Endogenous eye blinking rate to support human–automation interaction for e-learning multimedia content specification

Othmar Othmar Mwambe, Phan Xuan Tan, Eiji Kamioka

Research output: Contribution to journalArticlepeer-review

Abstract

As intelligent systems demand for human–automation interaction increases, the need for learners’ cognitive traits adaptation in adaptive educational hypermedia systems (AEHS) has dramatically increased. AEHS utilize learners’ cognitive processes to attain fair human–automation interaction for their adaptive processes. However, obtaining accurate cognitive trait for the AEHS adaptation process has been a challenge due to the fact that it is difficult to determine what extent such traits can comprehend system functionalities. Hence, this study has explored correlation among learners’ pupil size dilation, learners’ reading time and endogenous blinking rate when using AEHS so as to enable cognitive load estimation in support of AEHS adaptive process. An eye-tracking sensor was used and the study found correlation among learners’ pupil size dilation, reading time and learners’ endogenous blinking rate. Thus, the results show that endogenous blinking rate, pupil size and reading time are not only AEHS reliable parameters for cognitive load measurement but can also support human–automation interaction at large.

Original languageEnglish
Article number49
Pages (from-to)1-13
Number of pages13
JournalEducation Sciences
Volume11
Issue number2
DOIs
Publication statusPublished - 2021 Feb

Keywords

  • Adaptive hypermedia systems
  • Adaptive navigation support
  • Cognitive load measurement
  • E-learning multimedia content specification
  • Eye tracking
  • Human–automation interac-tion

ASJC Scopus subject areas

  • Education
  • Developmental and Educational Psychology
  • Public Administration

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