Exploring the Impact of Designing a Robot as a Pet with Interdependence Theory on Long-Term Relationships and Learning Performance

Abstract

Educational robots have shown promise in enhancing learning performance; but, many of these robots function solely as companions or tutors and rely on novelty to attract attention, making it challenging to maintain long-term relationships. Although pet robots have been utilized to create relationships with users, their potential in education remains underexplored. This study addresses this issue by designing a robot as a pet, applying the interdependence theory to establish lasting relationships and improve learning performance. The interdependence theory suggests that relationships between individuals can be strengthened through mutual dependence and the fulfillment of each other's needs. In this study, learners were prompted to engage in continuous care for their pet robots, receiving emotional reinforcement from them seamlessly across both virtual and tangible forms enabled by the ChatGPT API. To culminate their learning process, learners presented their ultimate learning outcomes alongside their pet robots, enacting situational dramas for their classmates. To evaluate the effectiveness of this approach, a quasi-experiment was conducted with 100 undergraduate learners enrolled in a Japanese for Hospitality and Tourism course in Taiwan. Results indicate that robots designed as pets, leveraging interdependence theory, significantly yield positive effects on learners, encompassing improved learning outcomes, extended interaction rates, and heightened satisfaction with their study journey compared to conventional robots. The study concludes by discussing research limitations and offering suggestions for further enhancements to this approach.