A scoping review of webcam eye tracking in learning and education

Title: A scoping review of webcam eye tracking in learning and education
Source document: Studia paedagogica. 2023, vol. 28, iss. 3, pp. [113]-131
  • ISSN
    1803-7437 (print)
    2336-4521 (online)
Type: Article
License: Not specified license
Rights access
open access

Notice: These citations are automatically created and might not follow citation rules properly.

The use of eye tracking in educational research has shown great potential in recent decades. There are various approaches to the usage of eye tracking technology in this area, including investigation of self-regulated learning from different types of learning environments. Nonetheless, the majority of published research studies have one tremendous limitation: using expensive remote or tower-based eye trackers to provide high-quality data in laboratory conditions. Now, new webcam eye trackers may offer an easily affordable approach allowing eye tracking measurements in the real environment, such as the investigation of learning behavior in online learning environments. The main aim of this scoping review is to explore the use of webcam eye tracking technology in the field of learning and education. We established three specific purposes: 1) to introduce educational topics being explored using webcam eye tracking, 2) to discuss the methodological aspects when exploring educational topics with webcam eye tracking, and 3) to investigate the eye tracking aspects used for the analysis. To do this, we analyzed 16 studies that used webcam eye tracking. The results of the scoping review show that 1) selected studies focus mainly on students’ behavior in online learning environments, such as engagement, lack of attention, cheating and others; 2) a wide range of studies aimed at the development of automatized detection tools; and 3) studies are mainly focused on extracting raw and event data features using them mostly for automatized detection purposes.
This study is an outcome of the project "Multimodal learning analytics to study self-regulated learning processes within learning management systems" (21-08218S) funded by the Czech Science Foundation.
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