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ProtoChat: Supporting the Conversation Design Process with Crowd Feedback

Published: 05 January 2021 Publication History

Abstract

Similar to a design process for designing graphical user interfaces, conversation designers often apply an iterative design process by defining a conversation flow, testing with users, reviewing user data, and improving the design. While it is possible to iterate on conversation design with existing chatbot prototyping tools, there still remain challenges in recruiting participants on-demand and collecting structured feedback on specific conversational components. These limitations hinder designers from running rapid iterations and making informed design decisions. We posit that involving a crowd in the conversation design process can address these challenges, and introduce ProtoChat, a crowd-powered chatbot design tool built to support the iterative process of conversation design. ProtoChat makes it easy to recruit crowd workers to test the current conversation within the design tool. ProtoChat's crowd-testing tool allows crowd workers to provide concrete and practical feedback and suggest improvements on specific parts of the conversation. With the data collected from crowd-testing, ProtoChat provides multiple types of visualizations to help designers analyze and revise their design. Through a three-day study with eight designers, we found that ProtoChat enabled an iterative design process for designing a chatbot. Designers improved their design by not only modifying the conversation design itself, but also adjusting the persona and getting UI design implications beyond the conversation design itself. The crowd responses were helpful for designers to explore user needs, contexts, and diverse response formats. With ProtoChat, designers can successfully collect concrete evidence from the crowd and make decisions to iteratively improve their conversation design.

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Published In

cover image Proceedings of the ACM on Human-Computer Interaction
Proceedings of the ACM on Human-Computer Interaction  Volume 4, Issue CSCW3
CSCW
December 2020
1825 pages
EISSN:2573-0142
DOI:10.1145/3446568
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 05 January 2021
Published in PACMHCI Volume 4, Issue CSCW3

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Author Tags

  1. chatbot design
  2. conversation design
  3. conversational user interface
  4. crowd feedback
  5. crowd testing
  6. crowdsourcing
  7. design iteration
  8. design process

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  • Research-article

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  • Samsung Research, Samsung Electronics Co., Ltd.

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  • (2024)Active Utterance Collection Based on Multi-armed Bandits for Natural Language Understanding in Dialog SystemsInformation Integration and Web Intelligence10.1007/978-3-031-78093-6_11(124-139)Online publication date: 1-Dec-2024
  • (2023)Scalable Design Evaluation for Everyone! Designing Configuration Systems for Crowd-Feedback Request GenerationProceedings of Mensch und Computer 202310.1145/3603555.3603566(91-100)Online publication date: 3-Sep-2023
  • (2023)Aligning Crowdworker Perspectives and Feedback Outcomes in Crowd-Feedback System DesignProceedings of the ACM on Human-Computer Interaction10.1145/35794567:CSCW1(1-28)Online publication date: 16-Apr-2023
  • (2023)Leveraging Large Language Models as Simulated Users for Initial, Low-Cost Evaluations of Designed ConversationsChatbot Research and Design10.1007/978-3-031-54975-5_5(77-93)Online publication date: 22-Nov-2023
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  • (2022)Towards User-Centric Guidelines for Chatbot Conversational DesignInternational Journal of Human–Computer Interaction10.1080/10447318.2022.211824440:2(98-120)Online publication date: 9-Sep-2022
  • (2022)Implementing scripted conversations by means of smart assistantsSoftware: Practice and Experience10.1002/spe.318253:5(1271-1283)Online publication date: 20-Dec-2022
  • (2021)CharacterChat: Supporting the Creation of Fictional Characters through Conversation and Progressive Manifestation with a ChatbotProceedings of the 13th Conference on Creativity and Cognition10.1145/3450741.3465253(1-10)Online publication date: 22-Jun-2021
  • (2021)Eliciting and Analysing Users’ Envisioned Dialogues with Perfect Voice AssistantsProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445536(1-15)Online publication date: 6-May-2021

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