A Study on Representational Competence in Physics Using Mobile Eye Tracking Systems

Seyyed Saleh Mozaffari Chanijani; Pascal Klein; Mohammad Osamh Adel Al-Naser; Syed Saqib Bukhari; Jochin Kuhn; Andreas Dengel

In: ACM. International Conference on Human-Computer Interaction with Mobile Devices and Services (MobileHCI-16), MobileHCI ’16 Adjunct, located at 18th, September 6-9, Florence, Italy, ACM, 2016.


In this paper, we have conducted an eye tracking experiment by employing an inexpensive, lightweight, and portable eye tracker paired with a tablet. Students were instructed to solve the physics problems by presenting them three coherent representations about a phenomenon: Vectorial representations, data tables and diagrams. The effectiveness of each representation was assessed for three levels of student expertise (experts, intermediates and novices) using eye-tracking gaze data. The results show that students of different skill level (a) prefer different representations for problem-solving, (b) switch between representations with different frequencies, and (c) can be distinguished by the density of representation use. The obtained results confirm earlier findings of physics education research quantitatively which were initially obtained by student interviews and observational studies.


Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence