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No Child Left Behind Act 20011
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Showing 1 to 15 of 56 results Save | Export
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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
Hart, Holly; Young, Christopher; Chen, Alicia; Zou, Andrew; Allensworth, Elaine M. – University of Chicago Consortium on School Research, 2020
The "5Essentials Survey" is one of the few validated instruments to measure school climate. Schools that are strong in at least three of the five essential supports are up to 10 times more likely to experience substantial gains in students' math and reading scores. More than 6,000 schools nationwide have administered the…
Descriptors: Educational Improvement, School Districts, Surveys, Predictive Validity
Cho, YoungWoo; Steedle, Jeffrey; Woodruff, David; Colton, Dean – ACT, Inc., 2020
Different uses of the ACT Assessment emphasize different intervals on its 1-36 score scale. Its use by colleges for applicant selection and course placement emphasize the middle and upper intervals of its score scale, and these uses have been extensively validated (ACT, 2019a). Its uses by school districts and state departments of education to…
Descriptors: College Entrance Examinations, Scores, College Applicants, Student Placement
Hart, Holly; Young, Christopher; Chen, Alicia; Zou, Andrew; Allensworth, Elaine M. – University of Chicago Consortium on School Research, 2020
The "5Essentials Survey" is one of the few validated instruments to measure school climate. Schools that are strong in at least three of the five essential supports are up to 10 times more likely to experience substantial gains in students' math and reading scores. More than 6,000 schools nationwide have administered the…
Descriptors: Educational Improvement, School Districts, Surveys, Accountability
Westrick, Paul A.; Marini, Jessica P.; Young, Linda; Ng, Helen; Shaw, Emily J. – College Board, 2023
This pilot study examines digital SAT® score relationships with first-year college performance. Results show that digital SAT scores predict college performance as well as paper and pencil SAT scores, and that digital SAT scores meaningfully improve our understanding of a student's readiness for college above high school grade point average…
Descriptors: Computer Assisted Testing, Scores, Career Readiness, College Readiness
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Galla, Brian M.; Shulman, Elizabeth P.; Plummer, Benjamin D.; Gardner, Margo; Hutt, Stephen J.; Goyer, J. Parker; D'Mello, Sidney K.; Finn, Amy S.; Duckworth, Angela L. – American Educational Research Journal, 2019
Compared with admissions test scores, why are high school grades better at predicting college graduation? We argue that success in college requires not only cognitive ability but also self-regulatory competencies that are better indexed by high school grades. In a national sample of 47,303 students who applied to college for the 2009/2010 academic…
Descriptors: Grades (Scholastic), Predictor Variables, Time to Degree, Scores
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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
Lane, Kathleen Lynne; Oakes, Wendy Peia; Cantwell, Emily D.; Royer, David J.; Leko, Melinda M.; Schatschneider, Christopher; Menzies, Holly Mariah – Journal of Emotional and Behavioral Disorders, 2019
In this article, we examined predictive validity of "Student Risk Screening Scale for Internalizing and Externalizing" (SRSS-IE) scores for use at the middle (N = 2,313 from four middle schools) and high (N = 2,727 from two high schools) school level. Results indicated middle and high school students with high levels of risk according to…
Descriptors: Screening Tests, At Risk Students, Predictive Validity, Student Behavior
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Williams, Raunda; Smiley, Ellen; Davis, Ronnie; Lamb, Teryana – Journal of Negro Education, 2018
The purpose of this study was to examine the predictability of selected cognitive and non-cognitive factors on retention. Data was collected from 822 first-time-freshmen college students at a four-year institution of higher learning. The material was analyzed using specific predictors of Fall 2012 to Spring 2013 retention. These cognitive and…
Descriptors: Predictor Variables, School Holding Power, College Freshmen, Student College Relationship
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Westrick, Paul A.; Le, Huy; Robbins, Steven B.; Radunzel, Justine M. R.; Schmidt, Frank L. – Educational Assessment, 2015
This meta-analysis examines the strength of the relationships of ACT® Composite scores, high school grades, and socioeconomic status (SES) with academic performance and persistence into the 2nd and 3rd years at 4-year colleges and universities. Based upon a sample of 189,612 students at 50 institutions, ACT Composite scores and high school grade…
Descriptors: College Entrance Examinations, Scores, Socioeconomic Status, Undergraduate Students
Bassiri, Dina – ACT, Inc., 2016
One outcome of the implementation of No Child Left Behind Act of 2001 and its call for better accountability in public schools across the nation has been the use of student assessment data in measuring schools' effectiveness. In general, inferences about schools' effectiveness depend on the type of statistical model used to link student assessment…
Descriptors: Value Added Models, High Schools, School Effectiveness, High School Graduates
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Dimitrov, Dimiter M.; Raykov, Tenko; AL-Qataee, Abdullah Ali – Educational and Psychological Measurement, 2015
This article is concerned with developing a measure of general academic ability (GAA) for high school graduates who apply to colleges, as well as with the identification of optimal weights of the GAA indicators in a linear combination that yields a composite score with maximal reliability and maximal predictive validity, employing the framework of…
Descriptors: Foreign Countries, Academic Ability, Aptitude Tests, High School Students
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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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Lovelace, Matthew D.; Reschly, Amy L.; Appleton, James J.; Lutz, Mary E. – Journal of Psychoeducational Assessment, 2014
The Student Engagement Instrument (SEI) is a self-report measure of cognitive and affective engagement with school. Prior SEI validation studies have focused primarily on construct validity through analyses of internal consistency, factor analysis, and measurement invariance. Results are presented here from a two-pronged study of the criterion…
Descriptors: Predictive Validity, Learner Engagement, Psychometrics, Measures (Individuals)
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Harrison, Judith R.; State, Talida M.; Evans, Steven W.; Schamberg, Terah – Journal of Positive Behavior Interventions, 2016
The purpose of this study was to evaluate the construct and predictive validity of scores on a measure of social acceptability of class-wide and individual student intervention, the School Intervention Rating Form (SIRF), with high school teachers. Utilizing scores from 158 teachers, exploratory factor analysis revealed a three-factor (i.e.,…
Descriptors: Construct Validity, Predictive Validity, Likert Scales, Intervention
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