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Supporting Second Language Learners through SKANDIBOT: A Lexicographical Design Approach
Copenhagen Business Sch, Dept Management Soc & Commun, Copenhagen, Denmark..
KTH, School of Electrical Engineering and Computer Science (EECS), Human Centered Technology, Media Technology and Interaction Design, MID.ORCID iD: 0000-0002-8543-3774
2022 (English)In: Proceedings - 2022 International Conference on Advanced Learning Technologies, ICALT 2022 / [ed] Chang, M Chen, NS Dascalu, M Sampson, DG Tlili, A Trausan-Matu, S, Institute of Electrical and Electronics Engineers (IEEE) , 2022, p. 239-241Conference paper, Published paper (Refereed)
Abstract [en]

Migrant professional language learners need to be supported in acquiring a second language effectively beyond the classroom. These learners frequently lack opportunities to participate in language classes due to full-time jobs. Yet, quick acquisition of the target language is a needed prerequisite for their successful integration into job settings and the host society. To assist these learners in their smooth acquisition of the target language, this study takes advantage of the recent developments in artificial intelligence and presents the design of a chatbot, called SKANDIBOT aimed at fostering second language learners' conversational practice in professional work settings of Sweden and Denmark. The results of this work-in-progress study indicate that both healthcare and learning professionals perceive the overall interaction design of SKANDIBOT and the information offered in it to be useful for their second language acquisition.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2022. p. 239-241
Series
IEEE International Conference on Advanced Learning Technologies, ISSN 2161-3761
Keywords [en]
Chatbots, Second Language Learning Acquisition, Lexicographical design
National Category
General Language Studies and Linguistics
Identifiers
URN: urn:nbn:se:kth:diva-322326DOI: 10.1109/ICALT55010.2022.00078ISI: 000885102700072Scopus ID: 2-s2.0-85136920887OAI: oai:DiVA.org:kth-322326DiVA, id: diva2:1718047
Conference
22nd IEEE International Conference on Advanced Learning Technologies (ICALT), JUL 01-04, 2022, Bucharest, Romania
Note

QC 20221212

Part of proceedings: ISBN 978-1-6654-9519-6

Available from: 2022-12-12 Created: 2022-12-12 Last updated: 2022-12-12Bibliographically approved

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Viberg, Olga

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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
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf