A new e-learning system focusing on emotional aspect using biological signals

Saromporn Charoenpit, Michiko Ohkura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

E-learning is the computer and network-enabled transfer of skills and knowledge. It is widely accepted that new technologies can make a big difference in education. Although the advantages of e-learning over person to person teaching are still under debate, the latter is considered to be superior with respect to teaching effectiveness. One reasons for this advantage of human expert tutors is their ability to deal with the emotional aspects of the learner. In an e-learning system, emotions are important in the classroom. We thus proposed a new e-learning system that focuses on affective aspects. Our system equips sensors to measure biological signals and analyzes user emotions for the improvement of the e-learning system's effectiveness.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages343-350
Number of pages8
Volume8005 LNCS
EditionPART 2
DOIs
Publication statusPublished - 2013
Event15th International Conference on Human-Computer Interaction, HCI International 2013 - Las Vegas, NV
Duration: 2013 Jul 212013 Jul 26

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume8005 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other15th International Conference on Human-Computer Interaction, HCI International 2013
CityLas Vegas, NV
Period13/7/2113/7/26

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Keywords

  • Affective aspects
  • Biological signal
  • E-learning
  • Emotions

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Charoenpit, S., & Ohkura, M. (2013). A new e-learning system focusing on emotional aspect using biological signals. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 2 ed., Vol. 8005 LNCS, pp. 343-350). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8005 LNCS, No. PART 2). https://doi.org/10.1007/978-3-642-39262-7_39