Publication Date
| In 2026 | 0 |
| Since 2025 | 1 |
| Since 2022 (last 5 years) | 1 |
| Since 2017 (last 10 years) | 1 |
| Since 2007 (last 20 years) | 2 |
Descriptor
| Learning Modules | 2 |
| Theory Practice Relationship | 2 |
| Courses | 1 |
| Curriculum Enrichment | 1 |
| Data Analysis | 1 |
| Data Science | 1 |
| Distance Education | 1 |
| Engineering Education | 1 |
| Faculty | 1 |
| Interdisciplinary Approach | 1 |
| Meteorology | 1 |
| More ▼ | |
Source
| IEEE Transactions on Education | 2 |
Author
| Biggerstaff, M. I. | 1 |
| Caitlin Snyder | 1 |
| Chilson, P. B. | 1 |
| Christopher P. Vanags | 1 |
| Emily C. Kern | 1 |
| Erin C. Henrick | 1 |
| Erin R. Hotchkiss | 1 |
| Fink, L. D. | 1 |
| Gautam Biswas | 1 |
| Habtamu Alemu Workneh | 1 |
| Kang Xia | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 2 |
| Reports - Descriptive | 1 |
| Reports - Research | 1 |
Education Level
| Higher Education | 2 |
| Postsecondary Education | 1 |
Audience
Location
| Oklahoma | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Direct linkMd. 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
Yeary, M. B.; Yu, T.; Palmer, R. D.; Monroy, H.; Ruin, I.; Zhang, G.; Chilson, P. B.; Biggerstaff, M. I.; Weiss, C.; Mitchell, K. A.; Fink, L. D. – IEEE Transactions on Education, 2010
Students are not exposed to enough real-life data. This paper describes how a community of scholars seeks to remedy this deficiency and gives the pedagogical details of an ongoing project that commenced in the Fall 2004 semester. Fostering deep learning, this multiyear project offers a new active-learning, hands-on interdisciplinary laboratory…
Descriptors: Meteorology, Data Analysis, Prediction, Natural Disasters
