Abstract
Mobile devices are now the most popular computing technology for accessing the Internet. This has resulted in designers devoting more of their time to improving users’ mobile experiences. This can be achieved in part by helping users find content quickly and easily. Understanding what supports or harms a user’s visual search is key to creating displays that meet usability efficiency requirements. Broadly, searches are guided by a combination of visual salience and previous experiences. We recommend revealing these influences by employing a computational saliency model and by employing our mobile spatial convention map. The research presented extends the previous attentional priority (AP) modeling work, from web pages to mobile interfaces. Notably, we reveal that users typically search a mobile web page by using a “railroad-like” viewing pattern rather than the “F” pattern that is typically described in web page research. Also, we propose a mobile web page-specific attentional priority (AP) model. The AP model combines our experience-based spatial convention map with a saliency model map. We examined the predictive performance of a saliency model, compared to the mobile-specific convention map. It was discovered that the convention map better predicted the initial deployment of attention, and the saliency map better accounted for later selection.
Similar content being viewed by others
References
Ahmad N, Rextin A, Kulsoom UE. Perspective on usability guidelines for smartphone applications: an empirical investigation and systematic literature review. J Inf Softw Technol. 2018;94:130–49.
Arnheim R. Art and visual perception: a psychology of the creative eye. Berkeley: University of California Press; 1954.
Awh E, Belopolsky AV, Theeuwes J. Top-down versus bottom-up attentional control: a failed theoretical dichotomy. Trends Cogn Sci. 2012;16:437–43.
Baddeley AD. Working memory. Science. 1992;255:556–9.
Biedert R, Dengel A, Buscher G, Vartan A. Reading and estimating gaze on smart phones. In: Proceedings of the symposium on eye tracking research and applications. ACM; 2012. p. 385–8.
Bradley S. Design principles: dominance, focal points and hierarchy. Smashing Magazine; 2015, February. Retrieved from https://www.smashingmagazine.com/2015/02/design-principles-dominance-focal-points-hierarchy/.
Buscher G, Cutrell E, Morris MR. What do you see when you’re surfing? Using eye tracking to predict salient regions in web pages. In: Proceedings of the computer–human interaction conference; 2009. p. 21–30.
Chittaro L. Visualizing information on mobile devices. Computer. 2006;39(3):40–5.
Chittaro L. Designing visual user interfaces for mobile applications. In: Proceedings of the 3rd ACM international symposium on engineering interactive computing systems. ACM Press; 2011. p. 331–2.
Chun MM. Contextual cueing of visual attention. Trends Cogn Sci. 2000;4:170–7.
Chun MM, Jiang Y. Contextual cueing: implicit learning and memory of visual context guides spatial attention. Cogn Psychol. 1998;36:28–71.
Coursaris CK, Kim DJ. A meta-analytical review of empirical mobile usability studies. J Usability Stud. 2011;6:117–71.
Cowan N. Evolving conceptions of memory storage, selective attention, and their mutual constraints within the human information processing system. Psychol Bull. 1988;104:163–91.
Cowan N. The magical number 4 in short-term memory: a reconsideration of mental storage capacity. Behav Brain Sci. 2000;24:154–76.
Desimone R, Duncan J. Neural mechanisms of selective visual attention. Annu Rev Neurosci. 1995;18:193–222.
Djamasbi S, Hall-Phillips A, Yang RR. SERPs and ads on mobile devices: an eye tracking study for generation Y. In: International conference on universal access in human–computer interaction. Berlin: Springer; 2013. p. 259–68.
Dunlop M, Brewster S. The challenge of mobile devices for human computer interaction. J Pers Ubiquitous Comput. 2002;6:235–6.
Faraday P. Visually critiquing web pages. In: Proceedings of the 6th conference on human factors and the web, Austin, TX; 2000.
Fernandez-Duque D, Johnson ML. Cause and effect theories of attention: the role of conceptual metaphors. Rev Gen Psychol. 2002;6:153–65.
Flieder K, Modritscher F. Foundations of pattern language based on gestalt principles. CHI: Works-in-Process; 2006. p. 773–8.
Grier R, Kortum P, Miller J. How users view web pages: an exploration of cognitive and perceptual mechanisms. In: Zaphiris P, Kurniawan S, editors. Human computer interaction research in web design and evaluation. Hershey: Information Science Reference; 2007. p. 22–41.
Harel J, Koch C, Perona P. Graph-based visual saliency. In: Proceedings of neural information processing systems; 2006. p. 1–8.
Harrison R, Flood D, Duce D. Usability of mobile applications: literature review and rationale for a new usability model. J Interact Sci. 2013;1:1–16.
Ismail NA, Ahmad F, Kamaruddin NA, Ibrahim R. A review of usability issues in mobile application. J Mob Comput Appl. 2016;3:47–52.
Itti L, Koch C, Niebur E. A model of saliency-based fast visual attention for rapid scene analysis. IEEE Trans Pattern Anal Mach Intell. 1998;20:1254–9.
Jana A, Bhattacharya S. Design and validation of an attention model of web page users. Adv Hum-Comput Interact. 2015;2015:1–14.
Johnson WA, Dark VJ. Selective attention. Annu Rev Psychol. 1986;37:43–75.
Jones B. Understanding visual hierarchy in web design. Envato. 2011 September. Retrieved from http://webdesign.tutsplus.com/articles/understanding-visual-hierarchy-in-web-design–webdesign-84.
Kim MS, Cave KR. Grouping effects on spatial attention in visual search. Gener Psychol. 1999;126:326–52.
Kjeldskov J, Stage J. New techniques for usability evaluation of mobile systems. Int J Hum Comput Stud. 2004;60:559–620.
Luo S, Zhou Y. Effects of smartphone icon background shapes and figure/background area ratios on visual search performance and user preferences. Front Comput Sci. 2015;9:751–64.
Malcolm GL, Henderson JM. Combining top-down processes to guide eye movements during real-world scene search. J Vis. 2010;10:1–11.
Mariakakis A, Goel M, Aumi MTI, Patel SN, Wobbrock JO. SwitchBack: using focus and saccade tracking to guide users’ attention for mobile task resumption. In: Proceedings of the 33rd annual ACM conference on human factors in computing systems. ACM; 2015. p. 2953–62.
Masciocchi CM, Still JD. Alternatives to eye tracking for predicting stimulus-driven attentional selection within interfaces. J Hum Comput Interact. 2013;34:285–301.
Moraglia G. Display organization and the detection of horizontal lines segments. Percept Psychophys. 1989;45:265–72.
Norman DA. Affordance, conventions, and design. Interactions. 1999;6:38–42.
Norman DA, Shallice T. Attention to action: Willed and automatic control of behavior. In: Davidson RJ, Schwartz GE, Shapiro D, editors. Consciousness and self-regulation: advances in research and theory, vol. 4. New York: Plenum Press; 1986. p. 1–18.
Parkhurst D, Law K, Niebur E. Modeling the role of salience in the allocation of overt visual attention. Vis Res. 2002;42:107–23.
Pashler H. Cross-dimensional interaction and texture segregation. Percept Psychophys. 1988;43:307–18.
Punchoojit L, Hongwarittorrn N. Usability studies on mobile user interface design patterns: a systematic literature review. J Adv Hum Comput Interact. 2017;2017:1–22.
Rayer K. Eye movements in reading and information processing: 20 years of research. Psychol Bull. 1998;124:372–422.
Repokari L, Saarela T, Kurki I. Visual search on a mobile phone display. In: Proceedings of SAICSIT; 2002. p. 253.
StatCounter. Desktop vs mobile vs tablet market share worldwide [data from June 2017 to June 2018]; 2018. Retrieved from http://gs.statcounter.com/platform-market-share/desktop-mobile-tablet/worldwide.
Still JD. Web page visual hierarchy: examining Faraday’s guidelines for entry points. J Comput Hum Behav. 2018;84:352–9.
Still JD. Web page attentional priority model. J Cogn Technol Work. 2017;19:363–74.
Still JD, Dark VJ. Examining working memory load and congruency effects on affordances and conventions. Int J Hum Comput Stud. 2010;68:561–71.
Still JD, Dark VJ. Cognitively describing and designing affordances. J Des Stud. 2013;13:285–301.
Still JD, Hicks J, Cain AA, Billman D. Predicting stimulus-driven attentional selection within mobile interfaces. In: Proceedings of the 8th international conference on cognitive and neuroergonomics; 2017. p. 255–61.
Still JD, Hicks JM, Cain AA. Examining the influence of saliency within mobile interface displays. J AIS Trans Human Comput Interact. 2020;12:28–44.
Still JD, Masciocchi CM. A saliency model predicts fixations in web interfaces. In: Proceedings of the 5th international workshop on model-driven development of advanced user interactions, 25–18, Atlanta, GA; 2010.
Still JD, Masciocchi CM. Considering the influence of visual saliency during interface searches. In: Alkhalifa EM, Gaid K, editors. Cognitively informed intelligent interfaces: system design and development. Hershey: Information Science Reference; 2012. p. 84–97.
Still JD, Still ML. Influence of visual salience on webpage product searches. ACM J Trans Appl Percept. 2019;16:1–11.
Still JD, Still ML, Grgic J. Designing intuitive interactions: exploring performance and reflective measures. Interact Comput. 2015;27:271–86.
Tatler BW. The central fixation bias in scene viewing: selecting an optimal viewing position independently of motor bases and image feature distributions. J Vis. 2007;14:1–17.
Theeuwes J. Perceptual selectivity for color and form. Percept Psychophys. 1992;51:599–606.
Theeuwes J. Top-down search strategies cannot override attentional capture. Psychon Bull Rev. 2004;11:65–70.
Wolfe JM. Guided search 4.0: Current progress with a model of visual search. In: Gray W, editor. Integrated models of cognitive systems. New York: Oxford; 2007. p. 99–119.
Wolfe JM, Horowitz TS. What attributes guide the deployment of visual attention and how do they do it? Nat Rev Neurosci. 2004;5:1–7. https://doi.org/10.1038/nrn1411.
Yoo HY, Cheon SH. Visualization by information type on mobile device. In: Proceedings of the 2006 Asia–Pacific symposium on information visualization, vol. 60. Australian Computer Society, Inc; 2006. p. 143–6.
Zhang D, Adipat B. Challenges, methodologies, and issues in the usability testing of mobile applications. Int J Hum Comput Interact. 2005;18:293–308.
Ziefle M. Information presentation in small screen devices: the trade-off between visual density and menu foresight. J Appl Ergonom. 2010;41:719–30.
Acknowledgements
This research was supported by a Summer Research Fellowship Program Grant from the Office of Research at Old Dominion University, Norfolk, Virginia, USA.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
On behalf of all authors, the corresponding author states that there is no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Still, J.D., Hicks, J.M. Mobile Interface Attentional Priority Model. SN COMPUT. SCI. 1, 142 (2020). https://doi.org/10.1007/s42979-020-00166-3
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s42979-020-00166-3