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Tochukwu Okoye – Learning Professional, 2024
Data is ubiquitous and inseparable from the human experience. It constantly informs and transforms interactions, decisions, and understanding. If the total amount of all the data created daily was printed on paper, it would fill a library the size of 110 Libraries of Congress. As a senior research consultant for an education market research and…
Descriptors: Elementary Secondary Education, Data Use, Inclusion, Educational Improvement
Amy Shelton; Collin Hitt – Journal of School Choice, 2024
There are over one million school-age children in Missouri, and we estimate 61,000 (6% of all school-age children) are homeschooled. Missouri is one of 29 states that does not require homeschooling to be reported. Using methods that can be replicated elsewhere with publicly available data, we test three approaches to estimating homeschool…
Descriptors: Home Schooling, Attendance, Data Collection, School Statistics
A Study Comparing Text-Based WhatsApp and Face-to-Face Interviews to Understand Early School Dropout
Desai, Rachana; Magan, Ansuyah; Maposa, Innocent; Ruiter, Robert; Rochat, Tamsen; Mercken, Liesbeth – Youth & Society, 2024
The majority of adolescents communicate via text-based messaging, particularly through WhatsApp, a widely used free communication application. Written content on WhatsApp has the methodological potential to provide rich qualitative interview data. This study compares data collected using text-based WhatsApp versus face-to-face interview…
Descriptors: Comparative Analysis, Data Collection, Computer Mediated Communication, Dropouts
Florian Keusch; Paulina K. Pankowska; Alexandru Cernat; Ruben L. Bach – Field Methods, 2024
Data donation is a novel approach to collecting digital trace data, where users are asked to download their retrospective data from a platform and share them with the researchers. Little is known about the willingness to donate data and the potential bias that may arise from nonparticipation. We conducted a study among over 900 German Facebook…
Descriptors: Data Collection, Research Methodology, Information Dissemination, Social Media
Gerald Gartlehner; Leila Kahwati; Rainer Hilscher; Ian Thomas; Shannon Kugley; Karen Crotty; Meera Viswanathan; Barbara Nussbaumer-Streit; Graham Booth; Nathaniel Erskine; Amanda Konet; Robert Chew – Research Synthesis Methods, 2024
Data extraction is a crucial, yet labor-intensive and error-prone part of evidence synthesis. To date, efforts to harness machine learning for enhancing efficiency of the data extraction process have fallen short of achieving sufficient accuracy and usability. With the release of large language models (LLMs), new possibilities have emerged to…
Descriptors: Data Collection, Evidence, Synthesis, Language Processing
Christoph Beuthner; Bernd Weiß; Henning Silber; Florian Keusch; Jette Schröder – International Journal of Social Research Methodology, 2024
As our modern world has become increasingly digitalized, various types of data from different data domains are available that can enrich survey data. To link survey data to other sources, consent from the survey respondents is required. This article compares consent to data linkage requests for seven data domains: administrative data, smartphone…
Descriptors: Foreign Countries, Online Surveys, Data Collection, Informed Consent
Marta Olmo-Extremera; Lucía Fernández-Terol; Diana Amber Montes – Qualitative Research Journal, 2024
Purpose: This study aims to describe and evaluate various visual and creative tools for supporting the in-depth biographical interview aimed at analyzing educational communities and their stakeholders. Design/methodology/approach: Researching educational spaces today requires new ways of understanding, analyzing and studying. The complex…
Descriptors: Visual Aids, Interviews, Qualitative Research, Stakeholders
John E. Kerrigan; Sally Lu – Journal of Research Administration, 2024
A major pre-award administrative challenge research universities face is turnaround time for generation of high-quality NIH Data Training Tables for NIH training grants (e.g., T32, K12, TL1, KL2, R25s) which are required for training grant submission proposals to the National Institutes of Health (NIH). Universities with dedicated training grant…
Descriptors: Research Universities, Research Administration, Educational Finance, Grants
Leonidas Sakalauskas; Vytautas Dulskis; Darius Plikynas – Structural Equation Modeling: A Multidisciplinary Journal, 2024
Dynamic structural equation models (DSEM) are designed for time series analysis of latent structures. Inherent to the application of DSEM is model parameter estimation, which has to be addressed in many applications by a single time series. In this context, however, the methods currently available either lack estimation quality or are…
Descriptors: Structural Equation Models, Time Management, Predictive Measurement, Data Collection
Dylan Wiliam; Douglas Fisher; Nancy Frey – Corwin, 2024
What if there was a better way to collect and interpret assessment data that could strengthen the link between teaching and learning? "Student Assessment: Better Evidence, Better Decisions, Better Learning" is the innovative guide to show you how it is done and done right. This unique book offers a new assessment model focused on…
Descriptors: Student Evaluation, Data Collection, Evidence Based Practice, Data Use
Gregory Chernov – Evaluation Review, 2025
Most existing solutions to the current replication crisis in science address only the factors stemming from specific poor research practices. We introduce a novel mechanism that leverages the experts' predictive abilities to analyze the root causes of replication failures. It is backed by the principle that the most accurate predictor is the most…
Descriptors: Replication (Evaluation), Prediction, Scientific Research, Failure
Julian Schuessler; Peter Selb – Sociological Methods & Research, 2025
Directed acyclic graphs (DAGs) are now a popular tool to inform causal inferences. We discuss how DAGs can also be used to encode theoretical assumptions about nonprobability samples and survey nonresponse and to determine whether population quantities including conditional distributions and regressions can be identified. We describe sources of…
Descriptors: Data Collection, Graphs, Error of Measurement, Statistical Bias
Knips, Andrew; Lopez, Sonya; Savoy, Michael; LaParo, Kendall – ASCD, 2022
Building a better data culture can be the path to better results and greater equity in schools. But what do we mean by data? Your students are not just statistics. They aren't simply a set of numbers or faceless dots on a proficiency scale. They are vibrant collections of experiences, thoughts, perspectives, emotions, wants, and dreams. And taken…
Descriptors: Equal Education, Data Use, Data Collection, Data Analysis
Marissa A. Diaz; Jerome E. Bickenbach; Carla Sabariego; Renaldo M. Bernard – Journal of Applied Research in Intellectual Disabilities, 2024
Background: A paucity of qualitative research on sensitive topics that focuses on participants with intellectual disabilities leaves their views unexplored. This scoping review mainly aimed to provide an overview of qualitative data collection methods used in research involving participants with intellectual disabilities to explore death and…
Descriptors: Research Methodology, Intellectual Disability, Death, Research
Nicholas Norman Adams – International Journal of Social Research Methodology, 2024
The global scale of COVID-19 has constrained academics from conducting much person-facing research. Reactively, trend is increasing for digital-based methodologies capturing already existing online data. Scholars often 'scrape' user-postings from internet forums using coding algorithms and text capture tools, before analysing data, drawing…
Descriptors: Research Methodology, Educational Trends, Informed Consent, COVID-19