Cooking with Conversation: Enhancing User Engagement and Learning with a Knowledge-Enhancing Assistant

IF 5.4 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Alexander Frummet, Alessandro Speggiorin, David Elsweiler, Anton Leuski, Jeff Dalton
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引用次数: 0

Abstract

We present two empirical studies to investigate users’ expectations and behaviours when using digital assistants, such as Alexa and Google Home, in a kitchen context: First, a survey (N=200) queries participants on their expectations for the kinds of information that such systems should be able to provide. While consensus exists on expecting information about cooking steps and processes, younger participants who enjoy cooking express a higher likelihood of expecting details on food history or the science of cooking. In a follow-up Wizard-of-Oz study (N = 48), users were guided through the steps of a recipe either by an active wizard that alerted participants to information it could provide or a passive wizard who only answered questions that were provided by the user. The active policy led to almost double the number of conversational utterances and 1.5 times more knowledge-related user questions compared to the passive policy. Also, it resulted in 1.7 times more knowledge communicated than the passive policy. We discuss the findings in the context of related work and reveal implications for the design and use of such assistants for cooking and other purposes such as DIY and craft tasks, as well as the lessons we learned for evaluating such systems.

用对话烹饪:利用知识强化助手提高用户参与度和学习效果
我们介绍了两项实证研究,以调查用户在厨房环境中使用 Alexa 和 Google Home 等数字助理时的期望和行为:首先,一项调查(N=200)询问了参与者对此类系统应能提供的信息种类的期望。虽然对烹饪步骤和流程信息的期望已达成共识,但喜欢烹饪的年轻参与者表示更有可能期望获得有关食物历史或烹饪科学的详细信息。在一项 "向导"(Wizard-of-Oz)的后续研究(N = 48)中,用户在菜谱步骤中的指导可以是主动向导(提醒参与者它可以提供的信息),也可以是被动向导(只回答用户提出的问题)。与被动向导相比,主动向导所产生的对话语句数量几乎是被动向导的两倍,而与知识相关的用户提问数量则是被动向导的 1.5 倍。此外,主动政策所传播的知识也是被动政策的 1.7 倍。我们将在相关工作的背景下讨论这些研究结果,并揭示设计和使用此类烹饪助手及其他用途(如 DIY 和手工任务)的意义,以及我们在评估此类系统时学到的经验。
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来源期刊
ACM Transactions on Information Systems
ACM Transactions on Information Systems 工程技术-计算机:信息系统
CiteScore
9.40
自引率
14.30%
发文量
165
审稿时长
>12 weeks
期刊介绍: The ACM Transactions on Information Systems (TOIS) publishes papers on information retrieval (such as search engines, recommender systems) that contain: new principled information retrieval models or algorithms with sound empirical validation; observational, experimental and/or theoretical studies yielding new insights into information retrieval or information seeking; accounts of applications of existing information retrieval techniques that shed light on the strengths and weaknesses of the techniques; formalization of new information retrieval or information seeking tasks and of methods for evaluating the performance on those tasks; development of content (text, image, speech, video, etc) analysis methods to support information retrieval and information seeking; development of computational models of user information preferences and interaction behaviors; creation and analysis of evaluation methodologies for information retrieval and information seeking; or surveys of existing work that propose a significant synthesis. The information retrieval scope of ACM Transactions on Information Systems (TOIS) appeals to industry practitioners for its wealth of creative ideas, and to academic researchers for its descriptions of their colleagues'' work.
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