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Visual Attention and Recognition Differences Based on Expertise in a Map Reading and Memorability Study

Bibliographic Data

ID22032017
AuthorsMerve Keskin (0000-0002-4678-5611, Finnish Geospatial Research Institute, corresponding author), Vassilios Krassanakis (0000-0002-3030-4203, University of West Attica), Arzu Çöltekin (0000-0002-3178-3509, FHNW University of Applied Sciences and Arts Northwestern Switzerland)
Year2023
Volume12
Issue1
Pages21
Publication date2023-01-12
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueISPRS International Journal of Geo-Information (JOURNAL)
Journal identifiersISSN: 2220-9964 • E-ISSN: 2220-9964
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi12010021
OpenAlexW4316038607
LanguageEN
Citations received4
References cited64

This study investigates how expert and novice map users’ attention is influenced by the map design characteristics of 2D web maps by building and sharing a framework to analyze large volumes of eye tracking data. Our goal is to respond to the following research questions: (i) which map landmarks are easily remembered? (memorability), (ii) how are task difficulty and recognition performance associated? (task difficulty), and (iii) how do experts and novices differ in terms of recognition performance? (expertise). In this context, we developed an automated area-of-interest (AOI) analysis framework to evaluate participants’ fixation durations, and to assess the influence of linear and polygonal map features on spatial memory. Our results demonstrate task-relevant attention patterns by all participants, and better selective attention allocation by experts. However, overall, we observe that task type and map feature type mattered more than expertise when remembering the map content. Predominantly polygonal map features such as hydrographic areas and road junctions serve as attentive features in terms of map reading and memorability. We make our dataset entitled CartoGAZE publicly available

Eye tracking · Human–computer interaction · Information retrieval · Computer Science · Gaze Tracking and Assistive Technology · Geographic Information Systems Studies · Spatial Cognition and Navigation · Artificial Intelligence

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Unique citing works4
Citations per year1,33
Citation span2023 - 2026 (4)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 4

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