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Direct linkMona 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
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
Stella Y. Kim; Sungyeun Kim – Educational Measurement: Issues and Practice, 2025
This study presents several multivariate Generalizability theory designs for analyzing automatic item-generated (AIG) based test forms. The study used real data to illustrate the analysis procedure and discuss practical considerations. We collected the data from two groups of students, each group receiving a different form generated by AIG. A…
Descriptors: Generalizability Theory, Automation, Test Items, Students
Zack J. Damon; Michael E. Ellis – Sport Management Education Journal, 2025
Sport analytics remains a growing area in the sport industry. As such, the demand for skills and knowledge in this area has grown. This demand includes off-field data, such as marketing trends, as well as financial data related to sport organizations. There has been a trickle-down effect in sport management (and other) education programs to teach…
Descriptors: Athletics, Data Collection, Data Analysis, Coding
Download full textKamila 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
Natividad Hernández Muñoz; Carmela Tomé Cornejo – Educational Linguistics, 2025
The development of research methodology in any scientific field is closely tied to technological advancements that allow for deeper and more sophisticated data analysis. To help readers understanding the scope of current lexical availability research, this chapter provides a description of the tools and research resources specifically developed…
Descriptors: Reading Research, Research Methodology, Data Collection, Data Analysis
Manel van Kessel; Inge Molenaar; Carolien A. N. Knoop-van Campen; Mario de Jonge; Nadira Saab – Journal of Learning Analytics, 2025
Adaptive learning technologies (ALTs) provide teachers with student data in teacher dashboards (TDs). However, there is substantial variation in dashboard use among teachers, and many find it difficult to draw conclusions based on student data. Teachers' skills, knowledge, and contextual conditions are believed to be essential in effective…
Descriptors: Elementary School Teachers, Technology Uses in Education, Teacher Attitudes, Data Collection
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
Mireia Bolíbar; Julia Martínez-Ariño; Maria Schiller – Field Methods, 2025
We propose a new method for analyzing and visualizing information on a large collection of personal networks to uncover the socio-centric structure of relationships among aggregated actors that we clustered into categories. The network of categories identifies the links between groups of sampled ego actors sharing a given attribute (e.g.,…
Descriptors: Measurement Techniques, Data Analysis, Data Collection, Networks
Jane Watson; Noleine Fitzallen – Teaching Statistics: An International Journal for Teachers, 2025
The practice of statistics has the power to motivate and support learning across the STEM (Science, Technology, Engineering, and Mathematics) disciplines. When connected with meaningful science contexts, statistical problem solving through the collection of data and subsequent data analysis, supported by contemporary graphing technology, presents…
Descriptors: Elementary School Students, Grade 5, Statistics, Statistics Education
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
Sean M. Fitzhugh; Cynthia K. Maupin; Arwen H. DeCostanza – Cognitive Research: Principles and Implications, 2025
Trust serves an important purpose in organizations composed of numerous, specialized, interdependent roles. Supporting confidence that individuals will dutifully fulfill the responsibilities of those roles without causing harm to the organization, trust enables coordinated task execution across multiple roles and facilitates information exchange…
Descriptors: Institutional Cooperation, Trust (Psychology), Information Networks, Military Training
Beixi Li; Ajit Bhattarai – Sage Research Methods Cases, 2025
The purpose of this case study is to illustrate how we practiced narrative métissage, an Indigenous research methodology, as non-Indigenous researchers. We engaged in an arts-based collaborative autoethnography to explore our growing understanding of scholarly impact using various concepts from transformative learning. In this case study, we…
Descriptors: Indigenous Knowledge, Research Methodology, Ethnography, Transformative Learning
Mark W. Isken – INFORMS Transactions on Education, 2025
A staple of many spreadsheet-based management science courses is the use of Excel for activities such as model building, sensitivity analysis, goal seeking, and Monte-Carlo simulation. What might those things look like if carried out using Python? We describe a teaching module in which Python is used to do typical Excel-based modeling and…
Descriptors: Spreadsheets, Models, Programming Languages, Monte Carlo Methods
Seth Elkin-Frankston; James McIntyre; Tad T. Brunyé; Aaron L. Gardony; Clifford L. Hancock; Meghan P. O'Donovan; Victoria G. Bode; Eric L. Miller – Cognitive Research: Principles and Implications, 2025
Existing toolkits for analyzing movement dynamics in animal ecology primarily focus on individual or group behavior in habitats without predefined boundaries, while methods for studying human activity often cater to bounded environments, such as team sports played on defined fields. This leaves a gap in tools for modeling and analyzing human group…
Descriptors: Group Dynamics, Military Personnel, Measures (Individuals), Computer Software
