Analyzing novice and expert user's cognitive load in using a multi-modal interface system

Muhammad Zeeshan Baig, Manolya Kavakli

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

10 Citations (Scopus)

Abstract

Learning and usability of a 3D modelling system depend on direct and indirect human-dependent factors. These factors need to be studied in order to design a state-of-the-art computer tool or software. In this paper, we have presented a novice/expert analysis of a 3D modelling system in which user used two different sets of inputs i.e. keyboard/mouse and speech/gesture to draw the 3D object in AutoCAD. To analyse the user's cognitive workload, we have used electroencephalography (EEG) signals and extracted various frequency bands and power spectral density (PSD) estimates. EEG signals and questionnaires were used to understand the user's behaviour. The results showed that users find i t d ifficult to dr aw a 3D object using the multi-modal input speech/gesture compared to keyboard/mouse. A significant change in theta and alpha bands activity was observed during the analysis. We found that novice users were relatively comfortable in using multi-modal interface system then the expert users which indicates that novice users can learn to use the multi-modal input more quickly then the expert users.

Original languageEnglish
Title of host publication26th International Conference on Systems Engineering, ICSEng 2018
Subtitle of host publicationconference proceedings
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-7
Number of pages7
ISBN (Electronic)9781538678343
ISBN (Print)9781538678350
DOIs
Publication statusPublished - 2018
Event26th International Conference on Systems Engineering, ICSEng 2018 - Sydney, Australia
Duration: 18 Dec 201820 Dec 2018

Conference

Conference26th International Conference on Systems Engineering, ICSEng 2018
Country/TerritoryAustralia
CitySydney
Period18/12/1820/12/18

Keywords

  • EEG
  • Expert
  • Expertise
  • Gesture.
  • HCI
  • Multimodal Interface system
  • Novice
  • Speech

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