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Teaching Computer Science with Abstract Strategy Games

Garcia, Dan and Bezakova, Ivona and Blank, Adam and Terrell, Neal (2021) Teaching Computer Science with Abstract Strategy Games. In: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education. Association for Computing Machinery , New York, NY, pp. 1232-1233. ISBN 9781450380621. https://resolver.caltech.edu/CaltechAUTHORS:20210310-104208957

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Abstract

Abstract Strategy Games are games of no chance with complete information - all players (usually two) know all there is about the current position; nothing is hidden. Examples of popular games are Tic-Tac-Toe, Chess, Checkers, Connect-4, Reversi, Mancala, Nim, Dots-and-Boxes, and Go; there are thousands more. In addition to the cultural history and remarkably beautiful mathematics locked within the strategies and game trees, we have found they form a wonderfully fertile, rich, and engaging source of activities around which to teach fundamentals of computer science. This panel will explore the ways in which we have used these games with our students, through interactive tutorials and reflection that will each surface a particular CS concept. After sharing best practices, we will invite the audience to contribute their own experiences.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1145/3408877.3432572DOIArticle
Additional Information:© 2021 Copyright is held by the owner/author(s).
Subject Keywords:abstract strategy games, computational game theory, artificial intelligence, CS 1, CS 2, software engineering
DOI:10.1145/3408877.3432572
Record Number:CaltechAUTHORS:20210310-104208957
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210310-104208957
Official Citation:Dan Garcia, Ivona Bezakova, Adam Blank, and Neal Terrell. 2021. Teaching Computer Science with Abstract Strategy Games. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (SIGCSE '21). Association for Computing Machinery, New York, NY, USA, 1232–1233. DOI:https://doi.org/10.1145/3408877.3432572
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:108384
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:10 Mar 2021 19:07
Last Modified:16 Nov 2021 19:11

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