doi: 10.18178/ijiet.2018.8.7.1086
Local Sequence Alignment for Scan Path Similarity Assessment
Abstract
It has long been shown that there is a close relationship between eye movement, human cognition and brain activity. The present work seeks to explore this relationship by investigating the students’ saccadic eye movement sequences in a problem solving task. We aim to assess students’ reasoning process in a clinical problem solving task using students’ visual trajectories. We use students’ scan path, followed while resolving medical cases, and a local sequence alignment algorithm, to evaluate their analytical reasoning during medical case resolution. An experimental protocol was conducted with 15 participants. Eye movements were recorded while they were interacting with our learning environment. The proposed approach, based on gaze data, can be reliably applied to eye movement sequence comparison. Our findings have implications for improving novice clinicians’ reasoning abilities in particular and ultimately enhancing learning outcomes.
Keywords
- Cognitive tasks
- eye movements
- local sequence alignment
- medical reasoning
- scan path similarity
How to Cite
Asma Ben Khedher, Imène Jraidi, and Claude Frasson, "Local Sequence Alignment for Scan Path Similarity Assessment," International Journal of Information and Education Technology, vol. 8, no. 7, pp. 482-490, 2018. https://doi.org/10.18178/ijiet.2018.8.7.1086
Copyright & License
Copyright © 2018 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).