HEC视域下数理统计“人机共协”课堂生态构建研究

Research on the Construction of a “Human-Machine Collaborative” Classroom Ecology in Mathematical Statistics from the Perspective of HEC

摘要: 人工智能技术的迅猛发展对传统《数理统计》教学模式提出了严峻挑战，计算技能的弱化与统计直觉的减退并存。本文基于人机共协计算(HEC)理念，提出从“知识传授”向“能力共协”转型的教学重构路径。其中，能力共协指人类统计思辨能力与机器计算建模能力分工互补、协同完成数据分析全流程，区别于单一依靠人工计算或完全依赖AI黑箱的单向能力模式。通过构建“人定界、机执行、人决策”的三阶段教学模型，重构了从描述统计到因果推断的教学内容体系，并设计了“异常值博弈”、“P值陷阱”及“回归黑箱”三个典型教学案例。理论推演表明，该“人机共协”课堂生态具备提升学生统计批判性思维与数据伦理意识的潜力，可为AI时代培养复合型统计人才提供理论层面的改革思路，相关教学成效有待后续实证教学实验进一步验证。

Abstract: The rapid advancement of artificial intelligence technology poses a severe challenge to traditional “Mathematical Statistics” teaching models, characterized by the weakening of computational skills and the decline of statistical intuition. Based on the Human-Machine Collaborative Computing (HEC) concept, this paper proposes a teaching transformation path from “knowledge transmission” to “capacity collaboration”. Capacity collaboration refers to the division of labor and complementary collaboration between human statistical reasoning and machine computational modeling, jointly completing the entire data analysis process, differing from unidirectional models that rely solely on manual computation or fully depend on AI black-box operations. By constructing a three-stage teaching model of “human-defined boundaries, machine execution, and human decision-making”, the teaching content system is restructured from descriptive statistics to causal inference, with three typical teaching cases designed: “Outlier Game”, “P-value Trap”, and “Regression Black Box”. Theoretical analysis demonstrates that this “human-machine collaborative” classroom ecology has the potential to enhance students’ statistical critical thinking and data ethics awareness, offering theoretical reform insights for cultivating interdisciplinary statistical talents in the AI era. The effectiveness of these teaching strategies requires further validation through subsequent empirical teaching experiments.