Rethinking Student-Robot Social Interactions in GenAI Capitalism and its Role in Shaping Cybersocialization through a Sociological Lens

Abstract

This study investigates the effects of artificial intelligence (AI) on social interactions in educational settings, with a particular focus on student-robot interactions within the framework of generative AI (GenAI) capitalism. It examines how these interactions shape cybersocialization from a sociological perspective. The goal is to investigate how AI-powered systems like virtual assistants, chatbots, and intelligent tutoring systems impact students' emotional, social, and collaborative abilities in both in-person and online learning environments. The study used a mixed-methods approach, surveying 29 professionals in pre-service teacher education and conducting five student interviews using semi-structured questions. We derived qualitative insights from open-ended responses and analyzed quantitative data using descriptive statistics, t-tests, ANOVA, and Cronbach's alpha. The results demonstrate that tools driven by AI improve student engagement, encourage group work, and offer emotional support while studying. However, issues such as data privacy, the digital divide, and achieving a balance between AI-driven and human-driven interactions emerged. The study suggests a mixed approach to education, using AI to supplement rather than supplant human interactions. To ensure equal access to technology, the study emphasizes the importance of AI tool training for teachers and advocates for measures to reduce the digital divide. Furthermore, as a future paradigm for education, we propose a cybersocialization approach that encourages both technical competence and vital interpersonal relationships.