred language modality, family language use, and…
Descriptors: Predictor Variables, Prediction, Predictive Measurement, Predictive Validity
Onder, Fulya Cenkseven; Yilmaz, Yasin – Educational Sciences: Theory and Practice, 2012
The purpose of this study is to determine whether the parenting styles and life satisfaction predict delinquent behaviors frequently or not. Firstly the data were collected from 471 girls and 410 boys, a total of 881 high school students. Then the research was carried out with 502 students showing low (n = 262, 52.2%) and high level of delinquent…
Descriptors: High School Students, Measures (Individuals), Parenting Styles, Delinquency
Cheema, Jehanzeb R.; Zhang, Bo – International Journal of Education and Development using Information and Communication Technology, 2013
This study looked at the effect of both quantity and quality of computer use on achievement. The Program for International Student Assessment (PISA) 2003 student survey comprising of 4,356 students (boys, n = 2,129; girls, n = 2,227) was used to predict academic achievement from quantity and quality of computer use while controlling for…
Descriptors: Academic Achievement, Computer Use, Educational Quality, Incidence
Zwick, Rebecca; Himelfarb, Igor – Journal of Educational Measurement, 2011
Research has often found that, when high school grades and SAT scores are used to predict first-year college grade-point average (FGPA) via regression analysis, African-American and Latino students, are, on average, predicted to earn higher FGPAs than they actually do. Under various plausible models, this phenomenon can be explained in terms of…
Descriptors: Socioeconomic Status, Grades (Scholastic), Error of Measurement, White Students
Lemon, Jan Cummins – ProQuest LLC, 2010
High school dropout continues to be an issue of national concern, and the inability of educators and researchers to find means of effectively reducing the dropout rate may be grounded in their approach to understanding this issue. Because there is limited prior research in addressing wellness, perceived stress, and mattering in relationship to…
Descriptors: Dropout Rate, Wellness, Predictor Variables, Correlation
Speroni, Cecilia – National Center for Postsecondary Research, 2011
Advanced Placement (AP) and Dual Enrollment (DE) are two programs that allow high school students to earn college credits. The recent growth of these programs has been unprecedented. However, there is little evidence that compares how they fare in terms of improving college access and success. Using data from two cohorts of all high school…
Descriptors: Advanced Placement, College Credits, Dual Enrollment, High School Students
Davey, Carla Mae – ProQuest LLC, 2010
According to generational theorists, the interests and experiences of incoming students have fluctuated over time, with Millennial students being more engaged and accomplished than their predecessors. This project explored data from 1974-2007 to determine the actual trends in engagement and accomplishments for three generations of students. Over…
Descriptors: Learner Engagement, School Activities, Grade Point Average, School Holding Power
Caldwell, James R.; And Others – Educ Psychol Meas, 1970
Descriptors: Academic Achievement, Evaluation Methods, Geometry, Grade 10