Endogenous Eye Blinking Rate to Support Human–Automation Interaction for E-Learning Multimedia Content Specification

• Main Authors: Othmar Othmar Mwambe, Phan Xuan Tan, Eiji Kamioka
• Format: Article
• Language: English
• Published: MDPI AG 2021-01-01
• Series: Education Sciences
• Subjects: cognitive load measurement; adaptive navigation support; human–automation interaction; e-learning multimedia content specification; adaptive hypermedia systems; eye tracking
• Online Access: https://www.mdpi.com/2227-7102/11/2/49

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.