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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
Direct linkAnna 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
Shao-Heng Ko; Kristin Stephens-Martinez – ACM Transactions on Computing Education, 2025
Background: Academic help-seeking benefits students' achievement, but existing literature either studies important factors in students' selection of all help resources via self-reported surveys or studies their help-seeking behavior in one or two separate help resources via actual help-seeking records. Little is known about whether computing…
Descriptors: Computer Science Education, College Students, Help Seeking, Student Behavior
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
David Eubanks; Scott A. Moore – Assessment Update, 2025
Assessment and institutional research offices have too much data and too little time. Standard reporting often crowds out opportunities for innovative research. Fortunately, advancements in data science now offer a clear solution. It is equal parts technique and philosophy. The first and easiest step is to modernize data work. This column…
Descriptors: Higher Education, Educational Assessment, Data Science, Research Methodology
Wole Michael Olatokun; Oluyemi Folorunso Ayanbode; Sunday Oluwadare Oladipo – Education and Information Technologies, 2025
This study examined the data science career preference, data science skills, and core competencies of 416 students from fourteen Nigerian universities using a Google Forms-created structured online questionnaire. A convenience sampling technique was adopted to select the participants. Data were analysed using both descriptive and inferential…
Descriptors: Data Science, Preferences, College Students, Foreign Countries
Md. Yunus Naseri; Caitlin Snyder; Katherine X. Perez-Rivera; Sambridhi Bhandari; Habtamu Alemu Workneh; Niroj Aryal; Gautam Biswas; Erin C. Henrick; Erin R. Hotchkiss; Manoj K. Jha; Steven Jiang; Emily C. Kern; Vinod K. Lohani; Landon T. Marston; Christopher P. Vanags; Kang Xia – IEEE Transactions on Education, 2025
Contribution: This article discusses a research-practice partnership (RPP) where instructors from six undergraduate courses in three universities developed data science modules tailored to the needs of their respective disciplines, academic levels, and pedagogies. Background: STEM disciplines at universities are incorporating data science topics…
Descriptors: Data Science, Courses, Research and Development, Theory Practice Relationship
Ian Thacker; Rebecca Schroeder; Sara Shields-Menard; Nickolas Goforth – International Journal of Science and Mathematics Education, 2025
To create opportunities for meaningful applications of data science for diverse students, we developed and implemented an online learning module focused on engaging students at a Hispanic Serving Institution (HSI) in an analysis of authentic soil data. Development of the module occurred over three design iterations involving interviews with 10…
Descriptors: Hispanic American Students, Minority Serving Institutions, Data Science, Undergraduate Students
Toshiya Arakawa; Haruki Miyakawa – Technology, Knowledge and Learning, 2025
Data science education in Japan extends from elementary to high school students. However, some studies show that this has not enhanced interest or curiosity in data science. Therefore, gamification appears to be an efficient method for encouraging high school students' interest in data science, with research indicating that video games are…
Descriptors: Data Science, Educational Games, Statistics Education, Foreign Countries
Susie Gronseth; Amani Itani; Kathryn Seastrand; Bettina Beech; Marino Bruce; Thamar Solorio; Ioannis Kakadiaris – Journal of Interactive Learning Research, 2025
This study examines the design, implementation, and evaluation of a Digital Educational Escape Room (DEER) titled "Escape from the Doctor's Office," developed to enhance artificial intelligence/machine learning (AI/ML) literacy. Grounded in constructivist pedagogy and behaviorist principles, the DEER was designed using the ADDIE…
Descriptors: Educational Games, Artificial Intelligence, Technological Literacy, Teamwork
Nathan A. Quarderer; Leah Wasser; Anne U. Gold; Patricia Montaño; Lauren Herwehe; Katherine Halama; Emily Biggane; Jessica Logan; David Parr; Sylvia Brady; James Sanovia; Charles Jason Tinant; Elisha Yellow Thunder; Justina White Eyes; LaShell Poor Bear/Bagola; Madison Phelps; Trey Orion Phelps; Brett Alberts; Michela Johnson; Nathan Korinek; William Travis; Naomi Jacquez; Kaiea Rohlehr; Emily Ward; Elsa Culler; R. Chelsea Nagy; Jennifer Balch – Journal of Statistics and Data Science Education, 2025
Today's data-driven world requires earth and environmental scientists to have skills at the intersection of domain and data science. These skills are imperative to harness information contained in a growing volume of complex data to solve the world's most pressing environmental challenges. Despite the importance of these skills, Earth and…
Descriptors: Electronic Learning, Earth Science, Environmental Education, Science Education
