While many instructors are aware of the "Literary Digest" 1936 poll as an example of biased sampling methods, this article details potential further explorations for the "Digest's" 1924-1936 quadrennial U.S. presidential election polls. Potential activities range from lessons in data acquisition, cleaning, and validation, to…

Not knowing the population size is a common problem in data-limited contexts. Drawing on work in Sierra Leone, this short take outlines a four-step solution to this problem: (1) estimate the population size using expert interviews; (2) verify estimates using interviews with participants sampled; (3) triangulate using secondary data; and (4)…

This case study focuses on a multidecade time-series study of changes in public acceptance of evolution in the United States. Change over time is often a central issue in social science research. There are two kinds of change over time. Time-series studies address change in populations or groups over time. Longitudinal studies address changes in…

CCNetwork, in many cases, begins their work by assessing client needs--speaking with clients, examining current evidence and data, reviewing documents, and identifying patterns across those. Needs-sensing methods are important inputs to helping shape and prioritize what CCNetwork does. Landscape scans take these efforts a bit further by helping to…

The authors discuss the use of surveys for collecting data from a population sample and emphasise the importance of being careful with the language of data collection. [For "The Data Files 5: Graphs for Exploring Relationships," see EJ1355504.]

Purpose: Researchers now have more ways than ever before to capture information about groups of interest. In many areas, these are augmenting traditional survey approaches -- in others, new methods are potential replacements. This paper aims to explore three key trends: use of nonprobability samples, mobile data collection and administrative and…

This Technical Annex report sets out methodological and technical notes for the 2024 Technical Education Learner Survey. It accompanies two substantive reports -- 'Technical Education Learner Survey 2024: progression of the 2nd T Level cohort' and 'Technical Education Learner Survey 2024: progression of Level 4/5 learners'. The main body of the…

Respondent-driven sampling (RDS) is a methodology for sampling and analysing survey data from rare and elusive populations that has gained increasing attention in migration research in recent years. Since its introduction in 1997, it has been applied in numerous surveys in the field of epidemiology (mainly for the estimation of HIV/AIDS prevalence…

Higher education professionals often are tasked with providing evidence to stakeholders that programs, services, and practices implemented on their campuses contribute to student success. Furthermore, in the absence of a solid base of evidence related to effective practices, higher education researchers and practitioners are left questioning what…

In the context of Artificial Intelligence, Generative Adversarial Nets (GANs) allow the creation and reproduction of artificial data from real datasets. The aims of this work are to seek to verify the equivalence of synthetic data with real data and to verify the possibilities of GAN in educational research. The research methodology begins with…

Large-scale assessment survey (LSAS) data are collected via complex sampling designs with special features (e.g., clustering and unequal probability of selection). Multilevel models have been utilized to account for clustering effects whereas the probability weighting approach (PWA) has been used to deal with design informativeness derived from…

This is the technical report for Wave 7 of the Study of Early Education and Development (SEED), a major longitudinal study following nearly 6,000 children from across England from age 2. Wave 7 included a face-to-face survey of families and children in 2022-2023, when children were in year 6 at school and aged 10-11 years old. For SEED wave 7, the…

Descriptive analyses of socially important or theoretically interesting phenomena and trends are a vital component of research in the behavioral, social, economic, and health sciences. Such analyses yield reliable results when using representative individual participant data (IPD) from studies with complex survey designs, including educational…

We discuss methods that can improve response rates in large-scale cross-sectional and longitudinal studies. Regardless of the specific study topic, sample member population, or method of contact, data collections should be designed with certain core principles in mind: legitimizing the study to prospective participants; presenting study…

Respondent attrition is a common problem in national longitudinal panel surveys. To make full use of the data, weights are provided to account for attrition. Weight adjustments are based on sampling design information and data from the base year; information from subsequent waves is typically not utilized. Alternative methods to address bias from…