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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
Ayfer Sayin; Okan Bulut – International Journal of Assessment Tools in Education, 2024
Test development is a complicated process that demands examining various factors, one of them being writing items of varying difficulty. It is important to use items of a different range of difficulty to ensure that the test results accurately indicate the test-taker's abilities. Therefore, the factors affecting item difficulty should be defined,…
Descriptors: Foreign Countries, High Schools, Standardized Tests, Placement Tests
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
Soltaninejad, Mehraneh – Malaysian Online Journal of Educational Sciences, 2015
The purpose of this study is to examine the relationships between achievement goal orientations and Learning Strategies. The sample of study consists of 350 public high school students (135 males and 215 females, mean age: 17 ± 0.65) from two high schools in Kerman province of Iran selected by random multistage cluster sampling method. In this…
Descriptors: Goal Orientation, Learning Strategies, Structural Equation Models, Investigations
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
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
Stemler, Steven E. – Educational Psychologist, 2012
University admissions tests should predict an applicant's ability to succeed in college, but how should this success be defined and measured? The status quo has been to use 1st-year grade point average (FYGPA) as the key indicator of college success, but a review of documents such as university mission statements reveals that universities expect…
Descriptors: Evidence, Grade Point Average, Academic Achievement, College Admission
Biddle, Nicholas – Education Economics, 2013
In this paper, the 2001 Australian Census is used to estimate predicted net benefits of education at a small geographic level. These are then linked to youth in the areas to test the associations with high school participation. This is done separately for Indigenous youth, a population sub-group with historically low levels of education…
Descriptors: Indigenous Populations, Cost Effectiveness, Foreign Countries, Educational Benefits
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
Smith, Wade; Droddy, Jason; Guarino, A. J. – Current Issues in Education, 2011
Schools across America are being ranked for their effectiveness on a number of student criteria, among them preparation of students for a successful college experience. This study investigates the relationship between graduating seniors, their successful first year retention in college and several personal and school related factors. The study…
Descriptors: Academic Achievement, Accountability, School Holding Power, Effect Size
Fletcher, Edward C., Jr. – Career and Technical Education Research, 2012
The purpose of this study was to predict occupational choices based on demographic variables and high school curriculum tracks. Based on an analysis of the 1997 National Longitudinal Survey of Youth (NLSY) data set that examined high school graduates' occupational choices in 2006, findings indicated that CTE graduates were 2.7 times more likely to…
Descriptors: Career Choice, High School Graduates, STEM Education, Social Influences
Sternberg, Robert J.; Bonney, Christina R.; Gabora, Liane; Merrifield, Maegan – Educational Psychologist, 2012
This article outlines shortcomings of currently used university admissions tests and discusses ways in which they could potentially be improved, summarizing two projects designed to enhance college and university admissions. The projects were inspired by the augmented theory of successful intelligence, according to which successful intelligence…
Descriptors: Intelligence, College Students, Grade Point Average, Prediction
Mo, Lun; Yang, Fang; Hu, Xiangen; Calaway, Florance; Nickey, John – Journal of Educational Research, 2011
The authors investigated the extent to which taking specific types of Advanced Placement (AP) courses and the number of courses taken predicts the likelihood of passing subject benchmarks and earning a score of 19 on the composite score on the ACT test, and examined the role gender plays in the projection. They found evidence that taking an AP…
Descriptors: Evidence, Science Tests, College Entrance Examinations, Gender Differences
Marnewick, Carl – Educational Studies, 2012
First-year students are still failing at an alarming rate. This is an international issue that universities face and there is currently no clear indication of the cause of the problem as universities move from being elite to providing mass education. This article examines the possible correlation between students' high school performance and…
Descriptors: Academic Achievement, Admission Criteria, Correlation, Mathematics Achievement
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
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