Teaching computer science in the victorian certificate of education: A pilot study

Richard Cox, Steven Bird, Bernd Meyer

    Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedings

    Abstract

    A new computer science curriculum has been developed for the Victorian Certificate of Education. It gives students direct entry into second year University computer science. The curriculum focuses on data structures and algorithms, with an emphasis on the graph abstract data type and graph algorithms. We taught a pilot course during 2014 involving students from seven schools, and administered an algorithmic thinking quiz on entry and exit, and also tested a first year university reference group. In this paper we present the curriculum and report on the evaluation. We discuss the effectiveness of our approach and make recommendations for improving future versions of the course. Pedagogical issues are discussed in relation to the cognitive education literature on the teaching of algorithmic thinking.

    Original languageEnglish
    Title of host publicationSIGCSE 2017 - Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education
    Place of PublicationSeattle, United States
    PublisherAssociation for Computing Machinery (ACM)
    Pages135-140
    Number of pages6
    ISBN (Electronic)9781450346986
    DOIs
    Publication statusPublished - 8 Mar 2017
    Event48th ACM SIGCSE Technical Symposium on Computer Science Education, SIGCSE 2017 - Seattle, United States
    Duration: 8 Mar 201711 Mar 2017

    Conference

    Conference48th ACM SIGCSE Technical Symposium on Computer Science Education, SIGCSE 2017
    CountryUnited States
    CitySeattle
    Period8/03/1711/03/17

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  • Cite this

    Cox, R., Bird, S., & Meyer, B. (2017). Teaching computer science in the victorian certificate of education: A pilot study. In SIGCSE 2017 - Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education (pp. 135-140). Association for Computing Machinery (ACM). https://doi.org/10.1145/3017680.3017735