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Synthetic Emotions vs. Gamification: Exploring Engagement Strategies for Small Social Robots in Different Age Groups

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Host publication Subtitle

Results from the 13th International Conference on Robot Intelligence Technology and Applications, Volume 1

Original language

English

Pages from-to (Number of pages)

Pages 1-7 (7 pages)

Publication milestones

  • Published - 22/07/2026

Publication status

Published - 22/07/2026

Volume

1

Publisher

Springer, United States, Germany

Book series

  • Book series name: Lecture Notes in Networks and Systems
    ISSN: 2367-3370

ISBN (Electronic)

978-3-032-23009-6

Publication IDs

  • ORCID: /0000-0002-5646-5195/work/222748708

Host publication title

Robot Intelligence Technology and Applications 10

Abstract

Many children experience challenges in emotional regulation and social interaction, which can limit their participation in everyday activities and therapeutic programs. For socially assistive robots to be effective in this context, it is essential that children remain consistently and meaningfully engaged. We explore engagement strategies for a tactile robot designed to support children suffering from anxiety disorders through daily interactions. The robot delivers either synthetic emotional feedback or point rewards to encourage user participation. We evaluated these strategies through two studies: a preference assessment with 16 school children aged 6-8 years, and a behavioral study with 14 university students aged 20-27 years in naturalistic environments. The study with school children indicated a preference for emotional engagement over points-based approaches. The follow up study with university students across a full day of interactions revealed contrasting results: points-based systems produced significantly higher task accuracy (p < 0.05) and sustained performance over time. Findings from different user groups suggest that stated preferences and behavioral outcomes can diverge depending on engagement context, highlighting the importance of validating design assumptions through observed interaction. This work contributes insights into age-related differences in engagement strategy effectiveness in human-robot interaction design.

Related Event

Title

Robot Intelligence Technology and Applications

Event type

Conference

Degree of recognition

International event

Date

17/12/2025 - 19/12/2025

Location

LondonUnited Kingdom