Abstract
As a new intermediary in smart education, artificial intelligence may weaken teacher-student interaction and induce relational alienation. Existing research overemphasizes technological efficacy while neglecting sociocultural impacts, particularly lacking an integrated framework to explain the generative logic of teacher-student relationship alienation. Grounded in educational alienation theory, this study constructs a technology-agent-environment triadic framework, examining technological characteristics (AI interaction capability and algorithmic black-box), agent competencies (teachers’ digital literacy and teaching rigidity, students’ self-efficacy and technology dependence), and environmental regulation (school evaluation system), with teacher-student interaction quality as a mediator. Based on 539 questionnaire responses analyzed via structural equation modeling, results indicate that teachers’ digital literacy, teaching rigidity, AI interaction capability, and student technology dependence significantly affect interaction quality, which significantly negatively impacts relationship alienation; student self-efficacy and algorithmic opacity show no significant effects. Multi-group analysis reveals that the school evaluation system significantly moderates paths from digital literacy, teaching rigidity, AI interaction capability, and algorithmic black-box to interaction quality. This study provides an integrated analytical framework and practical guidance for balancing technological application with teacher-student interaction.
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