人工智能时代的数学研究生培养
Mathematics Graduate Training in the Age of AI
浏览论文内容
中文总结 AI 辅助
本文主张在生成式AI改变数学学习与评估方式的背景下，数学研究生培养应明确目标，以“数学判断”能力为核心进行训练，并探讨相应政策。
中文摘要 AI 辅助
生成式人工智能改变了研究生数学学习、评估、写作和答辩的条件。本文的核心主张是，数学研究生项目应通过明确研究生数学教育旨在教授和评估的内容来回应这一时刻。在大多数方面，数学教育的目标并未改变。相反，随着工具的不断变化，明确数学培训的目标变得比以往任何时候都更加重要。我们使用“数学判断”这一术语来指代评估数学（例如，论断、定义、例子、证明、类比、计算、工具的使用、研究方向）在数学上是否健全、有用、适定且论证恰当的能力。我们的建议是将培训重点放在数学判断上，并为此考察了数学研究生项目可能采取的政策。
英文摘要
Generative AI changes the conditions under which graduate mathematics is learned, assessed, written, and defended. The central claim of this paper is that mathematics graduate programs should respond to the moment by clarifying what graduate mathematics education is trying to teach and assess. In most ways, the goals of mathematics education have not changed. Rather, with changing tools it has become more essential than ever to make clear the goals of mathematical training. We use the term mathematical judgment to refer to the capacity to evaluate mathematics (e.g., claims, definitions, examples, proofs, analogies, computations, uses of tools, research directions) as mathematically sound, useful, well-posed, and appropriately justified. The recommendation is to center training on mathematical judgment, and we examine possible policies for graduate programs in Mathematics to this end.
发表机构
- University of Arizona（亚利桑那大学）
机构由 AI 辅助整理，请以论文原文为准。
