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CSTA: Connecting Colleges and K-12 CS Teachers (Abstract Only)

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Published:21 February 2018Publication History

ABSTRACT

The Computer Science Teachers Association (CSTA) is an ACM-affiliated member organization of more than 26,000 educators and supporters of K-12 computer science. CSTA supports local communities of educators and partners through more than 70 local chapters, made up of educators, administrators, college faculty, and industry supporters, which meet regularly for networking and professional development. In addition, CSTA provides valuable resources to teachers and CS advocates, such as the newly revised K-12 CS Standards, research reports, a member listserv, a bimonthly newsletter, and recorded sessions from the annual conference. This session will provide a brief overview of CSTA, its chapters, and available resources for teachers. College faculty who are interested in connecting with local K-12 teachers will be encouraged to network and explore mutually beneficial partnerships. An open forum will follow for discussing CSTA's mission, possible initiatives, and benefits to K-12 and college educators. The major goals of this Birds-of-a-Feather session are:

  • To inform K-12 teachers and college faculty of the current initiatives underway at CSTA, as well as possible initiatives that are under development.

  • To allow K-12 teachers and college faculty with common interests to connect and potentially partner in supporting computer science in K-12.

  • To provide a forum for discussing the needs and desires of K-12 educators, which will then inform future CSTA initiatives and college partnerships.

  • To receive feedback from the community on current and possible initiatives.

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  1. CSTA: Connecting Colleges and K-12 CS Teachers (Abstract Only)

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      • Published in

        cover image ACM Conferences
        SIGCSE '18: Proceedings of the 49th ACM Technical Symposium on Computer Science Education
        February 2018
        1174 pages
        ISBN:9781450351034
        DOI:10.1145/3159450

        Copyright © 2018 Owner/Author

        Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 21 February 2018

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        • abstract

        Acceptance Rates

        SIGCSE '18 Paper Acceptance Rate161of459submissions,35%Overall Acceptance Rate1,595of4,542submissions,35%

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