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Evaluating Gemini in an arena for learning

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arxiv 2505.24477 v1 pith:W7TVENUX submitted 2025-05-30 cs.CY cs.AIcs.LG

Evaluating Gemini in an arena for learning

classification cs.CY cs.AIcs.LG
keywords learninggeminiarenamodelsexpertscaseseducatorsleading
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Artificial intelligence (AI) is poised to transform education, but the research community lacks a robust, general benchmark to evaluate AI models for learning. To assess state-of-the-art support for educational use cases, we ran an "arena for learning" where educators and pedagogy experts conduct blind, head-to-head, multi-turn comparisons of leading AI models. In particular, $N = 189$ educators drew from their experience to role-play realistic learning use cases, interacting with two models sequentially, after which $N = 206$ experts judged which model better supported the user's learning goals. The arena evaluated a slate of state-of-the-art models: Gemini 2.5 Pro, Claude 3.7 Sonnet, GPT-4o, and OpenAI o3. Excluding ties, experts preferred Gemini 2.5 Pro in 73.2% of these match-ups -- ranking it first overall in the arena. Gemini 2.5 Pro also demonstrated markedly higher performance across key principles of good pedagogy. Altogether, these results position Gemini 2.5 Pro as a leading model for learning.

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