Attachment and Affection Models in Human–Robot Interaction: Implications for Motivation and Engagement in Academic Settings

This paper explores the application of attachment and affection models within the context of Human– Robot Interaction (HRI), with a focus on academic and therapeutic settings. Drawing upon theories such as Bowlby’s Attachment Theory, the Self-Determination Theory (SDT), and Social Presence models, the study examines how emotional connection to social robots can foster intrinsic motivation, trust, and learning engagement. The research discusses the importance of secure attachment, emotional expressiveness, and adaptive behavior in the design of educational and therapeutic robots. It also integrates findings from a Bulgarian empirical study on academic motivation, highlighting the role of personality traits, institutional perception, and affective factors. The results suggest that incorporating affect-sensitive robotic design and attachment-informed strategies can enhance student motivation and support vulnerable learner groups through emotionally intelligent interaction.