You are here:

Effects of eye movement modeling examples on adaptive expertise in medical image diagnosis

, Technische Hochschule Deggendorf, Germany ; , University of Turku, Finland ; , Open University of the Netherlands ; , University of Gothenburg, Sweden

Computers & Education Volume 113, Number 1, ISSN 0360-1315 Publisher: Elsevier Ltd


Research indicates that expert performance is domain specific and hardly transfers to novel tasks or domains. However, due to technological changes in dynamic work settings, experts sometimes need to adapt and transfer their skills to new task affordances. The present mixed method study investigates whether eye movement modeling examples (EMME) can promote adaptive expertise in medical image diagnosis. Performance, eye tracking, and think-aloud protocol data were obtained from nine medical experts and fourteen medical students. Participants interpreted dynamic visualizations before (baseline) and after (retention, transfer) viewing an expert model's eye movements. Findings indicate that studying eye movement modeling examples had positive effects on performance, task-relevant fixations, and the use of cognitive and metacognitive comprehension strategies. Effects were stronger for the retention than for the transfer task. Medical experts benefitted more from the modeling examples than did medical students. Directions for future research and implications for related domains are discussed.


Gegenfurtner, A., Lehtinen, E., Jarodzka, H. & Säljö, R. (2017). Effects of eye movement modeling examples on adaptive expertise in medical image diagnosis. Computers & Education, 113(1), 212-225. Elsevier Ltd. Retrieved November 16, 2019 from .

This record was imported from Computers & Education on January 29, 2019. Computers & Education is a publication of Elsevier.

Full text is availabe on Science Direct: