Publication Date
In 2025 | 0 |
Since 2024 | 0 |
Since 2021 (last 5 years) | 0 |
Since 2016 (last 10 years) | 2 |
Since 2006 (last 20 years) | 3 |
Descriptor
Source
Educational Researcher | 3 |
Author
Adelson, Jill L. | 1 |
Cunningham, Brittany C. | 1 |
Dickinson, Emily R. | 1 |
Elaine M. Allensworth | 1 |
Fantuzzo, John W. | 1 |
Kallie Clark | 1 |
LeBoeuf, Whitney A. | 1 |
Rouse, Heather L. | 1 |
Publication Type
Journal Articles | 3 |
Reports - Research | 3 |
Education Level
Grade 3 | 2 |
Elementary Education | 1 |
Grade 10 | 1 |
Grade 4 | 1 |
Grade 5 | 1 |
Grade 6 | 1 |
Grade 7 | 1 |
Grade 8 | 1 |
Grade 9 | 1 |
High Schools | 1 |
Higher Education | 1 |
More ▼ |
Audience
Location
Illinois (Chicago) | 1 |
Kentucky | 1 |
Pennsylvania | 1 |
Laws, Policies, & Programs
Assessments and Surveys
ACT Assessment | 1 |
What Works Clearinghouse Rating
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
Adelson, Jill L.; Dickinson, Emily R.; Cunningham, Brittany C. – Educational Researcher, 2016
This brief examined the patterns of reading achievement using statewide data from all students (Grades 3-10) in multiple years to examine gaps based on student, school, and district characteristics. Results indicate reading achievement varied most between students within schools and that students' prior achievement was the strongest predictor of…
Descriptors: Reading Achievement, Achievement Gap, School Districts, Institutional Characteristics
Fantuzzo, John W.; LeBoeuf, Whitney A.; Rouse, Heather L. – Educational Researcher, 2014
This study investigated the unique relations between school concentrations of student risk factors and measures of reading, mathematics, and attendance. It used an integrated administrative data system to create a combined data set of risks (i.e., birth risks, teen mother, low maternal education, homelessness, maltreatment, and lead exposure) for…
Descriptors: At Risk Students, Well Being, Correlation, Early Parenthood