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Investigating Error Injection to Enhance the Effectiveness of Mobile Text Entry Studies of Error Behaviour
arXiv - CS - Human-Computer Interaction Pub Date : 2020-03-13 , DOI: arxiv-2003.06318
Andreas Komninos, Emma Nicol and Mark Dunlop

During lab studies of text entry methods it is typical to observer very few errors in participants' typing - users tend to type very carefully in labs. This is a problem when investigating methods to support error awareness or correction as support mechanisms are not tested. We designed a novel evaluation method based around injection of errors into the users' typing stream and report two user studies on the effectiveness of this technique. Injection allowed us to observe a larger number of instances and more diverse types of error correction behaviour than would normally be possible in a single study, without having a significant impact on key input behaviour characteristics. Qualitative feedback from both studies suggests that our injection algorithm was successful in creating errors that appeared realistic to participants. The use of error injection shows promise for the investigation of error correction behaviour in text entry studies.

中文翻译:

调查错误注入以提高错误行为的移动文本输入研究的有效性

在文本输入方法的实验室研究期间,通常观察到参与者打字中的错误很少 - 用户在实验室中往往会非常小心地打字。由于未测试支持机制,因此在调查支持错误感知或纠正的方法时,这是一个问题。我们设计了一种基于将错误注入用户打字流的新颖评估方法,并报告了有关该技术有效性的两项用户研究。与通常在单个研究中可能观察到的情况相比,注入使我们能够观察到更多的实例和更多不同类型的纠错行为,而不会对关键输入行为特征产生重大影响。两项研究的定性反馈表明,我们的注射算法成功地产生了对参与者来说看起来很现实的错误。
更新日期:2020-03-16
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