Teacher or Artificial Intelligence? The Effect of Decision-Making Agent on Junior High School Students’ Decision Acceptance: A Moderated Mediation Model

Artificial intelligence (AI) is increasingly used in educational decision-making. This raises important questions about how students perceive and accept outcomes from non-human agents. Based on authority acceptance theory and organizational justice theory, this study explored three research questions: how decision-making agents (teachers vs. AI) affect junior high school students’ acceptance of educational decisions, the mediating mechanism of perceived fairness, and the moderating effect of explanatory feedback. This study adopted a 2 (decision-making agent: teacher vs. AI) × 2 (explanatory feedback: with vs. without explanation) between-subjects experimental design, with 250 seventh-grade students as participants. Results showed that students reported significantly higher decision acceptance and perceived fairness for teacher-made decisions than for AI-generated decisions. Perceived fairness partially mediated the relationship between the decision-making agent and decision acceptance. The mediating effect accounted for 67.52% of the total effect. Explanatory feedback positively moderated only the path from the decision-making agent to perceived fairness, with no significant moderating effect on the direct link between the decision-making agent and decision acceptance. Provision of explanations widened the human–AI gap in perceived fairness, which in turn further enlarged the gap in decision acceptance via the mediating pathway of perceived fairness. These findings extend research on explanatory feedback to the basic education context, while highlighting the significance of teacher-led human–AI collaboration and interpretable AI design amid the digital transformation of education.