Exploring Users' Preferences for Chatbot's Guidance Type and Timing

Meng Hsin Wu, Su Fang Yeh, Xi Jing Chang, Yung Ju Chang

研究成果: Conference contribution同行評審

2 引文 斯高帕斯(Scopus)

摘要

While task-oriented chatbots have become popular recently, conversational breakdowns are still common and will often lead to unfavorable user experiences. Guidance serves a crucial role in helping users to understand how to have better interaction with chatbots. Nonetheless, questions like what kinds of guidance to provide and when to provide guidance remain underexplored. In this study, we examined users' preferences for two types of guidance (Example-Based and Rule-Based) at four guidance timings (Service- Onboarding, Task-Intro, After-Failure, and Upon-Request). Our results show that users preferred Example-based guidance, and generally preferred guidance provided at Task-Intro. Example-based guidance appearing at Task-Intro was the favorite guidance combination for most participants. Through analysis of participants' explanations of their preferences, the strengths and weaknesses of these guidance types and guidance timings are presented. The preliminary results are based on a subset of the data (n=24). Further in-depth investigation into the underlying factors that influence users' preferences for guidance, as well as the interplay effect between guidance type and guidance timing is needed.

原文English
主出版物標題CSCW 2021 - Conference Companion Publication of the 2021 Computer Supported Cooperative Work and Social Computing
發行者Association for Computing Machinery
頁面191-194
頁數4
ISBN(電子)9781450384797
DOIs
出版狀態Published - 23 10月 2021
事件24th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2021 - Virtual, Online, United States
持續時間: 23 10月 202127 10月 2021

出版系列

名字Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW

Conference

Conference24th ACM Conference on Computer-Supported Cooperative Work and Social Computing, CSCW 2021
國家/地區United States
城市Virtual, Online
期間23/10/2127/10/21

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