Publication Date
| In 2026 | 0 |
| Since 2025 | 603 |
| Since 2022 (last 5 years) | 603 |
Descriptor
Source
Author
Publication Type
Education Level
Location
| United Kingdom | 12 |
| Australia | 11 |
| United States | 11 |
| California | 10 |
| Texas | 10 |
| China | 8 |
| Germany | 8 |
| Turkey | 8 |
| United Kingdom (England) | 7 |
| Europe | 6 |
| Spain | 6 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkKadir Kesgin – Discover Education, 2025
The increasing demand for privacy-preserving, ethically aligned synthetic data generation in education has highlighted the limitations of existing tabular data generators. Traditional approaches often sacrifice fairness or privacy in pursuit of predictive accuracy, rendering them unsuitable for high-stakes academic settings. In this paper, we…
Descriptors: Synthesis, Data, Data Science, Data Use
Download full textJames R. Wolf – Information Systems Education Journal, 2025
This paper introduces the LEGO® Database, a large natural dataset that can be used to teach Structured Query Language (SQL) and relational database concepts. This dataset is well-suited for introductory and advanced database assignments and end-of-semester group projects. The data is freely available from Kaggle.com and contains eight tables with…
Descriptors: Higher Education, Databases, Data Analysis, Web Sites
Kamila Misiejuk; Sonsoles López-Pernas; Rogers Kaliisa; Mohammed Saqr – Journal of Learning Analytics, 2025
Generative artificial intelligence (GenAI) has opened new possibilities for designing learning analytics (LA) tools, gaining new insights about student learning processes and their environment, and supporting teachers in assessing and monitoring students. This systematic literature review maps the empirical research of 41 papers utilizing GenAI…
Descriptors: Literature Reviews, Artificial Intelligence, Learning Analytics, Data Collection
Guiyun Feng; Honghui Chen – Education and Information Technologies, 2025
Data mining has been successfully and widely utilized in educational information systems, and an important research field has been formed, which is educational data mining. Process mining inherits the characteristics of data mining which can not only use historical data in the system to analyze learning behavior and predict academic performance,…
Descriptors: Educational Research, Artificial Intelligence, Data Use, Algorithms
Damaris D. E. Carlisle – Sage Research Methods Cases, 2025
This case study explores the use of large language models (LLMs) as analytical partners for data exploration and interpretation. Grounded in original research, it navigates the intricacies of using LLMs for uncovering themes from datasets. The study tackles various methodological and practical challenges encountered during the research process…
Descriptors: Artificial Intelligence, Natural Language Processing, Data Analysis, Data Interpretation
Michael O. Martin, Editor; Julian Fraillon, Editor; Heiko Sibberns, Editor; Betina Borisova, Contributor; Ekaterina Buzkich, Contributor; David Ebbs, Contributor; Eugenio Gonzalez, Contributor; Seamus Hegarty, Contributor; Sabine Meinck, Contributor; Sebastian Meyer, Contributor; Irini Moustaki, Contributor; Lauren Musu, Contributor; Keith Rust, Contributor; Ulrich Sievers, Contributor; Matthias von Davier, Contributor; Kentaro Yamamoto, Contributor – International Association for the Evaluation of Educational Achievement, 2025
This publication presents "IEA's Technical Standards for International Large-Scale Assessment." The initial standards, published in 1999, aimed to consolidate the best practices and methodological rigor in IEA's approach to educational assessment, addressing the unique needs of international studies. The standards presented in this…
Descriptors: International Assessment, Standards, Test Construction, Data Collection
Ali Gohar Qazi; Norbert Pachler – Professional Development in Education, 2025
This paper proposes a conceptual framework enabling the development and adoption of descriptive, diagnostic, predictive and recommendatory data analytics in teacher professional learning by harnessing some of the affordances of digital technologies to convert data into actionable insights. The paper argues for a technology-enhanced approach that…
Descriptors: Faculty Development, Data Analysis, Data Use, Models
David Williamson Shaffer; Yeyu Wang; Andrew Ruis – Journal of Learning Analytics, 2025
Learning is a multimodal process, and learning analytics (LA) researchers can readily access rich learning process data from multiple modalities, including audio-video recordings or transcripts of in-person interactions; logfiles and messages from online activities; and biometric measurements such as eye-tracking, movement, and galvanic skin…
Descriptors: Learning Processes, Learning Analytics, Models, Data
Mona Hosseini; Åsta Haukås – Journal of Academic Ethics, 2025
Participant rights and voices are protected through institutional ethical considerations in the social sciences and applied linguistics. Yet, several ethical concerns remain. In addition to adhering to institutional "macroethics," researchers should develop "microethics" to address contextual issues within their research. The…
Descriptors: Ethics, Data Collection, Data Analysis, Interviews
Secil Caskurlu; Yasin Yalçin; Jaesung Hur; Hui Shi; James D. Klein – TechTrends: Linking Research and Practice to Improve Learning, 2025
This exploratory qualitative study examined how instructional designers use data to make decisions during the instructional design process. Participants included full-time instructional designers (n = 9) who were involved in one or more phases of the ADDIE (Analysis, Design, Development, Implementation, Evaluation) across different job sectors,…
Descriptors: Data Use, Instructional Design, Decision Making, Data Collection
Martyna Daria Swiatczak; Michael Baumgartner – Sociological Methods & Research, 2025
In this paper, we investigate the conditions under which data imbalances, a common data characteristic that occurs when factor values are unevenly distributed, are problematic for the performance of Coincidence Analysis (CNA). We further examine how such imbalances relate to fragmentation and noise in data. We show that even extreme data…
Descriptors: Causal Models, Comparative Analysis, Data Analysis, Statistical Distributions
Jason Williams – Solution Tree, 2025
Author Jason Williams develops a framework that balances data-based decision making with a deep consideration for addressing students' unique needs to foster improved learning outcomes. Focusing on five qualities integral to a healthy data culture, Williams offers educators a simple, reliable way to assess and reconsider their data practices to…
Descriptors: Shared Resources and Services, Information Dissemination, Information Management, Data
Ayhan Duygulu; María Angeles Navarro Martinez; Juan Francisco Blesa Simarro; Alina Dumitrascu; Ana Rosa Gonzalez Martinez – International Education Studies, 2025
This study focuses on describing data based school management processes in Türkiye, Spain and Romania. The study group consists of 49 participants. Maximal variation and stratified sampling were applied. For internal trustworthiness, respondent validation, data triangulation and cross check were utilized. For transferability, 'expert opinions' and…
Descriptors: Foreign Countries, Administrators, Competence, Data Collection
Jeremy Seeman; Aaron R. Williams; Claire McKay Bowen – Urban Institute, 2025
The Nebraska Statewide Workforce & Educational Reporting System (NSWERS) is a state longitudinal data system (SLDS) that coordinates data sharing, processing, and dissemination efforts across the Nebraska public school systems, Nebraska community colleges, the University of Nebraska system, the Nebraska Department of Labor, and other statewide…
Descriptors: Privacy, Access to Information, Data, State Programs
Sohaib Ahmad; Javid Shabbir – Measurement: Interdisciplinary Research and Perspectives, 2025
This study aims to suggest a generalized class of estimators for population proportion under simple random sampling, which uses auxiliary attributes. The bias and MSEs are considered derived to the first degree approximation. The validity of the suggested and existing estimators is assessed via an empirical investigation. The performance of…
Descriptors: Computation, Sampling, Data Collection, Data Analysis
