AI RESEARCH
How AI Systems Think About Education: Analyzing Latent Preference Patterns in Large Language Models
arXiv CS.AI
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ArXi:2603.21006v1 Announce Type: cross This paper presents the first systematic measurement of educational alignment in Large Language Models. Using a Delphi-validated instrument comprising 48 items across eight educational-theoretical dimensions, the study reveals that GPT-5.1 exhibits highly coherent preference patterns (99.78% transitivity; 92.79% model accuracy) that largely align with humanistic educational principles where expert consensus exists.