June 24, 2017
June 24, 2017
June 28, 2017
Computing & Information Technology
Evaluating the usability of software across various computing hardware, including desktop computers, laptops, tablets, and smartphones, is becoming increasingly important as our need to complete computing tasks on various computing platforms becomes more commonplace in our daily lives. This shift in computing expectations focuses on the ability to compute horizontally, performing the same tasks within different computing environments, as opposed to vertically, performing different tasks in the same computing environment. In this paper, we propose a method by which the usability of a given piece of software can be comparatively analyzed across all hardware platforms on which it is available. This methodology is based on the Majrashi and Hamilton’s twelve factors of usability and has been extended to include specific applications and metrics for the following computing platforms: desktop computers, laptops, tablets, smartphones.
These metrics focus on collecting quantitative data about the usability of each platform. This quantitative data contrasts with recent studies which focus extensively on qualitative data regarding the user experience. Combining these two types of studies will allow researchers to capture a more comprehensive picture of software usability across computing platforms.
The methodology has been validated by performing an initial study using the tasks and performance metrics across each of the defined computing platforms. The results from these initial tests have allowed us to make improvements to the testing methodology as well as some hypotheses for further testing. This proposed methodology, when used in conjunction with qualitative research, can provide a reliable approach for cross-platform usability analysis.
Some considerations for educational design of cross platform methodology are discussed.
Patrick, B., & Helps, R. G. (2017, June), Cross Platform Usability: Evaluating Computing Tasks Performed on Multiple Platforms Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. https://peer.asee.org/28090
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