Estimating Level of Engagement from Ocular Landmarks

Zeynep Yücel, Serina Koyama, Akito Monden, Mariko Sasakura

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


E-learning offers many advantages like being economical, flexible and customizable, but also has challenging aspects such as lack of–social-interaction, which results in contemplation and sense of remoteness. To overcome these and sustain learners’ motivation, various stimuli can be incorporated. Nevertheless, such adjustments initially require an assessment of engagement level. In this respect, we propose estimating engagement level from facial landmarks exploiting the facts that (i) perceptual decoupling is promoted by blinking during mentally demanding tasks; (ii) eye strain increases blinking rate, which also scales with task disengagement; (iii) eye aspect ratio is in close connection with attentional state and (iv) users’ head position is correlated with their level of involvement. Building empirical models of these actions, we devise a probabilistic estimation framework. Our results indicate that high and low levels of engagement are identified with considerable accuracy, whereas medium levels are inherently more challenging, which is also confirmed by inter-rater agreement of expert coders.

Original languageEnglish
Pages (from-to)1527-1539
Number of pages13
JournalInternational Journal of Human-Computer Interaction
Issue number16
Publication statusPublished - Oct 1 2020

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Human-Computer Interaction
  • Computer Science Applications


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