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Showing 1 to 15 of 31 results Save | Export
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Jing Liu; Megan Kuhfeld; Monica Lee; Danett Song – Society for Research on Educational Effectiveness, 2021
Background: Noncognitive skills are a critical component of human capital and are highly consequential for student life outcomes (Heckman et al., 2006; Cunha et al., 2010). While there is a great deal of debates around what noncognitive skills are, their measurement, and their interpretation (Duckworth & Yeager, 2015; Humphries & Kosse,…
Descriptors: Human Capital, Predictive Validity, Skill Development, Educational Policy
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Woods, Isaac L., Jr.; Niileksela, Christopher; Floyd, Randy G. – Contemporary School Psychology, 2021
Racial/ethnic bias in the prediction of students' educational potential was questioned in the Larry P. Vs. Riles case. The construct and predictive validity of the Woodcock-Johnson IV Tests of Cognitive Abilities (WJ IV; Schrank et al. 2014b) have not been examined for racial/ethnic bias. This study extended Keith's (1999) examination of bias…
Descriptors: Cognitive Ability, Cognitive Tests, Predictor Variables, Reading Achievement
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
Rickes, Scott – ProQuest LLC, 2018
The ability to predict accurately college freshman-year grade point average (FYGPA) in a way that minimizes the adverse impact associated with the predictors traditionally used as acceptance criteria has been an important and controversial topic for several decades. FYGPA is an important measure of educational performance because it is related to…
Descriptors: Racial Differences, Predictor Variables, Ethnicity, College Freshmen
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Higdem, Jana L.; Kostal, Jack W.; Kuncel, Nathan R.; Sackett, Paul R.; Shen, Winny; Beatty, Adam S.; Kiger, Thomas B. – Educational Measurement: Issues and Practice, 2016
Recent research has shown that admissions tests retain the vast majority of their predictive power after controlling for socioeconomic status (SES), and that SES provides only a slight increment over SAT and high school grades (high school grade point average [HSGPA]) in predicting academic performance. To address the possibility that these…
Descriptors: Socioeconomic Status, Gender Differences, Racial Differences, Grade Point Average
Beard, Jonathan; Marini, Jessica P. – College Board, 2015
The continued accumulation of validity evidence for the intended uses of educational assessment scores is critical to ensure that inferences made using the scores are sound. To that end, the College Board has continued to collect college outcome data to evaluate the relationship between SAT® scores and college success. This report provides updated…
Descriptors: Statistical Data, Predictive Validity, Educational Assessment, Evidence
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Johnson, Ursula Y.; Hull, Darrell M. – Journal of Educational Research, 2014
The authors examined science achievement growth at Grades 3, 5, and 8 and parent school involvement at the same time points using the Early Childhood Longitudinal Study-Kindergarten Class of 1998-1999. Data were analyzed using cross-classified multilevel latent growth curve modeling with time invariant and varying covariates. School-based…
Descriptors: Science Achievement, Parent Participation, Grade 3, Grade 5
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Ng, Florrie Fei-Yin; Tamis-LeMonda, Catherine; Yoshikawa, Hirokazu; Sze, Irene Nga-Lam – International Journal of Behavioral Development, 2015
Preschoolers' inhibitory control and early math skills were concurrently and longitudinally examined in 255 Chinese, African American, Dominican, and Mexican 4-year-olds in the United States. Inhibitory control at age 4, assessed with a peg-tapping task, was associated with early math skills at age 4 and predicted growth in such skills from age 4…
Descriptors: Preschool Children, Preschool Education, Predictor Variables, Predictive Validity
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Lewis, Kathy; Olver, Mark E.; Wong, Stephen C. P. – Assessment, 2013
The Violence Risk Scale (VRS) uses ratings of static and dynamic risk predictors to assess violence risk, identify targets for treatment, and assess changes in risk following treatment. The VRS was rated pre- and posttreatment on a sample of 150 males, mostly high-risk violent offenders many with psychopathic personality traits. These individuals…
Descriptors: At Risk Persons, Violence, Predictive Validity, Predictor Variables
Dacay, Monique – ProQuest LLC, 2011
Addressing inconsistencies in student achievement between students of different racial backgrounds has been acknowledged and explored for over fifty years. Policies and programs have been developed and funded to decrease the discrepancies between groups with limited evidence of success. This study will explore the presence of achievement…
Descriptors: Academic Achievement, College Readiness, Achievement Gap, Student Motivation
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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
Dahlin, Michael; Tarasawa, Beth – Northwest Evaluation Association, 2013
In this follow-up to "Do High Flyers Maintain Their Altitude? Performance Trends of Top Students," the academic growth of 35,000 elementary and middle school students in 31 states, all of them high achievers within their own schools, were followed over a three-year period. Their achievement scores were matched with their associated…
Descriptors: College Readiness, Accountability, Academic Standards, Longitudinal Studies
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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
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