DAPIE: Interactive Step-by-Step Explanatory Dialogues to Answer Children’s Why and How Questions


Children acquire an understanding of the world by asking "why'' and "how'' questions. Conversational agents (CAs) like smart speakers or voice assistants can be promising respondents to children's questions as they are more readily available than parents or teachers. However, CAs' answers to "why'' and "how'' questions are not designed for children, as they can be difficult to understand and provide little interactivity to engage the child. In this work, we propose design guidelines for creating interactive dialogues that promote children's engagement and help them understand explanations. Applying these guidelines, we propose DAPIE, a system that answers children's questions through interactive dialogue by employing an AI-based pipeline that automatically transforms existing long-form answers from online sources into such dialogues. A user study (N=16) showed that, with DAPIE, children performed better in an immediate understanding assessment while also reporting higher enjoyment than when explanations were presented sentence-by-sentence.

Yoonjoo Lee
KAIST, Daejeon, Korea, Republic of
Tae Soo Kim
KAIST, Daejeon, Korea, Republic of
Sungdong Kim
NAVER AI Lab, Seongnam, Korea, Republic of
Yohan Yun
KAIST, Suwon, Gyeonggi, Korea, Republic of
Juho Kim
KAIST, Daejeon, Korea, Republic of



会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Learning with and about AI

Hall B
6 件の発表
2023-04-26 18:00:00
2023-04-26 19:30:00