Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 -- 1350 2024-02-09 09:39:42 |
2 update references and layout -41 word(s) 1309 2024-02-18 04:02:54 |

Video Upload Options

Do you have a full video?

Confirm

Are you sure to Delete?
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Rymarkiewicz, W.; Cybulski, P.; Horbiński, T. Mobile Maps Using Eye Tracking. Encyclopedia. Available online: https://encyclopedia.pub/entry/54957 (accessed on 10 October 2024).
Rymarkiewicz W, Cybulski P, Horbiński T. Mobile Maps Using Eye Tracking. Encyclopedia. Available at: https://encyclopedia.pub/entry/54957. Accessed October 10, 2024.
Rymarkiewicz, Wojciech, Paweł Cybulski, Tymoteusz Horbiński. "Mobile Maps Using Eye Tracking" Encyclopedia, https://encyclopedia.pub/entry/54957 (accessed October 10, 2024).
Rymarkiewicz, W., Cybulski, P., & Horbiński, T. (2024, February 09). Mobile Maps Using Eye Tracking. In Encyclopedia. https://encyclopedia.pub/entry/54957
Rymarkiewicz, Wojciech, et al. "Mobile Maps Using Eye Tracking." Encyclopedia. Web. 09 February, 2024.
Mobile Maps Using Eye Tracking
Edit

The use of mobile mapping applications is currently one of the most popular methods of navigating in urban spaces. Widespread access to smartphones and a wide range of mobile navigation applications allow each of us quick and easy access to geographic information. Mobile maps, like paper ones, allow the user to browse, search for points of interest and calculate routes, but their significant advantage, as indicated by users, is real-time information about the user’s current position.

mobile maps eye tracking daily smartphone usage

1. Introduction

Mobile maps encounter many problems, e.g., difficulties in reading a map’s symbology correctly. For tourist maps, it is important to make them attractive to the user by using an original graphic design [1]. Navigation features such as routes and point symbols should be higher up in the visual hierarchy [2]; however, poorly designed symbols can be difficult for users to interpret, especially considering that such maps usually do not include a legend [3]. Inadequately selected graphics can also overwhelm the user, making a map difficult to use. The problem is exacerbated when you consider the smaller screens of smartphones and tablets. When designing the user experience (UX), it is important to take these limitations into account and design applications for mobile devices first, and only then for larger screens [4]. It is possible that the frequency of smartphone use has an impact on the ability to find symbols on mobile maps. There is therefore a need to investigate this effect and determine whether more experienced users are better able to perform map-related tasks. Analyzing eye movements can be helpful in evaluating this impact, as it can be used to examine aspects such as the speed of scanning and finding symbols on a map, as well as the degree of cognitive load.
Krassanakis and Cybulski [5] note in their paper that the cartographic community has recognized the importance of research related to visual perception and cognition, such that experimental techniques from other fields such as psychology can be used to investigate the fundamental elements of cartographic communication. The creation of effective and efficient maps can rely on the results of experiments in which the map is treated as a stimulus and the perceptual process as a response when viewing the map. They emphasize the significant impact of the use of eye-tracking techniques on cartography due to the large amount of research using eye-tracking technology in this field. The use of eye-tracking tools in usability studies of cartographic products helps to determine the users’ visual strategy and whether the users remember any of it, as well as what attracts the users’ attention and whether the respondents noticed a particular point or area [6].
Eye tracking metrics have consistently served as valuable tools in various research studies, with their presentation and correlation with performance measures contributing to a comprehensive understanding of efficiency and usability. Numerous investigations across diverse fields have utilized eye-tracking technology to unravel intricate patterns of visual behavior and glean insights into cognitive processes underlying human–computer interactions [7]. Researchers have employed fixation- and saccade-based metrics to assess the effectiveness of animated and interactive maps, the allocation of visual attention, and the cognitive load associated with different tasks [8][9].
Roth [4] also points out that mobile maps should also be examined in terms of the speed of movement, as a cartographic generalization based only on the scale of the map display may not be sufficient for users on the move. This is because users in motion perceive a larger area of the map in a given period of time than with a static map. This suggests that not taking this aspect into account when designing a map can lead to users being overwhelmed by the amount of cartographic content.

2. Mobile Maps Using Eye Tracking

Liao et al. [10], in their work on the differences in visual attention in pedestrian navigation when using 2D and 3D maps, found that there are serious difficulties in conducting research with an eye-tracking tool under field conditions. Internal conditions, on the other hand, provide users with a quiet and distraction-free environment, which also provides more control for the person conducting the experiment. Therefore, they decided to simulate field situations in a laboratory environment. The surveys conducted on the participants confirmed that it is possible to simulate a real indoor environment and thus test the effects of maps on pedestrian navigation. They also show that changes in stress on the human nervous system led to changes in pupil diameter. Therefore, it is possible to reliably determine the degree of cognitive load based on the change in pupil diameter [11].
As Cybulski et al. [12] note in their study, not accounting for individual differences in mobile device use and familiarity with mobile devices may have an impact on participants’ outcomes and preferences. Therefore, it is useful to consider the average daily usage time of smartphones in studies on the effectiveness and correctness of locating symbols in different map contexts and to check whether there is any correlation.
The scanning speed, understood as the sequence of all fixations and saccades on the screen, is used to determine the users’ scanning and visual performance. Al-Showarah et al. [13] compared the influence of age on smartphone/tablet use in an eye-tracking study. They found that younger users with more experience using a smartphone had shorter scanning times than older users with less experience. It is worth checking whether this correlation also exists in a more homogeneous age group of respondents who differ in their average daily usage time of mobile devices.
Motion simulation in mobile app recordings is similar to animated maps. As a result, similar problems occur, e.g., problems with the user retaining large amounts of information that appear in subsequent scenes [14]. Symbols appear on the screen, move and disappear, which can make it difficult to read the map. Therefore, eye-tracking research is of great value as it makes it possible to determine the way users view a map, which helps to explain the effectiveness and efficiency of the map.
Building upon Skaramagkas et al.’s [15] findings, it is essential to underscore that an enlarged pupil diameter could signify heightened engagement in cognitive or emotional processes. This observation aligns with the established literature suggesting that variations in pupil size are reflective of the intensity of mental and emotional activities [16]. In the specific context of map-reading tasks, where cognitive demands fluctuate based on factors such as task complexity, spatial information processing and user engagement, monitoring pupil dilation becomes a valuable metric for gauging the cognitive load or emotional involvement of individuals [17].
Usability testing for personalized user characteristics, such as age, gender or experience, has been proposed in various studies [18][19][20]. Scan path speed measured during cartographic tasks involving satellite images and presented through saccadic amplitude revealed more demanding scanning processes during the peripheral search in the study of Krejtz et al. [21]. Saccadic amplitude was also analyzed by Putto et al. [22] while participants were searching and selecting different geometrical objects based on elevation visualization, and in that study, the largest saccadic amplitude was observed for contour lines. Based on saccadic velocity, Kiefer et al. [23] were able to recognize participants’ activities on a cartographic background.
Differences between males and females in map use were studied some time ago by Gilmartin and Patton [24]. Their findings concern children and adults in tasks such as route planning or symbol identification. The only differences found among children were that boys’ performance was significantly better than girls. Montello et al. [25] presented differences between males and females in various map-based tasks. They showed that male participants were better at newly acquired spatial information, while female participants outperformed males in static object/location memory tasks. Spatial orientation in wayfinding tasks based on 3D maps was studied by Liao and Dong [26] in the context of sex differences. They found that male participants’ fixation duration and fixation count distribution were more platykurtic than those of female participants.

References

  1. Medynska-Gulij, B. Point Symbols: Investigating Principles and Originality in Cartographic Design. Cartogr. J. 2008, 45, 62–67.
  2. van Tonder, B.; Wesson, J. Design and Evaluation of an Adaptive Mobile Map-Based Visualisation System. In Human-Computer Interaction—INTERACT 2009; Lecture Notes in Computer Science 2009; Gross, T., Gulliksen, J., Kotzé, P., Oestreicher, L., Palanque, P., Prates, R.O., Winckler, M., Eds.; Springer: Berlin/Heidelberg, Germany, 2009; Volume 5726.
  3. Robinson, A.C.; Pezanowski, S.; Troedson, S.; Bianchetti, R.; Blanford, J.; Stevens, J.; Guidero, E.; Roth, R.; MacEachren, A.M. Symbol Store: Sharing map symbols for emergency management. Cartogr. Geogr. Inf. Sci. 2013, 40, 415–426.
  4. Roth, R. What is Mobile First Cartographic Design? In ICA Joint Workshop on User Experience Design for Mobile Cartography; International Cartographic Association: Bern, Switzerland, 2019.
  5. Krassanakis, V.; Cybulski, P. Eye Tracking Research in Cartography: Looking into the Future. ISPRS Int. J. Geo-Inf. 2021, 10, 411.
  6. Krassanakis, V.; Cybulski, P. A review on eye movement analysis in map reading process: The status of the last decade. Geod. Cartogr. 2019, 68, 191–209.
  7. Goldberg, J.H.; Wichansky, A.M. Eye Tracking in Usability Evaluation: A Practitioner’s Guide. In The Mind’s Eye; Hyönä, J., Radach, R., Deubel, H., Eds.; Elsevier: Amsterdam, The Netherlands, 2003; Volume 200, pp. 493–516.
  8. Çöltekin, A.; Heil, B.; Garlandini, S.; Fabrikant, S.I. Evaluating the Effectiveness of Interactive Map Interface Designs: A Case Study Integrating Usability Metrics with Eye-Movement Analysis. Cartogr. Geogr. Inf. Sci. 2009, 36, 5–17.
  9. Dong, W.; Liao, H.; Xu, F.; Liu, Z.; Zhang, S.B. Using eye tracking to evaluate the usability of animated maps. Sci. China Earth Sci. 2014, 57, 512–522.
  10. Liao, H.; Dong, W.; Peng, C.; Liu, H. Exploring differences of visual attention in pedestrian navigation when using 2D maps and 3D geo-browsers. Cartogr. Geogr. Inf. Sci. 2017, 44, 474–490.
  11. Smerecnik, C.; Mesters, I.; Kessels, L.; Ruiter, R.; Vries, N.; de Vries, H. Understanding the positive effects of graphical risk information on comprehension: Measuring attention directed to written, tabular, and graphical risk information. Risk Anal. 2010, 30, 1387–1398.
  12. Cybulski, P.; Medyńska-Gulij, B.; Horbiński, T. Users’ Visual Experience During Temporal Navigation in Forecast Weather Maps on Mobile Devices. J. Geovis Spat. Anal. 2023, 7, 32.
  13. Al-Showarah, S.; AL-Jawad, N.; Sellahewa, H. Effects of User Age on Smartphone and Tablet Use, Measured with an Eye-Tracker via Fixation Duration, Scan-Path Duration, and Saccades Proportion. In Universal Access in Human-Computer Interaction. Universal Access to Information and Knowledge, Proceedings of the 17th International Conference of UAHCI 2023 and HCII 2023, Copenhagen, Denmark, 23–28 July 2023; Lecture Notes in Computer, Science; Stephanidis, C., Antona, M., Eds.; Springer: Cham, Switzerland, 2023; Volume 8514, pp. 3–14.
  14. Cybulski, P. Effectiveness of Memorizing an Animated Route—Comparing Satellite and Road Map Differences in the Eye-Tracking Study. ISPRS Int. J. Geo-Inf. 2021, 10, 159.
  15. Skaramagkas, V.; Giannakakis, G.; Ktistakis, E.; Manousos, D.; Karatzanis, I.; Tachos, N.S.; Tripoliti, E.; Marias, K.; Fotiadis, D.I.; Tsiknakis, M. Review of Eye Tracking Metrics Involved in Emotional and Cognitive Processes. IEEE Rev. Biomed. Eng. 2021, 16, 260–277.
  16. Foroughi, C.K.; Sibley, C.; Coyne, J.T. Pupil size as a measure of within-task learning. Psychophysiology 2017, 54, 1436–1443.
  17. Kiefer, P.; Giannopoulos, I.; Duchowski, A.; Raubal, M. Measuring Cognitive Load for Map Tasks Through Pupil Diameter. In Proceedings of the 9th International Conference on Geographic Information Science, Montreal, QC, Canada, 27–30 September 2016; Miller, J., O’Sullivan, D., Wiegand, N., Eds.; Springer: Cham, Switzerland, 2016; Volume 9927.
  18. Sarjakoski, L.T.; Nivala, A.M. Adaptation to Context—A Way to Improve the Usability of Mobile Maps. In Map-Based Mobile Services; Meng, L., Reichenbacher, T., Zipf, A., Eds.; Springer: Berlin, Germany, 2005.
  19. Griffin, A.L.; White, T.; Fish, C.; Tomio, B.; Huang, H.; Sluter, C.R.; Bravo, J.V.M.; Fabrikant, S.I.; Bleisch, S.; Yamada, M.; et al. Designing across map use contexts: A research agenda. Int. J. Cartogr. 2017, 3, 90–114.
  20. Montello, D.R. Cognitive Map-Design Research in the Twentieth Century: Theoretical and Empirical Approaches. Cartogr. Geogr. Inf. Sci. 2002, 29, 283–304.
  21. Krejtz, K.; Çöltekin, A.; Duchowski, A.; Niedzielska, A. Using Coefficient to Distinguish Ambient/Focal Visual Attention During Cartographic Tasks. J. Eye Mov. Res. 2017, 10, 1–13.
  22. Putto, K.; Kettunene, P.; Torniainen, J.; Krause, C.M.; Sarjakoski, L.T. Effects of Cartogrpahic Elevation Visualization and Map-reading Tasks on Eye Movements. Cartogr. J. 2014, 51, 225–236.
  23. Kiefer, P.; Giannopoulos, I.; Raubal, M. Using eye movements to recognize activities on cartographic maps. In Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Orlando, FL, USA, 5–8 November 2013; pp. 488–491.
  24. Gilmartin, P.P.; Patton, J.C. Comparing the Sexes on Spatial Abilities: Map-Use Skills. Ann. Assoc. Am. Geogr. 1984, 74, 605–619.
  25. Montello, D.R.; Lovelace, K.L.; Golledge, R.G.; Self, C.M. Sex-Related Differences and Similarities in Geographic and Environmental Spatial Abilities. Ann. Assoc. Am. Geogr. 1999, 89, 515–534.
  26. Liao, H.; Dong, W. An Exploratory Study Investigating Gender Effects on Using 3D Maps for Spatial Orientation in Wayfinding. ISPRS Int. J. Geo-Inf. 2017, 6, 60.
More
Information
Subjects: Others
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register : , ,
View Times: 254
Revisions: 2 times (View History)
Update Date: 18 Feb 2024
1000/1000
ScholarVision Creations