Research on multimodal affective computing oriented to online collaborative learning

  • Jinpeng Yang
  • , Yaofeng Xue*
  • , Zhitong Zeng
  • , Wei Guo
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Analyzing the emotion interaction of online collaborative learning, this paper proposes a multimodal affective computing model combined with the logical function. The framework of an affective computing is designed, which includes several modules for collection, processing, analysis and visualization of data, sentiment classification and feedback. Finally, the feasibility and validity of the prototype system is verified.

Original languageEnglish
Title of host publicationProceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019
EditorsMaiga Chang, Demetrios G Sampson, Ronghuai Huang, Alex Sandro Gomes, Nian-Shing Chen, Ig Ibert Bittencourt, Kinshuk Kinshuk, Diego Dermeval, Ibsen Mateus Bittencourt
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages137-139
Number of pages3
ISBN (Electronic)9781728134857
DOIs
StatePublished - Jul 2019
Event19th IEEE International Conference on Advanced Learning Technologies, ICALT 2019 - Maceio, Brazil
Duration: 15 Jul 201918 Jul 2019

Publication series

NameProceedings - IEEE 19th International Conference on Advanced Learning Technologies, ICALT 2019

Conference

Conference19th IEEE International Conference on Advanced Learning Technologies, ICALT 2019
Country/TerritoryBrazil
CityMaceio
Period15/07/1918/07/19

Keywords

  • Affective computing
  • Data analysis
  • Learning community
  • Logical function
  • Online collaborative learning

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