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A Graph-based Approach to Analyze and Compare Computer Science Curricula for Primary and Lower Secondary Education

Published:28 June 2017Publication History

ABSTRACT

A growing number of countries start to introduce computer science related topics in primary education, but their curricula or educational standards significantly differ in various aspects. This contribution introduces a way to analyze and compare curricula, education standards and competency models, using a graph-based representation form and several graph-theoretical metrics.

References

  1. J. M. Lightfoot. A Graph-Theoretic Approach to Improved Curriculum Structure and Assessment Placement. Comm. of the IIMA, 10(2):59--73, 2010.Google ScholarGoogle Scholar
  2. L. Marshall. A comparison of the core aspects of the acm/ieee computer science curriculum 2013 strawman report with the specified core of cc2001 and cs2008 review. In Proceedings of Second Computer Science Education Research Conference, CSERC '12, pages 29--34, New York, NY, USA, 2012. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. A Graph-based Approach to Analyze and Compare Computer Science Curricula for Primary and Lower Secondary Education

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        • Published in

          cover image ACM Conferences
          ITiCSE '17: Proceedings of the 2017 ACM Conference on Innovation and Technology in Computer Science Education
          June 2017
          412 pages
          ISBN:9781450347044
          DOI:10.1145/3059009

          Copyright © 2017 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.

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 28 June 2017

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          ITiCSE '17 Paper Acceptance Rate56of175submissions,32%Overall Acceptance Rate552of1,613submissions,34%

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