​Educational Research

Eye tracking is a tool used in educational research in order to understand the knowledge process, cognitive load on students, and teaching methods. The results help design and improve the learning environment.

Understanding educational contexts

Eye tracking can capture interesting insights about student learning behavior and teaching methods in a broad range of educational situations. The data from an eye tracker can reveal different learning strategies for researchers to better understand student cognitive workload. This information can also be used to evaluate teacher performance and instruction methods.
By understanding the classroom dynamics, including interaction between students and teachers, researchers can define appropriate training programs and instructions in order to improve education.

Products and services

Tobii Pro offers hardware and software, along with training and support, for the study of education in different contexts. We have flexible solutions that enable research both in real-world environments and in lab settings.

We have created eye trackers with a range of capabilities- from easy-to-use live viewing in order to get immediate insights to more advanced solutions for the full spectrum of qualitative and quantitative analysis. Read more


Kennesaw State University

Eye tracking was used in this preliminary research study by Kennesaw State University to investigate student gaze patterns during physical science lectures. It discovered that classroom attention is impacted by various factors throughout the duration of the lecture. Read more

Western Kentucky University

Eye tracking was used in a visual communication research project on information concerning potable water. Researchers from Western Kentucky University investigated the effectiveness of visual design on instructional materials intended to educate West African residents about personal and public water use, water pollution and conservation. Read more

  • Moro, R., & Bielikova, M. (2015). Utilizing Gaze Data in Learning: From Reading Patterns Detection to Personalization. Presented at the CEUR. UMAP 2015 Extended Proceedings, Dublin. Retrieved from http://ceur-ws.org/Vol-1388/poster_paper10.pdf
  • Antonietti, A., Colombo, B., & Di Nuzzo, C. (2015). Metacognition in self-regulated multimedia learning: integrating behavioural, psychophysiological and introspective measures. Learning, Media and Technology, 40(2), 187–209. http://doi.org/10.1080/17439884.2014.933112
  • Lee, H., Kanakogi, Y., & Hiraki, K. (2015). Building a responsive teacher: how temporal contingency of gaze interaction influences word learning with virtual tutors. Royal Society Open Science, 2(1), 140361–140361. http://doi.org/10.1098/rsos.140361

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