Designing Conversational Agents: A Self-Determination Theory Approach


Bringing positive experiences to users is one of the key goals when designing conversational agents (CAs). Yet we still lack an understanding of users’ underlying needs to achieve positive experiences and how to support them in design. This research first applies Self-Determination Theory in an interview study to explore how users’ needs of competence, autonomy and relatedness could be supported or undermined in CA experiences. Ten guidelines are then derived from the interview findings. The key findings demonstrate that: competence is affected by users’ knowledge of the CA capabilities and effectiveness of the conversation; autonomy is influenced by flexibility of the conversation, personalisation of the experiences, and control over user data; regarding relatedness, users still have concerns over integrating social features into CAs. The guidelines recommend how to inform users about the system capabilities, design effective and socially appropriate conversations, and support increased system intelligence, customisation, and data transparency.

Xi Yang
Imperial College London, London, United Kingdom
Marco Aurisicchio
Imperial College London, London, United Kingdom




会議: CHI 2021

The ACM CHI Conference on Human Factors in Computing Systems (

セッション: Meetings, Chats, and Speech

[A] Paper Room 15, 2021-05-10 17:00:00~2021-05-10 19:00:00 / [B] Paper Room 15, 2021-05-11 01:00:00~2021-05-11 03:00:00 / [C] Paper Room 15, 2021-05-11 09:00:00~2021-05-11 11:00:00
Paper Room 15
11 件の発表
2021-05-10 17:00:00
2021-05-10 19:00:00