Malmö University Publications
Change search
CiteExportLink to record
Permanent link

Direct link
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
Research trends in multimodal learning analytics: A systematic mapping study
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).ORCID iD: 0000-0002-9278-8063
Copenhagen University, Copenhagen, Denmark.
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT).
2023 (English)In: Computers and Education: Artificial Intelligence, ISSN 2666-920X, Vol. 4, p. 100136-100136, article id 100136Article, review/survey (Refereed) Published
Abstract [en]

Understanding and improving education are critical goals of learning analytics. However, learning is not always mediated or aided by a digital system that can capture digital traces. Learning in such environments can be studied by recording, processing, and analyzing different signals, including video and audio, so that traces of actors’ actions and interactions are captured. Multimodal Learning Analytics refers to analyzing these signals through the use and integration of these multiple modes. However, a need exists to evaluate how research is conducted in the emerging field of multimodal learning analytics to aid and evaluate how these systems work. With the growth of multimodal learning analytics, research trends and technologies are needed to support its development. We conducted a systematic mapping study based on established systematic literature practices to identify multimodal learning analytics research types, methodologies, and trending research themes. Most mapped papers presented different solutions and used evaluation-based research methods to demonstrate an increasing interest in multimodal learning analytics technologies. In addition, we identified 14 topics under four themes––learning context, learning process, systems and modality, and technologies––that can contribute to the growth of multimodal learning analytics.

Place, publisher, year, edition, pages
Elsevier, 2023. Vol. 4, p. 100136-100136, article id 100136
Keywords [en]
Multimodal learning analytics, Mapping study, Learning technologies, Artificial intelligence
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:mau:diva-64288DOI: 10.1016/j.caeai.2023.100136Scopus ID: 2-s2.0-85151456109OAI: oai:DiVA.org:mau-64288DiVA, id: diva2:1818876
Available from: 2023-12-12 Created: 2023-12-12 Last updated: 2023-12-12Bibliographically approved

Open Access in DiVA

fulltext(3296 kB)91 downloads
File information
File name FULLTEXT01.pdfFile size 3296 kBChecksum SHA-512
dd7f4d7f395b8eef3d1fa2ab76e16c50ad84f460f540467b56a568e273acd815d411765e4c5fd5337ae0b10e3c9c7464c028514d100a3ea6784405722cd3ff3a
Type fulltextMimetype application/pdf

Other links

Publisher's full textScopus

Authority records

Ouhaichi, HamzaVogel, Bahtijar

Search in DiVA

By author/editor
Ouhaichi, HamzaVogel, Bahtijar
By organisation
Department of Computer Science and Media Technology (DVMT)
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 91 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 107 hits
CiteExportLink to record
Permanent link

Direct link
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