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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
Direct linkGuiyun 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
Frank Lee; Alex Algarra – Information Systems Education Journal, 2024
Exploratory data analysis (EDA), data visualization, and visual analytics are essential for understanding and analyzing complex datasets. In this project, we explored these techniques and their applications in data analytics. The case discusses Tableau, a powerful data visualization tool, and Google BigQuery, a cloud-based data warehouse that…
Descriptors: Visual Aids, Data Use, Data Collection, Naming
Wen-Chiang Ivan Lim; Neil T. Heffernan III; Ivan Eroshenko; Wai Khumwang; Pei-Chen Chan – Grantee Submission, 2025
Intelligent tutoring systems are increasingly used in schools, providing teachers with valuable analytics on student learning. However, many teachers lack the time to review these reports in detail due to heavy workloads, and some face challenges with data literacy. This project investigates the use of large language models (LLMs) to generate…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Assignments, Learning Management Systems
Cassandra Artman Collier – Journal of Information Systems Education, 2024
When we imagine the work of a data analyst, we often picture meaningful data analysis and beautiful data visualizations. Although that is an exciting part of the job, data analysts actually spend the majority of their time acquiring, cleaning, and preparing data for analysis. This teaching case guides students through some of the most common data…
Descriptors: Data Analysis, Visual Aids, Web Sites, Data Processing
Mostafa M. Samy; Mohamed A. Metwally; Mahmoud Ashry; Wael M. Elmayyah – Measurement: Interdisciplinary Research and Perspectives, 2025
Gas Turbine Engines (GTE) have the highest power-to-weight ratio among Internal Combustion Engines (ICE). Its modularity and ability to utilize various types of fuel make it highly recommended in power plants, naval transportation, and, of course, the most equipped in aviation. The lack of GTEs' real data is increasing a recognized need for…
Descriptors: Engines, Power Technology, Data Collection, Data Interpretation
Margaret Marchant; Ethan Eliason – Journal of Education for Business, 2024
Undergraduate economics programs prepare students for future careers by developing competency working with data, or "data literacy." Our research examined the data literacy components of undergraduate economics programs at R1 and R2 universities in the United States (N = 190). We developed a protocol with core data skills and coded…
Descriptors: Undergraduate Students, Economics Education, Data Collection, Data Interpretation
Beth Chance; Andrew Kerr; Jett Palmer – Journal of Statistics and Data Science Education, 2024
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…
Descriptors: Publications, Public Opinion, Surveys, Bias
Sumitra Tatapudy; Rachel Potter; Linnea Bostrom; Anne Colgan; Casey J. Self; Julia Smith; Shangmou Xu; Elli J. Theobald – CBE - Life Sciences Education, 2024
The underrepresentation and underperformance of low-income, first-generation, gender minoritized, Black, Latine, and Indigenous students in Science, Technology, Engineering, and Mathematics (STEM) occurs for a variety of reasons, including, that students in these groups experience opportunity gaps in STEM classes. A critical approach to disrupting…
Descriptors: Equal Education, Outcomes of Education, Visualization, Reflection
Sainan Xu; Jing Lu; Jiwei Zhang; Chun Wang; Gongjun Xu – Grantee Submission, 2024
With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…
Descriptors: Educational Assessment, Bayesian Statistics, Statistical Inference, Item Response Theory
Hemy Ramiel; Eran Fisher – Learning, Media and Technology, 2024
This paper adds an algorithmic epistemology perspective to previous works that examine the datafication of subjective social and emotional characteristics, perceptions, and behaviours. The paper employs a comparative epistemological approach to explore two behavioural educational platforms: RedCritter Teacher and Panorama Education. We unpack…
Descriptors: Epistemology, Social Emotional Learning, Data, Higher Education
Christopher Cleveland; Jessica Markham – Annenberg Institute for School Reform at Brown University, 2024
Students with disabilities represent 15% of U.S. public school students. Individualized Education Programs (IEPs) inform how students with disabilities experience education. Very little is known about the aspects of IEPs as they are historically paper-based forms. In this study, we develop a coding taxonomy to categorize IEP goals into 10 subjects…
Descriptors: Individualized Education Programs, Special Needs Students, Special Education, Taxonomy
Christine M. White; Stephanie A. Estrera; Christopher Schatschneider; Sara A. Hart – Grantee Submission, 2024
Researchers in the education sciences, like those in other disciplines, are increasingly encountering requirements and incentives to make the data supporting empirical research available to others. However, the process of preparing and sharing research data can be daunting. The present article aims to support researchers who are beginning to think…
Descriptors: Data, Educational Research, Information Dissemination, Incentives
