Correlating Cross-Platform Usability Problems with Eye Tracking Patterns

Majrashi, Khalid; Hamilton, Margaret; Uitdenbogerd, Alexandra L.

doi:10.14236/ewic/hci2016.40

Cited by 9 publications

(9 citation statements)

References 15 publications

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“…This may hinder users' discovery and exploration, especially because relative spatial organization across interfaces supports transfer learning [42]. In their study on cross-device usage, Majrashi et al [28] also showed that users tend to recall the location of features on the PC interface, and immediately direct their gaze to the same area on the mobile interface.…”

Section: Supporting Learnability Across Devicesmentioning

confidence: 99%

Where is that Feature?

Alvina

Bunt

Chilana

et al. 2020

Proceedings of the 2020 ACM Designing Interactive Systems Conference

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People increasingly access cross-device applications from their smartphones while on the go. Yet, they do not fully use the mobile versions for complex tasks, preferring the desktop version of the same application. We conducted a survey (N=77) to identify challenges when switching back and forth between devices. We discovered significant cross-device learnability issues, including that users often find exploring the mobile version frustrating, which leads to prematurely giving up on using the mobile version. Based on the findings, we created four design concepts as video prototypes to explore how to support cross-device learnability. The concepts vary in four key dimensions: the device involved, automation, temporality, and learning approach. Interviews (N=20) probing the design concepts identified individual differences affecting cross-device learning preferences, and that users are more motivated to use cross-device applications when offered the right crossdevice learnability support. We conclude with future design directions for supporting seamless cross-device learnability.

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Section: Supporting Learnability Across Devicesmentioning

confidence: 99%

Where is that Feature?

Alvina

Bunt

Chilana

et al. 2020

Proceedings of the 2020 ACM Designing Interactive Systems Conference

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“…Previous work conducted gaze behavior analyses while reading [9,24,67,83,86], or while consuming user interfaces for usability analyses [59,60,61,79,80] on mobile interfaces.…”

Section: Gaze Behavior Analysismentioning

confidence: 99%

“…The size of the emulator's screen was adapted to match that of a smartphone. A similar approach was adopted in multiple studies [20,58,79,80,95]. Several works explored cross-platform usability [23,94], where usability across several platforms, including handheld mobile devices, was evaluated and compared [79,80].…”

Section: Simulating Mobile Devicesmentioning

confidence: 99%

“…A similar approach was adopted in multiple studies [20,58,79,80,95]. Several works explored cross-platform usability [23,94], where usability across several platforms, including handheld mobile devices, was evaluated and compared [79,80]. For example, Majrashi et al identified eye movement patterns associated with cross-platform usability issues, i.e., usability problems related to switching from an interface to another [80].…”

Section: Simulating Mobile Devicesmentioning

confidence: 99%

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The past, present, and future of gaze-enabled handheld mobile devices

Khamis¹,

Alt

Bulling

2018

Proceedings of the 20th International Conference on Human-Computer Interaction With Mobile Devices and Services

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“…Usability has traditionally been an important quality attribute of interactive systems, where usable interfaces were found to improve human productivity and performance [12,15,16]. The growth of cross-platform interaction and services has resulted in a new emerging theme for usability referred to as 'cross-platform usability' (or 'inter-usability' or 'horizontal usability') (see [17][18][19][20][21][22][23]).…”

Section: Introductionmentioning

confidence: 99%

Cross-Platform Usability Model Evaluation

Majrashi¹,

Hamilton

Uitdenbogerd

et al. 2020

MTI

Self Cite

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It is becoming common for several devices to be utilised together to access and manipulate shared information spaces and migrate tasks between devices. Despite the increased worldwide use of cross-platform services, there is limited research into how cross-platform service usability can be assessed. This paper presents a novel cross-platform usability model. The model employs the think-aloud protocol, observations, and questionnaires to reveal cross-platform usability problems. Two Likert scales were developed for measuring overall user satisfaction of cross-platform usability and user satisfaction with the seamlessness of the transition between one device and another. The paper further employs a series of objective measures for the proposed model. The viability and performance of the model were examined in the context of evaluating three cross-platform services across three devices. The results demonstrate that the model is a valuable method for assessing and quantifying cross-platform usability. The findings were thoroughly analysed and discussed, and subsequently used to refine the model. The model was also evaluated by eight user experience experts and seven out of the eight agreed that it is useful.

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Correlating Cross-Platform Usability Problems with Eye Tracking Patterns

Cited by 9 publications

References 15 publications

Where is that Feature?

Where is that Feature?

The past, present, and future of gaze-enabled handheld mobile devices

Cross-Platform Usability Model Evaluation

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