Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 1 |
Since 2016 (last 10 years) | 1 |
Since 2006 (last 20 years) | 1 |
Descriptor
Data Analysis | 3 |
Decision Making | 3 |
Higher Education | 2 |
Student Attitudes | 2 |
Advantaged | 1 |
Bias | 1 |
College Applicants | 1 |
College Choice | 1 |
Course Evaluation | 1 |
Data Collection | 1 |
Epistemology | 1 |
More ▼ |
Source
Research in Higher Education | 3 |
Publication Type
Journal Articles | 3 |
Information Analyses | 1 |
Opinion Papers | 1 |
Reports - Research | 1 |
Speeches/Meeting Papers | 1 |
Education Level
Grade 9 | 1 |
High Schools | 1 |
Higher Education | 1 |
Junior High Schools | 1 |
Middle Schools | 1 |
Postsecondary Education | 1 |
Secondary Education | 1 |
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Wesley Jeffrey; Benjamin G. Gibbs – Research in Higher Education, 2024
While a substantial body of work has shown that higher-SES students tend to apply to more selective colleges than their lower-SES counterparts, we know relatively less about "why" students differ in their application behavior. In this study, we draw upon a sociological approach to educational stratification to unpack the SES-based gap in…
Descriptors: College Applicants, Socioeconomic Status, Socioeconomic Influences, College Choice

McCallum, L. W. – Research in Higher Education, 1984
A meta-analysis of studies examining the criterion validity of student course evaluation data is discussed. Results indicate that the overall size of effect is not only highly significant, but also very meaningful when analyzed in relation to enhancing the likelihood of making more accurate tenure decisions. (Author/MLW)
Descriptors: Course Evaluation, Data Analysis, Decision Making, Faculty Evaluation

Hackman, Judith Dozier – Research in Higher Education, 1983
Seven institutional research maxims based on research and theory about how people cognitively process information are discussed: more may not be better; augment humans with models; chunk data wisely; know decision-makers; heuristics are not always helpful; arrange tables by patterns; and accept negative evidence and new hypotheses. (Author/MLW)
Descriptors: Bias, Data Analysis, Data Collection, Decision Making