Task Modeling Infrastructure for Analyzing Smart Phone Usage

Levy, Meira; Shoval, Peretz; Shapira, Bracha; Dayan, Aviram; Tubi, Meytal

doi:10.1109/icmb-gmr.2010.47

Cited by 4 publications

(1 citation statement)

References 11 publications

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“…Prior to the analysis of an application, task models that support tracking smart phone users and analyzing their use of smart phone applications are created using a designated task-modeling tool [4].…”

Section: Performance Metricsmentioning

confidence: 99%

Mate

Porat

Schclar

Shapira

2013

CHI '13 Extended Abstracts on Human Factors in Computing Systems

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The 'SmartMobile' research project is directed to design and develop tools to help mobile companies view and analyze data related to the usage and performance of their applications and services.In this paper we focus on one of the main tools that were developed -MATE (Mobile Analysis Tool for usability Experts). MATE is designed to highlight potential usability problems in specific mobile applications, tasks and screens. This is done by extracting and aggregating relevant usage and performance metrics from real customers using their mobile devices. Subjective metrics received from usability tests may be inserted to MATE in order to compare objective and subjective metrics per scenario and per task. Usability evaluations performed by experienced usability experts strengthened the necessity of this tool as an important complement to usability testing.

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Section: Performance Metricsmentioning

confidence: 99%

Mate

Porat

Schclar

Shapira

2013

CHI '13 Extended Abstracts on Human Factors in Computing Systems

Self Cite

View full text Add to dashboard Cite

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Behavioural Variables Analysis in Mobile Environments

Marczal

Aquino

2015

Design, User Experience, and Usability: Users and Interactions

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Development of an Ergonomic Method for Determination of Smartphone Hard Key Locations

Choi

Jung

Park

et al. 2018

Proceedings of the Human Factors and Ergonomics Society Annual

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The present study proposed a design method for determination of optimal hard key locations based on analysis of preferred grip posture and preferred hard key control area, and examined the effectiveness of the method by applying it to a smartphone with 5.0” screen. 45 participants were involved for analysis of preferred grip postures and another 44 participants were recruited for measurement of preferred hard key control area. Smartphone mock-ups which allow participants to adjust the locations of hard keys in their preference were developed having similar specification of real smartphone. L (left) 3 - R (right) 1 - K (back) 1 grip posture (82.6%) that the back side of the device is supported by the index finger and L (left) 4 - R (right) 1 grip posture (11.9%) that all five fingers contribute to grasp the device hardly were the most preferred for the smartphone with 5.0” screen. The optimal hard key locations were found 77 ~ 96 mm area from the bottom for the 20 mm right hard key and 88 ~ 97 mm area from the bottom for the 10 mm left hard key. A verification with real smartphones in various use contexts is needed to apply the results to the product design since the experiments were conducted in a laboratory setting with mock-ups.

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Task Modeling Infrastructure for Analyzing Smart Phone Usage

Cited by 4 publications

References 11 publications

Mate

Mate

Behavioural Variables Analysis in Mobile Environments

Development of an Ergonomic Method for Determination of Smartphone Hard Key Locations

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