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Making Visible and Modeling the Underrepresented: Teachers' Reflections on Their Role Modeling in Higher Education
KTH, School of Industrial Engineering and Management (ITM), Learning, Learning in Stem.ORCID iD: 0000-0001-6874-2885
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2022 (English)In: ITiCSE '22: Proceedings of the 27th ACM Conference on on Innovation and Technology in Computer Science Education, Association for Computing Machinery , 2022, Vol. 2, p. 566-567Conference paper, Published paper (Refereed)
Abstract [en]

This work contributes to a better understanding of computing teachers' perceptions of themselves as role models. Role models are described as important to address under-representation, yet there is little in-depth research on how role modeling works and what university teachers in computing can model to broaden participation in the discipline. We will analyze teachers' reflections on how they may, or want to, be perceived by their students, particularly in terms of professional competencies, emotions and attitudes towards well-being. We will use and further develop an already existing framework on role modeling in computing, and we will relate our findings to existing research on computing and science identities. Modeling aspects outside the computing norm can help provide students with a wider notion of what it means to be a computer scientist. Besides developing the theoretical understanding of computing teachers as role models , our work can support various ways of developing computing teachers' competences and departments' teaching culture. The results are one way to contribute to student diversity and equitable access, and more broadly increase the relevance of computing education for sustainability.

Place, publisher, year, edition, pages
Association for Computing Machinery , 2022. Vol. 2, p. 566-567
Series
Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE, ISSN 1942-647X ; 2
Keywords [en]
emotions, higher education, professional competencies, role model, teacher
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-317533DOI: 10.1145/3502717.3532170Scopus ID: 2-s2.0-85134539582OAI: oai:DiVA.org:kth-317533DiVA, id: diva2:1695357
Conference
27th ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE 2022, 8 July 2022 through 13 July 2022, Dublin, Ireland
Note

QC 20220913

Part of proceedings: ISBN 978-145039200-6

Available from: 2022-09-13 Created: 2022-09-13 Last updated: 2022-09-13Bibliographically approved

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Peters, Anne-Kathrin

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
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  • Other locale
More languages
Output format
  • html
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  • asciidoc
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