Digging Deeper with Data: Engineering Research Experiences for STEM Undergraduates and Teachers

Arash Jamshidi; Elisa Stone

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Conference: 2022 ASEE Annual Conference & Exposition
Location: Minneapolis, MN
Publication Date: August 23, 2022
Start Date: June 26, 2022
End Date: June 29, 2022
Conference Session: NSF Grantees Poster Session
Page Count: 20
DOI: 10.18260/1-2--41975
Permanent URL: https://peer.asee.org/41975
Download Count: 220

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Paper Authors

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Arash Jamshidi University of California, Berkeley

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Program Director, Summer Research Institute (SRI) at the University of California, Berkeley’s CalTeach program

Arash Jamshidi is the program director for the Summer Research Institute (SRI) at the University of California, Berkeley’s CalTeach program. With SRI, Arash oversees an NSF-funded collaboration between San Francisco Bay Area public school STEM teachers, undergraduate STEM majors, and university researchers to connect lab research practices to K-12 instruction. Additionally, as a faculty member at UC Berkeley, Arash instructs and supports pre-service teachers as they transition towards a career in the classroom. Alongside his work with SRI, Arash is also part of the OpenSciEd initiative, a multi-state collaboration to create research-based, open-source science instructional materials aligned to the Framework for K-12 Science Education and the NGSS. With OpenSciEd, Arash helps develop high-quality, NGSS-designed curriculum and delivers professional development for teachers, as well as state and district leaders around the United States. Previously, Arash worked at the Stanford Center for Assessment, Learning, and Equity (SCALE) focusing on NGSS-aligned curriculum and assessments, while also supporting teachers through professional learning. While with SCALE, Arash co-developed the NGSS-aligned middle school science curriculum for the San Francisco Unified School District, and reviewed and contributed to the Stanford NGSS Integrated Curriculum: An Exploration of a Multidimensional World.

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Elisa Stone University of California, Berkeley

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Abstract

It has become increasingly important for K-12 students to learn how to investigate patterns, correlations, and significance in data. The Berkeley Engineering Research Experiences for Teachers plus Data (BERET+D) pairs undergraduate pre-service teachers and experienced in-service science and mathematics teachers (PSTs and ISTs) to engage in engineering and data science research, exploring and analyzing data sets drawn from a variety of STEM fields and laboratories across the UC Berkeley campus. In addition to conducting independent summer research projects with guidance from university research faculty, the program provides opportunities for: (1) PSTs to develop data science-based lessons inspired by their research and aligned to the Next Generation Science Standards (NGSS), (2) ISTs to create data science-based curricula designed to inspire middle and high school students to see STEM classes as exciting and with real-life applications, and (3) ISTs to collaborate with and mentor PSTs preparing to enter K-12 STEM classrooms. Contributing towards broader impacts, CalTeach recruits a racially and socioeconomically diverse population of PSTs, and all ISTs were recruited from local public schools, in order to educate, prepare, and encourage more minority and female K-12 students to consider higher education and careers in STEM.

During the first two summers of this project (2020-2021), participants completed over forty data-science related projects, developed over thirty K-12 data-science related lesson plans in math, science, and engineering, and created six classroom-ready and publicly accessible (teachengineering.org) curricular units showcasing data science. As an example of these curricular units, and as further evidence of the project’s broader impact, one IST has developed an ongoing partnership between their classroom and a research laboratory on campus allowing high school physics students to learn data science techniques by analyzing and interpreting distant satellite signals collected by radio telescopes. Preliminary evaluation of this ongoing project revealed that participants viewed data science as important and essential in K-12 curriculum, that data analysis is a critical and useful skill for youth, and that data science aligns closely with the science and engineering practices called forth by NGSS. Though constrained by work-from-home restrictions due to COVID during the first two years, participants described their experience as positive and valuable, particularly in conceiving of ways to engage young learners with data-science through remote instruction.

Citation
Format

Jamshidi, A., & Stone, E. (2022, August), Digging Deeper with Data: Engineering Research Experiences for STEM Undergraduates and Teachers Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41975

TY  - CPAPER
AB  - It has become increasingly important for K-12 students to learn how to investigate patterns, correlations, and significance in data. The Berkeley Engineering Research Experiences for Teachers plus Data (BERET+D) pairs undergraduate pre-service teachers and experienced in-service science and mathematics teachers (PSTs and ISTs) to engage in engineering and data science research, exploring and analyzing data sets drawn from a variety of STEM fields and laboratories across the UC Berkeley campus. In addition to conducting independent summer research projects with guidance from university research faculty, the program provides opportunities for: (1) PSTs to develop data science-based lessons inspired by their research and aligned to the Next Generation Science Standards (NGSS), (2) ISTs to create data science-based curricula designed to inspire middle and high school students to see STEM classes as exciting and with real-life applications, and (3) ISTs to collaborate with and mentor PSTs preparing to enter K-12 STEM classrooms. Contributing towards broader impacts, CalTeach recruits a racially and socioeconomically diverse population of PSTs, and all ISTs were recruited from local public schools, in order to educate, prepare, and encourage more minority and female K-12 students to consider higher education and careers in STEM.

During the first two summers of this project (2020-2021), participants completed over forty data-science related projects, developed over thirty K-12 data-science related lesson plans in math, science, and engineering, and created six classroom-ready and publicly accessible (teachengineering.org) curricular units showcasing data science. As an example of these curricular units, and as further evidence of the project’s broader impact, one IST has developed an ongoing partnership between their classroom and a research laboratory on campus allowing high school physics students to learn data science techniques by analyzing and interpreting distant satellite signals collected by radio telescopes. Preliminary evaluation of this ongoing project revealed that participants viewed data science as important and essential in K-12 curriculum, that data analysis is a critical and useful skill for youth, and that data science aligns closely with the science and engineering practices called forth by NGSS. Though constrained by work-from-home restrictions due to COVID during the first two years, participants described their experience as positive and valuable, particularly in conceiving of ways to engage young learners with data-science through remote instruction.
AU  - Arash Jamshidi
AU  - Elisa Stone
CY  - Minneapolis, MN
DA  - 2022/08/23
PB  - ASEE Conferences
TI  - Digging Deeper with Data: Engineering Research Experiences for STEM Undergraduates and Teachers
UR  - https://peer.asee.org/41975
DO  - 10.18260/1-2--41975
ER  -