使用自动测试进行用户界面评估实验

Kania Katherina , Dany Eka Saputra
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引用次数: 0

摘要

可学习性是用户交互的一个重要方面,它衡量用户需要多长时间来熟悉软件。使用专家分析或用户问卷的评估方法无法完全反映软件的可学习性。自动测试可以记录用户表现数据,并对可学性进行客观评估。然而,嵌入记录代码进行自动测试的成本可能很高。本作品提出了一种新颖的自动测试方法,用于评估现有软件的可学性。通过使用 Figma 和 Maze 应用程序,制作了一个被评估软件的复制品,并注入了用户表现记录模块。实验结果表明,可学习性数据是可以客观获取的。在实验中,被评估软件的用户平均需要反复学习 3 次。训练有素的受访者每次操作的平均完成时间约为 2.37 秒,而未经训练的受访者每次操作的平均完成时间约为 1.86 秒。
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Experiment on UI evaluation using automated test
Learnability is one important aspect of user interaction that measures how long a user needs to familiarize themselves with the software. The evaluation method using expert analysis or user questionnaire cannot fully capture the learnability aspect of a software. Automated testing can record the user performance data and provide an objective evaluation of learnability. However, embedding recording code to conduct automated test can be expensive. This work proposes a novel method of automatic testing to evaluate the learnability of an existing software. By using Figma and Maze apps, a replica of evaluated software is made and injected with users’ performance recording module with much ease. The result of the experiment shows that learnability data can be acquired objectively. In the experiment, the user of evaluated software requires an average learning rate of 3 iterations. While the average completion time is around 2.37 seconds per action for trained respondents and 1.86 seconds for untrained respondents.
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