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A Case for Deep Learning Through Online Oral Examinations: An Autoethnographical Exploration of a Change of Assessment Method
Södertörn University, School of Social Sciences, Public Administration.ORCID iD: 0000-0003-0634-4157
2023 (English)In: Högre Utbildning, E-ISSN 2000-7558, Vol. 13, no 3, p. 72-86Article in journal (Refereed) Published
Abstract [en]

The Covid-19 pandemic made digital oral exams a necessity for most higher education courses in Sweden and elsewhere in the world. Yet, more reflection on oral examination could help understand their utility in contemporary higher education. This paper probes the relationship between learning habits and assessment through an autoethnographic exploration into oral examination in an intermediate quantitative methods class for social science students in Sweden. Drawing on theories on constructive alignment and deep learning, this article makes the case for oral examinations as facilitating deep(er) learning. At the same time, the article discusses the oral examination as a critical way to think about the formal assessment culture brought about by ever tightening teaching budgets and external audits.

Place, publisher, year, edition, pages
Cappelen Damm Akademisk, 2023. Vol. 13, no 3, p. 72-86
Keywords [en]
deep-learning, online oral examination, constructive alignment, quantitative methods, methods teaching
National Category
Pedagogy
Research subject
Studies in the Educational Sciences
Identifiers
URN: urn:nbn:se:sh:diva-52996DOI: 10.23865/hu.v13.3172Scopus ID: 2-s2.0-85181891195OAI: oai:DiVA.org:sh-52996DiVA, id: diva2:1824311
Available from: 2024-01-04 Created: 2024-01-04 Last updated: 2024-07-01Bibliographically approved

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Turunen, Jaakko

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • harvard-anglia-ruskin-university
  • apa-old-doi-prefix.csl
  • sodertorns-hogskola-harvard.csl
  • sodertorns-hogskola-oxford.csl
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf