Enhancing Response Quality by Children in Voice-based Sleep Diaries via AI-based Continuous Feedback

要旨

Digital sleep diaries are widely used to monitor children’s sleep, yet response quality is often low because children may not know how, or be motivated, to give detailed answers. We investigate how “live,” continuous feedback in voice-based sleep diaries can support higher-quality responses. In a co-design workshop, we explored children's preferences for different forms of feedback. We designed and compared experimentally symbolic, numeric, and no-feedback conditions, showing that both feedback types improved response quality across questions. Finally, an eight-day field study revealed that feedback resulted in higher and more consistent quality in self-report over time. Across these three studies, children valued playful and clear feedback, with preferences shifting depending on their cognitive needs. Our findings demonstrate that effective feedback must balance affective engagement with cognitive clarity and adapt to different contexts. We contribute empirically supported design insights to enhance children's adherence and response quality in voice-based self-report surveys.

著者
Shanshan Chen
Eindhoven University of Technology, Eindhoven, Netherlands
Jun Hu
Eindhoven University of Technology, Eindhoven, Netherlands
Gubing Wang
Tilburg University , Tilburg , Netherlands
Panos Markopoulos
Eindhoven University of Technology, Eindhoven, Netherlands

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: AI, Learning and Inclusion in Education

P1 - Room 114
7 件の発表
2026-04-16 20:15:00
2026-04-16 21:45:00