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Sarah Amber Evans; Lingzi Hong; Jeonghyun Kim; Erin Rice-Oyler; Irhamni Ali – Information and Learning Sciences, 2024
Purpose: Data literacy empowers college students, equipping them with essential skills necessary for their personal lives and careers in today's data-driven world. This study aims to explore how community college students evaluate their data literacy and further examine demographic and educational/career advancement disparities in their…
Descriptors: Community College Students, Self Evaluation (Individuals), Data Analysis, Demography
Justin B. Doromal; Erica Greenberg; Elli Nikolopoulos; Eve Mefferd; Heather Sandstrom; Rachel Lamb; Victoria Nelson; Timothy Triplett – Urban Institute, 2024
Early childhood educators play essential roles in providing stable and high-quality child care for young children and supporting their development and growth. As is also true nationwide, historically low wages in the District of Columbia have led to challenges in compensating and retaining qualified early childhood educators, and in turn, building…
Descriptors: Program Implementation, Early Childhood Education, Educational Equity (Finance), Educational Finance
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Jade Mai Cock; Hugues Saltini; Haoyu Sheng; Riya Ranjan; Richard Davis; Tanja Käser – International Educational Data Mining Society, 2024
Predictive models play a pivotal role in education by aiding learning, teaching, and assessment processes. However, they have the potential to perpetuate educational inequalities through algorithmic biases. This paper investigates how behavioral differences across demographic groups of different sizes propagate through the student success modeling…
Descriptors: Demography, Statistical Bias, Algorithms, Behavior
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Michael Lachanski – Grantee Submission, 2023
Background: The distribution of job tenure plays an important role in demography, economics, and sociology. Job tenure in a labor market is analogous to age in a population. Demographers have used indirect methods based on variable-r methods to estimate parameters for life table models. The variable-r method can also be employed to estimate the…
Descriptors: Demography, School Demography, Tenure, Labor Market
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Shiyu Zhang; James Wagner – Sociological Methods & Research, 2024
Adaptive survey design refers to using targeted procedures to recruit different sampled cases. This technique strives to reduce bias and variance of survey estimates by trying to recruit a larger and more balanced set of respondents. However, it is not well understood how adaptive design can improve data and survey estimates beyond the…
Descriptors: Surveys, Research Design, Response Rates (Questionnaires), Demography
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Baylee A. Edwards; Jude Kolodisner; Jacob P. Youngblood; Katelyn M. Cooper; Sara E. Brownell – Advances in Physiology Education, 2024
The impersonal nature of high-enrollment science courses makes it difficult to build student-instructor relationships, which can negatively impact student learning and engagement, especially for members of marginalized groups. In this study, we explored whether an instructor collecting and sharing aggregated student demographics could positively…
Descriptors: Higher Education, Data Collection, Surveys, Demography
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Suich, Helen; Yap, Mandy; Pham, Trang – International Journal of Social Research Methodology, 2022
This paper uses Individual Deprivation Measure data from Indonesia and South Africa to demonstrate the effects of coverage bias associated with mobile phone-based sampling and data collection approaches that restrict sampling frames to those who own or have access to a mobile phone -- a increasingly common method. Analysis of this data…
Descriptors: Bias, Handheld Devices, Telecommunications, Sampling
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Enid Zambrana, Ruth; Amaro, Gabriel; Butler, Courtney; DuPont-Reyes, Melissa; Parra-Medina, Deborah – Health Education & Behavior, 2021
Introduction: Prior to 1980, U.S. national demographic and health data collection did not identify individuals of Hispanic/Latina/o heritage as a population group. Post-1990, robust immigration from Latin America (e.g., South America, Central America, Mexico) and subsequent growth in U.S. births, dynamically reconstructed the ethnoracial lines…
Descriptors: Data Analysis, Data Collection, Demography, Hispanic Americans
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Hannah R. Thompson; Joni Ladawn Ricks-Oddie; Margaret Schneider; Sophia Day; Kira Argenio; Kevin Konty; Shlomit Radom-Aizik; Yawen Guo; Dan M. Cooper – Journal of School Health, 2025
Background: Data missingness can bias interpretation and outcomes resulting from data use. We describe data missingness in the longest-standing US-based youth fitness surveillance system (2006/07-2019/20). Methods: This observational study uses the New York City FITNESSGRAM (NYCFG) database from 1,983,629 unique 4th-12th grade students (9,147,873…
Descriptors: Physical Fitness, Data Interpretation, Statistical Bias, Youth
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Álvaro de Oliveira D'Antona; José Diego Gobbo Alves – International Journal of Social Research Methodology, 2024
We describe the use of tablet computers with ESRI Survey123 for data collection in sociodemographic surveys applied to land use and cover change studies. Based on the administration of 716 questionnaires during the expedition carried out in 2022 in 64 rural communities along the Rio Negro River, in the Brazilian Amazon, we evaluate the advantages…
Descriptors: Foreign Countries, Tablet Computers, Technology Uses in Education, Social Science Research
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Kahn, Jennifer; Jiang, Shiyan – Learning, Media and Technology, 2021
We present a micro-analysis of youth interactions with large complex, socioeconomic datasets and data visualization tools. Middle and high school youth used georeferenced data and data visualization tools to assemble models that present their family migration histories in relation to larger socioeconomic trends in a summer program. Using…
Descriptors: Visualization, Data Use, Data Interpretation, Decision Making
Daugherty, Lindsay; Anderson, Drew M. – RAND Corporation, 2021
This appendix supplements the report "Stackable Credential Pipelines in Ohio: Evidence on Programs and Earnings Outcomes" (ED613593). In the appendix, the authors provide more details about the data and empirical approach, additional information about the samples, and some alternative results from analyses related to those that appear in…
Descriptors: Credentials, Postsecondary Education, Research Methodology, Data Collection
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Schles, Rachel Anne; McCarthy, Tessa; Blankenship, Karen; Coy, Justin – Exceptional Children, 2021
The prevalence of students with visual impairments varies across the United States, yet limited analysis exists on how many students receive special education services. The following study collected population data on students with visual impairments for the 2017-2018 school year and ran focus groups with state-level administrators to understand…
Descriptors: Students with Disabilities, Visual Impairments, Blindness, Administrators
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Barros, Thiago M.; Souza Neto, Plácido A.; Silva, Ivanovitch; Guedes, Luiz Affonso – Education Sciences, 2019
Predicting school dropout rates is an important issue for the smooth execution of an educational system. This problem is solved by classifying students into two classes using educational activities related statistical datasets. One of the classes must identify the students who have the tendency to persist. The other class must identify the…
Descriptors: Predictor Variables, Models, Dropout Rate, Classification
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Scott D. Scheer; Trent Baldwin; Amelia R. Michaels; Julie Fox; Kirk Bloir – Journal of Youth Development, 2022
4-H youth development programs throughout the United States can be planned and delivered more effectively in their states by assessing demographic data and following research-based theories and models of positive youth development. A review of the research literature determined current youth development theories and models to effectively guide…
Descriptors: Youth Programs, Youth Clubs, Community Programs, Program Implementation
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