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English(EN) Flawed but Memorable: Student Critical Reception of Interest-Personalized GenAI Analogies in Computing Education

AI类比在教育中的应用：学生认为有趣但存在缺陷

作者 PulseAugur 编辑部 · [1 个来源] ·

一项涉及十名计算机科学本科生的研究发现，与通用解释相比，由AI生成的兴趣个性化类比被认为更具吸引力和记忆性，但学生对这些类比的信任度却参差不齐。具有更深领域知识的学生能够识别类比中的结构性缺陷，这凸显了AI系统需要评估学生知识而非仅仅是兴趣。研究表明，生成式AI应将有缺陷的类比视为检查和纠正的机会。 AI

影响 AI生成的类比可以提高参与度，但需要仔细评估其准确性和潜在假设。

排序理由 关于AI在教育中应用的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

AI类比在教育中的应用：学生认为有趣但存在缺陷

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关于AI在教育中应用的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Seth Bernstein, Naaz Sibia ·

    有缺陷但令人难忘：学生对计算教育中兴趣个性化生成式AI类比的批判性评价

    arXiv:2609.06095v1 Announce Type: cross Abstract: Motivation: Undergraduate computing students increasingly turn to generative AI (GenAI) tools to understand abstract concepts through analogies. Analogies compare an unfamiliar concept to something familiar, but judging whether th…

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