Publication Date
In 2025 | 5 |
Since 2024 | 30 |
Since 2021 (last 5 years) | 106 |
Since 2016 (last 10 years) | 248 |
Since 2006 (last 20 years) | 560 |
Descriptor
Source
Author
Publication Type
Education Level
Audience
Policymakers | 59 |
Community | 51 |
Teachers | 26 |
Practitioners | 4 |
Researchers | 4 |
Students | 4 |
Administrators | 3 |
Parents | 2 |
Counselors | 1 |
Support Staff | 1 |
Location
Australia | 18 |
Arizona | 14 |
Canada | 11 |
Germany | 10 |
United Kingdom | 10 |
United Kingdom (England) | 10 |
United States | 10 |
California | 8 |
Texas | 8 |
North Carolina | 7 |
Oregon | 7 |
More ▼ |
Laws, Policies, & Programs
No Child Left Behind Act 2001 | 17 |
Elementary and Secondary… | 4 |
Every Student Succeeds Act… | 4 |
Individuals with Disabilities… | 2 |
Race to the Top | 2 |
Individuals with Disabilities… | 1 |
United Nations Convention on… | 1 |
Assessments and Surveys
What Works Clearinghouse Rating
Does not meet standards | 1 |
Adam Rajcan; Edgar A. Burns – Australian Universities' Review, 2024
As part of a study investigating research productivity of sociology PhD students in Australia, an application to the federal government's Department of Education, Skills and Employment (DESE) aimed to establish a baseline count of completed sociology doctorates by university. It was anticipated that university totals might be different from PhD…
Descriptors: Foreign Countries, Sociology, Doctoral Students, Graduation Rate
Jessica Arnold; Julie Webb – WestEd, 2024
While there are many different types of education data, policymakers and education leaders often place heavy emphasis on data from large-scale quantitative measures, such as annual state assessments. But data from these sources alone do not provide a complete picture of learning and are often not well suited to informing improvements at the local…
Descriptors: Data Use, Measurement, Educational Improvement, Outcomes of Education
Ian Hardy – Professional Development in Education, 2024
Schooling in Australia has become subject to increased processes of data-based governance. This article draws upon the insights of an experienced teacher, 'Meriam', who, having taught more than 34-years over almost a 50-year span, reflected upon the nature of such changes. Utilising theorising in relation to datafication processes and…
Descriptors: Foreign Countries, Experienced Teachers, Teacher Attitudes, Educational Change
Iannario, Maria; Tarantola, Claudia – Sociological Methods & Research, 2023
This contribution deals with effect measures for covariates in ordinal data models to address the interpretation of the results on the extreme categories of the scales, evaluate possible response styles, and motivate collapsing of extreme categories. It provides a simpler interpretation of the influence of the covariates on the probability of the…
Descriptors: Data Analysis, Data Interpretation, Probability, Models
Jonas Videbaek Jørgensen – Evidence & Policy: A Journal of Research, Debate and Practice, 2024
Background: Understanding knowledge utilisation in policymaking is a core task for the social and political sciences. However, limitations and biases abound in commonplace approaches to measuring such use. Consequently, we have little systematic evidence of the extent to which knowledge sources are used in policy decisions. Aims and objectives:…
Descriptors: Research Utilization, Policy Formation, Measurement, Content Analysis
Elizabeth H. Connors; Amber W. Childs; Susan Douglas; Amanda Jensen-Doss – Administration and Policy in Mental Health and Mental Health Services Research, 2025
Measurement-based care (MBC) research and practice, including clinical workflows and systems to support MBC, are grounded in adult-serving mental health systems. MBC research evidence is building in child and adolescent services, but MBC practice is inherently more complex due to identified client age, the family system and the need to involve…
Descriptors: Psychotherapy, Data, Data Use, Decision Making
Silvia Testa; Renato Miceli; Renato Miceli – Educational Measurement: Issues and Practice, 2025
Random Equating (RE) and Heuristic Approach (HA) are two linking procedures that may be used to compare the scores of individuals in two tests that measure the same latent trait, in conditions where there are no common items or individuals. In this study, RE--that may only be used when the individuals taking the two tests come from the same…
Descriptors: Comparative Testing, Heuristics, Problem Solving, Personality Traits
Paul A. Jewsbury; Yue Jia; Eugenio J. Gonzalez – Large-scale Assessments in Education, 2024
Large-scale assessments are rich sources of data that can inform a diverse range of research questions related to educational policy and practice. For this reason, datasets from large-scale assessments are available to enable secondary analysts to replicate and extend published reports of assessment results. These datasets include multiple imputed…
Descriptors: Measurement, Data Analysis, Achievement, Statistical Analysis
Caspari-Sadeghi, Sima – Cogent Education, 2023
Data-driven decision-making and data-intensive research are becoming prevalent in many sectors of modern society, i.e. healthcare, politics, business, and entertainment. During the COVID-19 pandemic, huge amounts of educational data and new types of evidence were generated through various online platforms, digital tools, and communication…
Descriptors: Learning Analytics, Data Analysis, Higher Education, Feedback (Response)
Landers, Richard N.; Auer, Elena M.; Mersy, Gabriel; Marin, Sebastian; Blaik, Jason – International Journal of Testing, 2022
Assessment trace data, such as mouse positions and their timing, offer interesting and provocative reflections of individual differences yet are currently underutilized by testing professionals. In this article, we present a 10-step procedure to maximize the probability that a trace data modeling project will be successful: (1) grounding the…
Descriptors: Artificial Intelligence, Data Collection, Psychometrics, Data Science
Roy Levy; Daniel McNeish – Journal of Educational and Behavioral Statistics, 2025
Research in education and behavioral sciences often involves the use of latent variable models that are related to indicators, as well as related to covariates or outcomes. Such models are subject to interpretational confounding, which occurs when fitting the model with covariates or outcomes alters the results for the measurement model. This has…
Descriptors: Models, Statistical Analysis, Measurement, Data Interpretation
Duschl, Richard; Avraamidou, Lucy; Azevedo, Nathália Helena – Science & Education, 2021
Grounded within current reform recommendations and built upon Giere's views (1986, 1999) on model-based science, we propose an alternative approach to science education which we refer to as the "Evidence-Explanation (EE) Continuum." The approach addresses conceptual, epistemological, and social domains of knowledge, and places emphasis…
Descriptors: Science Education, Epistemology, Data, Observation
The Challenges of Large-Scale, Web-Based Language Datasets: Word Length and Predictability Revisited
Meylan, Stephan C.; Griffiths, Thomas L. – Cognitive Science, 2021
Language research has come to rely heavily on large-scale, web-based datasets. These datasets can present significant methodological challenges, requiring researchers to make a number of decisions about how they are collected, represented, and analyzed. These decisions often concern long-standing challenges in corpus-based language research,…
Descriptors: Data Analysis, Data Collection, Word Frequency, Prediction
Walston, Jill; Conley, Marshal – Regional Educational Laboratory Southwest, 2022
This toolkit is designed to guide educators in developing and improving practical measurement instruments for use in networked improvement communities (NICs) and other education contexts in which principles of continuous improvement are applied. Continuous improvement includes distinct repeating processes: understanding the problem, identifying…
Descriptors: Measurement Techniques, Measurement, Educational Improvement, Communities of Practice
Swenson, Sandra; He, Yi; Boyd, Heather; Good, Kate Schowe – Journal of College Science Teaching, 2022
Students reasoning with data in an authentic science environment had the opportunity to learn about the process of science and the world around them while developing skills to analyze and interpret self-collected and secondhand data. Our results show that nearly 50% of the treatment group responses were accurate when describing the reason for…
Descriptors: Design, Heuristics, Data Analysis, Data Interpretation