HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Conference papers

A Semi-automated Approach to Categorise Learning Outcomes into Digital Literacy or Computer Science

Abstract : Computer science related curricula, standards and frameworks are designed and implemented in many countries to incorporate informatics education in schools, already starting with kindergarten and primary education. A recurring point of discussion addresses the focus of those educational models concerning the different fields of computer science - the topics related to the scientific subject of computer science, or digital literacy (the set of skills and competencies needed in everyday life in the digital age). In this paper, we present a semi-automated approach to categorise learning outcomes of computer science related curricula into one of those two categories. Categorisation is performed with linguistic metrics computed for nouns and verbs of representative curricula of each category. The categorisation is compared against classifications of nine experts of computer science teaching and research. The results show a matching categorisation for 70% of all learning outcomes and 90% of learning outcomes uniformly classified by the experts.
Document type :
Conference papers
Complete list of metadata

Cited literature [19 references]  Display  Hide  Download

Contributor : Hal Ifip Connect in order to contact the contributor
Submitted on : Tuesday, November 19, 2019 - 4:12:58 PM
Last modification on : Tuesday, November 19, 2019 - 4:26:16 PM


Files produced by the author(s)


Distributed under a Creative Commons Attribution 4.0 International License



Stefan Pasterk, Max Kesselbacher, Andreas Bollin. A Semi-automated Approach to Categorise Learning Outcomes into Digital Literacy or Computer Science. Open Conference on Computers in Education (OCCE), Jun 2018, Linz, Austria. pp.77-87, ⟨10.1007/978-3-030-23513-0_8⟩. ⟨hal-02370911⟩



Record views


Files downloads