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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
Erin L. Castro; Amy Lerman – Metropolitan Universities, 2025
The challenge: This paper examines the state of knowledge and evaluation in prison higher education. Little is known about its efforts, outcomes, and impact or about the students enrolled in such efforts. Potential consequences: Incarcerated college students are a disenfranchised population with restricted autonomy. Without understanding prison…
Descriptors: Correctional Education, Higher Education, Student Evaluation, Barriers
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
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
Kaitlyn Coburn; Kris Troy; Carly A. Busch; Naomi Barber-Choi; Kevin M. Bonney; Brock Couch; Marcos E. GarcĂa-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
Kean Birch; Janja Komljenovic; Sam Sellar; Morten Hansen – Learning, Media and Technology, 2025
The COVID pandemic highlighted the increasing deployment of digital technologies in educational institutions, defined as 'edtech'. The most visible edtech was video conferencing software, but a swathe of edtech startups have sought to roll out their products and services to educational institutions. We focus specifically on the deployment of…
Descriptors: Educational Technology, Technology Uses in Education, Higher Education, Videoconferencing
Catherine Ferguson – Issues in Educational Research, 2025
The use of artificial intelligence (AI) in higher education has mostly focused on issues associated with teaching and assessment. In this paper I used AI to support the analysis of data which consisted of public comments on a newspaper article. This small, low risk research was chosen to demonstrate the potential use of AI and how it may support…
Descriptors: Artificial Intelligence, Data Analysis, Technology Uses in Education, Higher Education
Kelli A. Bird; Benjamin L. Castleman; Yifeng Song – Journal of Policy Analysis and Management, 2025
Predictive analytics are increasingly pervasive in higher education. However, algorithmic bias has the potential to reinforce racial inequities in postsecondary success. We provide a comprehensive and translational investigation of algorithmic bias in two separate prediction models--one predicting course completion, the second predicting degree…
Descriptors: Algorithms, Technology Uses in Education, Bias, Racism
Denekew Zewdie Negassa – Educational Planning, 2025
The study addresses the challenges Addis Ababa University faculty encounters in fulfilling their community service mission. A qualitative research method with a case study design was used. Data were collected through individual interviews with vice deans, department heads, community service professionals, and academic staff. Further review of…
Descriptors: Foreign Countries, College Faculty, Deans, Department Heads
Katherine Bui; Keith R. Berry Jr. – Journal of Research Administration, 2025
Research administrators (RA) at institutions of higher education (IHE) provide critical support to faculty throughout the lifecycle of research, which include developing research, applying to funding opportunities, managing awards through closeout, and maintaining compliance. Fulfilling these tasks requires well-developed RA processes and clear…
Descriptors: COVID-19, Pandemics, Data Collection, Data Use
Xiaofang Hao – International Journal of Web-Based Learning and Teaching Technologies, 2025
Online education is an important component of education reform and one of the important learning modes in today's society, which can achieve the goal of learning anytime, anywhere and for everyone. Therefore, this paper constructs an analysis model of online education course emotional perception and course resource integration based on new media…
Descriptors: Stakeholders, Online Courses, Education Courses, Instructional Materials
Dina Fitria Murad; Meta Amalya Dewi; Arbaiah Inn; Silvia Ayunda Murad; Noor Udin; Taufik Darwis – Journal of Educators Online, 2025
This study aims to produce a more personalized recommendation system for online learning using multicriteria in collaborative filtering and data from the Binus Online Learning repository as a knowledge base. The study uses forecasting (regression) and consists of three stages: (1) collecting data on the results of the learning process; (2) adding…
Descriptors: Electronic Learning, Data Collection, Context Effect, Learning Processes
Chelsea McCracken; Ruby MacDougall – ITHAKA S+R, 2025
Research data services--support offerings which enable and improve data-intensive research--have garnered sustained attention from library research support service providers for nearly two decades. Libraries have played a leading role in developing research data services, and on most university campuses they provide the largest and most diverse…
Descriptors: Researchers, Data Analysis, Research Methodology, Universities