Multitasking with Alexa: how using intelligent personal assistants impacts language-based primary task performance

Justin Edwards, H. Liu, Tianyu Zhou, Sandy J. J. Gould, L. Clark, Philip R. Doyle, Benjamin R. Cowan
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引用次数: 18

Abstract

Intelligent personal assistants (IPAs) are supposed to help us multitask. Yet the impact of IPA use on multitasking is not clearly quantified, particularly in situations where primary tasks are also language based. Using a dual task paradigm, our study observes how IPA interactions impact two different types of writing primary tasks; copying and generating content. We found writing tasks that involve content generation, which are more cognitively demanding and share more of the resources needed for IPA use, are significantly more disrupted by IPA interaction than less demanding tasks such as copying content. We discuss how theories of cognitive resources, including multiple resource theory and working memory, explain these results. We also outline the need for future work how interruption length and relevance may impact primary task performance as well as the need to identify effects of interruption timing in user and IPA led interruptions.
使用Alexa进行多任务处理:使用智能个人助理如何影响基于语言的主要任务表现
智能个人助理(IPAs)被认为可以帮助我们同时处理多项任务。然而,使用国际音标对多任务处理的影响还没有明确的量化,特别是在主要任务也是基于语言的情况下。使用双任务范式,我们的研究观察了IPA相互作用如何影响两种不同类型的写作主要任务;复制和生成内容。我们发现,涉及内容生成的写作任务对认知要求更高,并且需要共享更多使用国际音标所需的资源,与抄袭内容等要求较低的任务相比,国际音标交互对写作任务的干扰明显更大。我们讨论了包括多重资源理论和工作记忆在内的认知资源理论如何解释这些结果。我们还概述了未来工作的需要,即中断长度和相关性如何影响主要任务的执行,以及需要确定中断时间对用户和IPA导致的中断的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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