AI赋能下统计计算课程教学的BOPPPS框架设计——基于重庆科技大学的方案构想

Design of BOPPPS Framework for Statistics Computing Teaching Empowered by AI—A Scheme Conception Based on Chongqing University of Science and Technology

摘要: 人工智能技术的快速发展正在深刻重塑统计计算的教学形态。本文以重庆科技大学应用统计专业硕士《统计计算》课程为研究对象，针对该课程教学中存在的理论抽象、实践性强、学生参与度较低等问题，提出以AI赋能为驱动、以BOPPPS闭环教学模式为框架的课程教学设计方案。首先，结合“产教融合、数智赋能”的应用型人才培养定位，分析将生成式人工智能嵌入“导学–目标–前测–参与式学习–后测–总结”六环节教学流程的具体路径；其次，探讨了知识图谱驱动的智慧课程资源建设方案；最后，设计“AI辅助 + 项目驱动”的形成性评价机制。

Abstract: The rapid advancement of artificial intelligence (AI) is profoundly reshaping the teaching of statistical computing. Taking the “Statistical Computing” course for master’s students in Applied Statistics at Chongqing University of Science and Technology as the research subject, this paper addresses key challenges in the course, including abstract theoretical content, strong practical demands, and low student engagement. To tackle these issues, the study proposes a teaching design scheme driven by AI empowerment within a closed-loop BOPPPS teaching model. First, grounded in the applied talent cultivation orientation of “industry-education integration and digital intelligence empowerment”, the study analyzes the specific pathways for integrating generative AI into the six-stage teaching process: Bridge-in, Objective, Pre-assessment, Participatory Learning, Post-assessment, and Summary. Second, it discusses the development of a knowledge graph-driven smart course resource system. Finally, a formative assessment mechanism based on “AI assistance + project-driven” approaches is designed.