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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
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
Direct linkZack 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
John J. Cheslock – Research in Higher Education, 2025
The IPEDS Finance survey is a key resource for academic research, policy analysis, and efforts to improve transparency and accountability. However, the data from the survey can be difficult to use properly. This research note addresses a specific challenge: how to incorporate the $16 billion in revenues and expenditures reported annually within…
Descriptors: Institutional Characteristics, Postsecondary Education, Data Collection, Educational Finance
Ge Bai – International Journal of Web-Based Learning and Teaching Technologies, 2025
This study focuses on the construction of the learner-centered teaching college English teaching mode under big data technology. Traditional college English teaching has issues, such as standardized teaching ignoring individual differences and lagging feedback. However, the development of big data technology offers opportunities for teaching…
Descriptors: Student Centered Learning, English Instruction, College Instruction, College Students
Martin Abt; Katharina Loibl; Timo Leuders; Wim Van Dooren; Frank Reinhold – Educational Studies in Mathematics, 2025
In the boxplot, the box always represents -- regardless of its area -- the middle half of the data and thus a measure of variability (interquartile range). However, when students first learn about boxplots, they are usual already familiar with other forms of statistical representations (e.g., bar or circle graphs) in which a larger area represents…
Descriptors: College Students, Data Analysis, Graphs, Error Patterns
Sean M. Baser; Mónica Maldonado; Matt T. Dean; William B. Walker Jr.; Erik C. Ness – State Higher Education Executive Officers, 2025
States serve as the central authority in higher education oversight, playing a critical role in consumer protection and quality assurance within the regulatory triad and as an independent regulatory entity. However, there is a notable gap in understanding the components of renewal processes, how agencies implement them in practice, and the…
Descriptors: State Agencies, Accountability, State Regulation, Governance
Sean M. Baser – State Higher Education Executive Officers, 2025
Student outcome data is essential for decision-making in higher education, informing choices at the student, institutional, and state levels. Within state authorization--the gatekeeping process for institutional entry, continued operation, and closure--these data support oversight, accountability, and consumer transparency. This brief summarizes…
Descriptors: Data Use, State Regulation, Governance, Higher Education
Anna Khalemsky; Roy Gelbard; Yelena Stukalin – Journal of Statistics and Data Science Education, 2025
Classification, a fundamental data analytics task, has widespread applications across various academic disciplines, such as marketing, finance, sociology, psychology, education, and public health. Its versatility enables researchers to explore diverse research questions and extract valuable insights from data. Therefore, it is crucial to extend…
Descriptors: Classification, Undergraduate Students, Undergraduate Study, Data Science
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
Kalista Peña – Tribal College Journal of American Indian Higher Education, 2025
Native nations have long proven their resilience against the odds, consistently paving a path forward and exercising their sovereign rights as autonomous, self-governing peoples. As the world embarks upon an increasingly digital age, Indigenous peoples face a new threat: datafication. Datafication is "turning nearly every aspect of human life…
Descriptors: Minority Serving Institutions, Tribally Controlled Education, Tribal Sovereignty, Data Use
Eirini Kalaitzopoulou; Athanasios Christopoulos; Paul Matthews – Informatics in Education, 2025
While research on Learning Analytics (LA) is plentiful, it often prioritises perspectives on LA systems over the practical ways instructors use data to analyse and refine the learning process per se. The present study addresses this inadequacy by investigating how student data is employed by educators in UK Higher Education Institutions (HEIs) and…
Descriptors: Information Literacy, Learning Analytics, Data Use, College Faculty
Kaitlyn Coburn; Kris Troy; Carly A. Busch; Naomi Barber-Choi; Kevin M. Bonney; Brock Couch; Marcos E. García-Ojeda; Rachel Hutto; Lauryn Famble; Matt Flagg; Tracy Gladding; Anna Kowalkowski; Carlos Landaverde; Stanley M. Lo; Kimberly MacLeod; Blessed Mbogo; Taya Misheva; Andy Trinh; Rebecca Vides; Erik Wieboldt; Cara Gormally; Jeffrey Maloy – CBE - Life Sciences Education, 2025
Trans* and genderqueer student retention and liberation is integral for equity in undergraduate education. While STEM leadership calls for data-supported systemic change, the erasure and othering of trans* and genderqueer identities in STEM research perpetuates cisnormative narratives. We sought to characterize how sex and gender data are…
Descriptors: LGBTQ People, Transgender People, Disproportionate Representation, Educational Research
SeHee Jung; Hanwen Wang; Bingyi Su; Lu Lu; Liwei Qing; Xiaolei Fang; Xu Xu – TechTrends: Linking Research and Practice to Improve Learning, 2025
This study presents a mobile application (app) that facilitates undergraduate students to learn data science using their own full-body motion data. The app captures a user's movements through the built-in camera of a mobile device and processes the images for data generation using BlazePose, an open-source computer vision model for real-time pose…
Descriptors: Undergraduate Students, Data Science, Handheld Devices, Open Source Technology
Jing Chen; Tianhui Chen – Journal of Computer Assisted Learning, 2025
Background: The creation of Intelligent Supervision Platforms in universities leverages Big Data for robust monitoring and decision-making, which significantly enhances overall efficiency and adaptability in educational environments. Objectives: This research focuses on evaluating how Big Data-driven Intelligent Supervision Platforms in…
Descriptors: Educational Change, Higher Education, Universities, Supervision
