Novel Use of Scenarios in the Usability Engineering of a Next-generation MLST Tool

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Date
2014-04-17
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Publisher
Virginia Tech
Abstract

This work explores the utilization of scenarios in an iterative usability engineering process for the development of a next-generation multilocus sequence typing (MLST) tool. The following three research question were investigated during the usability process: (1) what are the differences in the elicited requirements as scenarios move further from extant work practices, (2) what are the differences in the elicited requirements between structured and free-form scenario groups, and (3) are participant-developed scenarios from the scenario-based interviews effective for use as tasks in formative usability evaluation.

Scenario-based interviews were conducted to collect relevant work-practice information and domain knowledge from two user classes. Requirements distilled from the scenarios and complementary interview questions informed the design of multiple iterations of the tool. A formative usability evaluation was conducted on the second iteration of the tool with the same participants.

Resulting requirements from the scenario-based interviews suggest that proposing scenarios beyond current work practices overwhelmed and confused participants, and therefore worked against requirements generation. Conversely, a less structured scenario-based interview scheme yielded a greater quantity of requirements, and specifically produced more creative requirements. Participant-developed scenarios from the scenario-based interviews were ultimately useful as benchmark tasks in the formative usability evaluation because they were intricate enough to afford meaningful interaction with the interface, while still being completable by both user classes. This research helps to provide a greater understanding of the utilization of novel scenario styles and methodologies, thereby providing support for the continued investigation into scenario use for a variety of applications.

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Keywords
usability, HCI, scenarios, MLST
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