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Using Thematic Analysis to Understand Students’ Learning of Soft Skills from Videos
Halmstad University, School of Education, Humanities and Social Science, Centrum för lärande, kultur och samhälle (CLKS).ORCID iD: 0000-0002-4650-2976
University of Leeds, Leeds, UK.
University of Canterbury, Christchurch, New Zealand.
2018 (English)In: Proceedings of European Conference on Technology Enhanced Learning, Cham: Springer, 2018, Vol. 11082, p. 656-659Conference paper, Published paper (Refereed)
Abstract [en]

Learning from visual and social media makes a complex area of study and a vital part of understanding the development of 21st century skills. The Active Video Watching (AVW) platform was developed in order to scaffold students’ active learning of soft skills from videos, by encouraging users to engage with the content (e.g. marking important aspects and writing comments). Previous studies of AVW used learning analytics to identify student comments which can be used in “intelligent nudges” for triggering reflection among others who watch the same video. Here, we describe the methodology and reasoning for conducting a qualitative thematic analysis of such comments, with respect to learning presentation skills. Our aim is to uncover additional learning opportunities from the data and how they might be explained within a broader theoretical framework of observational learning. As a basis for discussion, we present a preliminary thematic map of the results and how students’ remarks on good/bad examples in the videos relate to the types of knowledge they gain from it. We suggest several resulting topics for future study. © Springer Nature Switzerland AG 2018

Place, publisher, year, edition, pages
Cham: Springer, 2018. Vol. 11082, p. 656-659
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 11082
Keywords [en]
Video-based learning, Soft skill learning, Thematic analysis, Interactive systems, Intelligent support
National Category
Learning Human Computer Interaction
Identifiers
URN: urn:nbn:se:hh:diva-38620DOI: 10.1007/978-3-319-98572-5_67ISI: 000552686200067Scopus ID: 2-s2.0-85053187441ISBN: 978-3-319-98571-8 (print)ISBN: 978-3-319-98572-5 (electronic)OAI: oai:DiVA.org:hh-38620DiVA, id: diva2:1271085
Conference
13th European Conference on Technology Enhanced Learning, EC-TEL 2018, Leeds, United Kingdom, September 3-6, 2018
Available from: 2018-12-16 Created: 2018-12-16 Last updated: 2023-10-05Bibliographically approved

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Sjödén, Björn

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CiteExportLink to record
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Citation style
  • apa
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  • Other locale
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Output format
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