基于“BOPPPS”教学模式下的概率论与数理统计教学设计——以“贝叶斯公式”为例

Teaching Design of Probability Theory and Mathematical Statistics Based on “BOPPPS” Teaching Mode—Taking “Bayesian Formula” as an Example

摘要: 概率论与数理统计课程兼具抽象理论性与实践应用性，这一特性对传统教学模式提出了新的挑战。BOPPPS教学模式构建了“导入–目标–前测–参与式学习–后测–总结”的完整闭环，解决了传统教学的照本宣科、针对性弱以及学用脱节等问题。本文以“贝叶斯公式”这一核心知识点为研究对象，构建一套针对性突出、可直接落地的教学方案，旨在破解学生对抽象统计概念的理解难题，切实提升其知识迁移与应用能力。

Abstract: The courses of probability theory and mathematical statistics have both abstract theory and practical application, which poses a new challenge to the traditional teaching mode. BOPPPS teaching mode has built a complete closed loop of “introduction-goal-pre-test-participatory learning-post-test-summary”, which has solved the problems of traditional teaching, such as scripted, weak pertinence and disjointed learning and application. In this paper, the core knowledge point “Bayesian formula” is taken as the research object, and a set of targeted and directly applicable teaching scheme is constructed, aiming at solving the problem of students’ understanding of abstract statistical concepts and effectively improving their knowledge transfer and application ability.