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Board 326: K-12 Teachers and Data Science: Learning Interdiscplinary Science Through Research Experiences

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Conference

2024 ASEE Annual Conference & Exposition

Location

Portland, Oregon

Publication Date

June 23, 2024

Start Date

June 23, 2024

End Date

June 26, 2024

Conference Session

NSF Grantees Poster Session

Tagged Topics

Diversity and NSF Grantees Poster Session

Page Count

7

DOI

10.18260/1-2--46906

Permanent URL

https://peer.asee.org/46906

Download Count

67

Paper Authors

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Katherine G. Herbert-Berger Montclair State University

biography

Thomas J Marlowe Seton Hall University Orcid 16x16 orcid.org/0000-0002-1514-9866

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Thomas J Marlowe is Professor Emeritus of Mathematics and Computer Science at Seton Hall University, with PhDs in each discipline from Rutgers University. His research has spanned many areas, including coalgebra theory, algorithms, program optimization and compilers, real-time systems, software engineering, computer science pedagogy, and interdisciplinary studies.

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Vaibhav Anu Montclair State University

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An Assistant Professor of Computer Science at Montclair State University, Dr. Anu co-directs the Software Systems lab at the Center for Computing and Information Science.

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Stefan A Robila Montclair State University

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Abstract

K-12 Teachers and Data Science: Learning Interdiscplinary Science through Research Experiences Authors: Katherine G. Herbert-Berger, Vaibhav K. Anu, Sumi Hagiwara, Rebecca A. Goldstein, Minsun Shin, Stefan Robila, Jason T.L. Wang, Thomas J. Marlowe

Data science is now pervasive across STEM, and early exposure and education in its basics will be important for the future workforce, academic programs, and scholarly research in engineering, technology, and the formal and natural sciences, and in fact, across the full spectrum of disciplines. When combined with an emphasis on soft skills and an interdisciplinary focus, such educational experiences have deeper and more meaningful effects. Our Montclair State University NSF Research Experience for Teachers (RET) grant (NSF Award Number: #2206885, IRB Number: 22-23-3003) exposed teachers to a program integrating solar weather, data science, computer science and artificial intelligence, and STEM pedagogy. The cohort comprised nine middle- and high-school teachers with diverse academic backgrounds and demographics from northern and central New Jersey. The teachers interacted with and were advised by faculty from Montclair and two other institutions, and with outside experts, to learn the basics, develop lesson plans and present these to and interact with a learning-intensive summer camp. As a capstone, the teachers have synthesized research projects from this interdisciplinary content together with their own interests and background. As a result, the teachers have submitted a number of posters with abstracts to the 2024 ACM SIGCSE and IEEE ISEC conferences, and will be presenting grant-related lessons in their classes during the current academic year.

Herbert-Berger, K. G., & Marlowe, T. J., & Anu, V., & Robila, S. A. (2024, June), Board 326: K-12 Teachers and Data Science: Learning Interdiscplinary Science Through Research Experiences Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--46906

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