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William Parker Morgan IV – ProQuest LLC, 2020
Accurate placement into an initial college mathematics course is a key step toward the successful completion of college mathematics and, eventually, a college degree. Conversely, misplacement in mathematics may lead to a reduced likelihood of course completion and degree attainment. This study investigated the ability of two placement models to…
Descriptors: College Mathematics, College Students, Student Placement, Mathematics Achievement
Elaine M. Allensworth; Kallie Clark – Grantee Submission, 2020
High school GPAs (HSGPAs) are often perceived to represent inconsistent levels of readiness for college across high schools, while test scores (e.g., ACT scores) are seen as comparable. This study tests those assumptions, examining variation across high schools of both HSGPAs and ACT scores as measures of academic readiness for college. We find…
Descriptors: Grade Point Average, College Entrance Examinations, Predictor Variables, Academic Persistence
Elaine M. Allensworth; Kallie Clark – Educational Researcher, 2020
High school GPAs (HSGPAs) are often perceived to represent inconsistent levels of readiness for college across high schools, whereas test scores (e.g., ACT scores) are seen as comparable. This study tests those assumptions, examining variation across high schools of both HSGPAs and ACT scores as measures of academic readiness for college. We found…
Descriptors: Grade Point Average, College Entrance Examinations, Predictor Variables, Academic Persistence
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Means, Barbara; Wang, Haiwen; Wei, Xin; Lynch, Sharon; Peters, Vanessa; Young, Viki; Allen, Carrie – Science Education, 2017
Inclusive STEM high schools (ISHSs) (where STEM is science, technology, engineering, and mathematics) admit students on the basis of interest rather than competitive examination. This study examines the central assumption behind these schools--that they provide students from subgroups underrepresented in STEM with experiences that equip them…
Descriptors: STEM Education, High Schools, High School Students, Hierarchical Linear Modeling
Westrick, Paul A. – ACT, Inc., 2014
The purpose of this study was to determine if validity coefficients for ACT scores and high school grade point average (HSGPA) decayed or held stable over eight semesters of undergraduate study in science, technology, engineering, and mathematics (STEM) fields at civilian four-year institutions, and whether the decay patterns differed from those…
Descriptors: STEM Education, Validity, College Entrance Examinations, Scores
Zhang, Qian; Sanchez, Edgar I. – ACT, Inc., 2013
This study explores inflation in high school grade point average (HSGPA), defined as trend over time in the conditional average of HSGPA, given ACT® Composite score. The time period considered is 2004 to 2011. Using hierarchical linear modeling, the study updates a previous analysis of Woodruff and Ziomek (2004). The study also investigates…
Descriptors: High School Students, Grade Inflation, Grade Point Average, Hierarchical Linear Modeling
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Roderick, Melissa; Holsapple, Matthew; Kelley-Kemple, Thomas; Johnson, David W. – Society for Research on Educational Effectiveness, 2014
Over the past 20 years, gaps in students' educational aspirations have shrunk considerably (Roderick et al., 2008; Roderick, Nagaoka, & Coca, 2011; Kao & Tienda, 1998; Avery & Kane, 2004; Turner, 2007; Deil-Amen & Tevis, 2010). Similarly, racial and ethnic gaps in college enrollment have shrunk. The one area in which postsecondary…
Descriptors: College Readiness, Graduation Rate, Higher Education, College Students
Westrick, Paul A. – ACT, Inc., 2015
This study examined the effects of differential grading in science, technology, engineering, and mathematics (STEM) and non-STEM fields over eight consecutive semesters. Using data from 62,122 students at 26 four-year postsecondary institutions, students were subdivided by institutional admission selectivity levels, gender, and student major…
Descriptors: Grading, Student Evaluation, STEM Education, Meta Analysis
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McArdle, John J.; Paskus, Thomas S.; Boker, Steven M. – Multivariate Behavioral Research, 2013
This is an application of contemporary multilevel regression modeling to the prediction of academic performances of 1st-year college students. At a first level of analysis, the data come from N greater than 16,000 students who were college freshman in 1994-1995 and who were also participants in high-level college athletics. At a second level of…
Descriptors: Multivariate Analysis, Multiple Regression Analysis, Hierarchical Linear Modeling, College Athletics
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Henry, Gary T.; Campbell, Shanyce L.; Thompson, Charles L.; Patriarca, Linda A.; Luterbach, Kenneth J.; Lys, Diana B.; Covington, Vivian Martin – Journal of Teacher Education, 2013
Calls for evidence-based reform of teacher preparation programs (TPPs) suggest the question: Do the current indicators of progress and performance used by TPPs predict effectiveness of their graduates when they become teachers? In this study, the indicators of progress and performance used by one program are examined for their ability to predict…
Descriptors: Teacher Education, Preservice Teachers, Evidence, Predictive Validity
Wilson, James K., III – ProQuest LLC, 2012
The purpose of this study was to better predict how a first semester college freshman becomes prepared for college. The theoretical framework guiding this study is Vrooms' expectancy theory, motivation plays a key role in success. This study used a hierarchical multiple regression model. The independent variables of interest included high school…
Descriptors: Predictor Variables, College Readiness, College Freshmen, College Preparation