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Rebecca Whittle; Joie Ensor; Miriam Hattle; Paula Dhiman; Gary S. Collins; Richard D. Riley – Research Synthesis Methods, 2024
Collecting data for an individual participant data meta-analysis (IPDMA) project can be time consuming and resource intensive and could still have insufficient power to answer the question of interest. Therefore, researchers should consider the power of their planned IPDMA before collecting IPD. Here we propose a method to estimate the power of a…
Descriptors: Data, Individual Characteristics, Participant Characteristics, Meta Analysis
Brachle, Benjamin; McElravy, L. J. – Journal of Leadership Education, 2023
The rising costs of recruiting and hiring workers and the seismic shift of age demographics in the United States workforce has created much stir around the concept of generational cohorts. Although much has been done by researchers and practitioners alike to attempt a better understanding of each generational group's leadership preferences,…
Descriptors: Educational Research, Research Problems, Leadership, Cohort Analysis
Luo, Liying; Hodges, James S. – Sociological Methods & Research, 2022
Social scientists have frequently sought to understand the distinct effects of age, period, and cohort, but disaggregation of the three dimensions is difficult because cohort = period - age. We argue that this technical difficulty reflects a disconnection between how the cohort effect is conceptualized and how it is modeled in the traditional…
Descriptors: Social Sciences, Time, Age, Population Groups
Smith, Michael L.; Sokolová, Vera – British Journal of Sociology of Education, 2022
This article analyses gender inequalities in educational attainment in the Czech Republic from the novel perspective of multiple educational pathways, which are primary channels of study involving at least two educational transitions (secondary and tertiary) with qualitatively different tracks. We estimate gender gaps in the attainment of six…
Descriptors: Gender Differences, Educational Attainment, Foreign Countries, Social Stratification
Balázs Égert; Christine de la Maisonneuve; David Turner – Education Economics, 2024
This paper develops a new measure of human capital, calculated as a cohort-weighted average of the quality of education (PISA scores) and the quantity of education (mean years of schooling). Contrary to the existing studies, the relative weights of quality and quantity are estimated (and not calibrated). The quality of education is estimated to be…
Descriptors: Human Capital, Outcomes of Education, Educational Quality, Macroeconomics
Nickles, George M.; Herbert, Bruce – Journal of Educational Research and Practice, 2022
Centerness is defined as a quality of multi-agent systems (groups) where agents share a common set of system goals and interact so the system will achieve those goals. A pair of measures is identified to capture the two dimensions of centerness: distance-weighted fragmentation and average goal centerness. As a case study, the measures of…
Descriptors: Faculty Development, Social Networks, Information Science, Teacher Centers
Blazar, David; Kraft, Matthew A. – AERA Open, 2019
Over the past 15 years, the education research community has advocated for rigorous research designs that support causal inferences, for research that provides more generalizable results across settings, and for the value of research-practice partnerships that inform the design of local programs and policies. We propose the multi-cohort,…
Descriptors: Longitudinal Studies, Educational Research, Cohort Analysis, Replication (Evaluation)
Reardon, Sean F.; Papay, John P.; Kilbride, Tara; Strunk, Katherine O.; Cowen, Joshua; An, Lily; Donohue, Kate – Stanford Center for Education Policy Analysis, 2019
In this paper we compare two approaches to measuring the average rate at which students learn in a given school or district. One type of measure--longitudinal growth measures--relies on student-level longitudinal data. A second type--cohort growth measures--relies only on repeated aggregated, cross-sectional data. Because student-level data is…
Descriptors: Measurement Techniques, Growth Models, Cohort Analysis, Longitudinal Studies
Prevost, Luanna B.; Vergara, Claudia E.; Urban-Lurain, Mark; Campa, Henry, III. – Innovative Higher Education, 2018
Higher education institutions prepare future faculty members for multiple roles, including teaching. However, teaching professional development programs for graduate students vary widely. We present evaluation data from a high engagement program for STEM doctoral students. We analyzed the impact on three cohorts of participants over three academic…
Descriptors: STEM Education, Graduate Students, Fellowships, Program Evaluation
Delisle, Jason D. – American Enterprise Institute, 2018
This report is one of the first to examine federal student loan repayments for graduate institutions. While the data are not without limitations and this report is based only on two lists of 20 institutions each, the data reveal some important findings. Historically Black Colleges and Universities (HBCUs) have some of the weakest rates of loan…
Descriptors: Graduate Study, Graduate Students, Student Financial Aid, Loan Repayment
Shukla, Vachaspati; Mishra, Udaya S. – Prospects: Quarterly Review of Comparative Education, 2017
This article evaluates the progress in literacy among the Indian states, from an age-cohort perspective. It argues that age-cohort analysis offers a robust understanding of the dynamics of literacy progress. The article clearly brings out the fact that, despite the accomplishment of universal elementary education, achieving the goal of full…
Descriptors: Foreign Countries, Literacy, Academic Achievement, Demography
Achieve, Inc., 2016
Every state has made the college and career readiness of its high school graduates a major priority, but few are doing a good job monitoring how well the education system is delivering on that goal. States mostly rely on high school graduation rates to gauge progress. While there have been signifcant improvements in the high school graduation…
Descriptors: High School Students, Grade 9, College Readiness, Career Readiness
Carter, Tim – SRATE Journal, 2018
Generation Z, also known as the Homeland Generation, is the most recent generational cohort to enter the university setting. As with other generational cohorts, various shaping factors have impacted this group contributing to its unique and defining characteristics. When carefully considered, these characteristics may provide insight into how to…
Descriptors: Generational Differences, Teaching (Occupation), Cohort Analysis, Student Characteristics
Gershenson, Seth; Papageorge, Nicholas – Education Next, 2018
Despite abundant anecdotes and theories suggesting a causal effect of teachers' expectations on student outcomes, documenting its presence and size has been challenging. The reason is simple: positive correlations between what teachers expect and what students ultimately accomplish might simply result from teachers being skilled observers. In…
Descriptors: Teacher Expectations of Students, Racial Bias, Academic Achievement, Outcomes of Education
Majumdar, Rwitajit; Iyer, Sridhar – Research and Practice in Technology Enhanced Learning, 2016
Interactive Stratified Attribute Tracking (iSAT) is a visual analytics tool for cohort analysis. In this paper, we show how instructors can use iSAT to visualize transitions of groups of students during teaching-learning activities. Interactive visual analytics gives the instructor the affordance of understanding the dynamics of the class of…
Descriptors: Visual Learning, Learning Analytics, Cohort Analysis, Affordances