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.
Index Terms—Cognitive tasks, eye movements, local
sequence alignment, medical reasoning, scan path similarity.
The authors are with the University of Montreal, Canada (e-mail:
benkheda@iro.umontreal.ca).
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.