Seeing the instructor's face and gaze in demonstration video examples affects attention allocation but not learning

Margot van Wermeskerken*, Tamara van Gog

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Although the use of video examples in which an instructor demonstrates how to perform a task has become widespread in online and blended education, specific guidelines for designing such examples to optimize learning are scarce. One design question concerns the presence of the instructor or the instructor's face in the video; because faces attract attention, this might hinder learning by drawing students' attention away from the demonstration. Yet, a recent study suggested that seeing the instructor's face in demonstration video examples may help learning, presumably because the instructor's gaze offers guidance as to what s/he is attending to, which may allow anticipating what s/he is going to do. Using a different task, the main aim of the present study was to see if we could replicate this finding by comparing learning outcomes after observing video examples in which the instructor's face was not visible, or was visible and offered gaze guidance. In addition, we aimed to explore whether the effect –assuming we replicated it– would indeed be due to gaze guidance; we therefore added a third, exploratory condition in which the instructor's face was visible but offered no gaze guidance (i.e., staring straight into the camera). Students' eye movements were recorded in all conditions. We did not replicate prior findings with regard to learning outcomes: learning was neither facilitated nor compromised when seeing the instructor's face. The eye movement data suggested that learners are able to efficiently distribute their attention between the instructor's face and the task he is demonstrating.

Original languageEnglish
Pages (from-to)98-107
Number of pages10
JournalComputers and Education
Publication statusPublished - 1 Oct 2017


  • Demonstration
  • Example-based learning
  • Eye tracking
  • Gaze guidance
  • Modeling


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