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  5. Building Computer Science K-12 PLCs in Rural Communities

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Article
English
2019

Building Computer Science K-12 PLCs in Rural Communities

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English
2019
DOI: 10.1145/3287324.3293825

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Mao Zheng
Mao Zheng

Institution not specified

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Allison Sauppé
Samantha S. Foley
T.B. Gendreau
+2 more

Abstract

Computer science is in increasing demand at the K-12 level. However, due to a lack of qualified educators, numerous programs (e.g., Google's CS4HS, NSF's CSForAll) have been created to train teachers and increase student access to computer science. Although these programs have seen some success, schools in areas with lower population density continue to struggle to offer computer science opportunities. These schools face unique challenges due to their low population density, including increasing teaching demands in core subjects, smaller teaching staff, and a smaller pipeline of students, making it difficult to justify offering a course in computer science. This poster draws on our experience of collaborating with K-12 teachers in rural schools in western Wisconsin to help mitigate these unique challenges. We have obtained two Google CS4HS grants to hold educational computer science workshops with teachers from across the region. These workshops allowed us to work closely with teachers and help them become more comfortable with incorporating computer science into their classrooms, while also helping us to form relationships with both teachers and administrators in a number of districts. Building on these relationships, we are taking the next step of working more closely with individual school districts to form professional learning communities. Our goal in this work is to connect K-12 teachers within each district and help facilitate a robust pipeline of students interested in computer science and justify offering AP CS courses at the high school level.

How to cite this publication

Allison Sauppé, Samantha S. Foley, T.B. Gendreau, Joshua T. Hertel, Mao Zheng (2019). Building Computer Science K-12 PLCs in Rural Communities. , pp. 1275-1275, DOI: 10.1145/3287324.3293825.

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Publication Details

Type

Article

Year

2019

Authors

5

Datasets

0

Total Files

0

Language

English

DOI

10.1145/3287324.3293825

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