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Direct linkLeher Singh; Mihaela D. Barokova; Heidi A. Baumgartner; Diana C. Lopera-Perez; Paul Okyere Omane; Mark Sheskin; Francis L. Yuen; Yang Wu; Katherine J. Alcock; Elena C. Altmann; Marina Bazhydai; Alexandra Carstensen; Kin Chung Jacky Chan; Hu Chuan-Peng; Rodrigo Dal Ben; Laura Franchin; Jessica E. Kosie; Casey Lew-Williams; Asana Okocha; Tilman Reinelt; Tobias Schuwerk; Melanie Soderstrom; Angeline S. M. Tsui; Michael C. Frank – Developmental Psychology, 2024
Culture is a key determinant of children's development both in its own right and as a measure of generalizability of developmental phenomena. Studying the role of culture in development requires information about participants' demographic backgrounds. However, both reporting and treatment of demographic data are limited and inconsistent in child…
Descriptors: Data Collection, Young Children, Demography, Cultural Traits
Hsiu-Wen Yang; Christine Harradine; Chih-Ing Lim; Douglas H. Clements; Megan Vinh; Julie Sarama – Early Childhood Education Journal, 2025
Given the increased diversity of the population in the United States and the importance of early science, technology, engineering, and mathematics (STEM) learning, it is crucial to identify ways to reduce racial, ethnic, and gender disparities in STEM education. This is particularly important for children with disabilities with intersecting…
Descriptors: Demography, Early Intervention, STEM Education, Equal Education
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
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
Download full textBaker, Ryan S.; Esbenshade, Lief; Vitale, Jonathan; Karumbaiah, Shamya – Journal of Educational Data Mining, 2023
Predictive analytics methods in education are seeing widespread use and are producing increasingly accurate predictions of students' outcomes. With the increased use of predictive analytics comes increasing concern about fairness for specific subgroups of the population. One approach that has been proposed to increase fairness is using demographic…
Descriptors: Demography, Data Use, Prediction, Research Methodology
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
Lee, Yi-Hsuan; Haberman, Shelby J. – Journal of Educational Measurement, 2021
For assessments that use different forms in different administrations, equating methods are applied to ensure comparability of scores over time. Ideally, a score scale is well maintained throughout the life of a testing program. In reality, instability of a score scale can result from a variety of causes, some are expected while others may be…
Descriptors: Scores, Regression (Statistics), Demography, Data
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
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
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
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
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
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
Poschmann, Philipp; Goldenstein, Jan – Sociological Methods & Research, 2022
Despite the recent and ongoing progress in using text-mining tools to automatically analyze large text corpora, there remains significant potential to facilitate the study of social action in social science research. In this context, particularly the disambiguation (who is referred to in a text?) and specification (which demographic…
Descriptors: Web Sites, Collaborative Writing, Reliability, Accuracy
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
