《Python程序开发语言》是数据科学与大数据技术和应用统计学等专业的一门专业必修课程,其课程的教学体系建设对培养学生的动手实践能力和创新思维意义非凡,且能为学生以后学习大数据、人工智能奠定基础。因此,本文以重庆科技大学《Python程序开发语言》课程教学现状中的“痛点”为例,构建“图谱式教学内容、项目式教学实践、混合式教学手段、特色式教学思政、多元式考核体系”的“五式”创新举措,实现教学与专业教育、特色育人、实践创新紧密联系的“三联”目标,全面解决痛点问题。实践表明:知识图谱的应用全面提高了学生学习的学习效率,大幅度地提高了学生灵活运用Python语言解决实际问题的能力。此体系能为当前Python语言课程教学体系改革提供参考。“Python Programming Language” is a compulsory professional course for majors such as data science and big data technology, and applied statistics. The construction of its teaching system plays a crucial role in cultivating students’ practical ability and innovative thinking, and can lay a foundation for students’ future study of big data and artificial intelligence. Therefore, taking the “pain points” in the teaching of “Python Programming Language” at Chongqing University of Science and Technology as an example, this paper constructs the “five-mode” innovative measures of “knowledge-graph-based teaching content, project-based teaching practice, blended teaching methods, characteristic-based ideological and political education in teaching, and a diversified assessment system”. These measures aim to achieve the “three-connection” goals of closely integrating teaching with professional education, characteristic education, and practical innovation, comprehensively addressing the pain points. Practice shows that the application of knowledge graphs has comprehensively improved students’ learning efficiency and signi
随着信息技术的飞速发展,Python语言的学习愈发关键,但其传统教学模式在培育学生实践能力上渐显乏力。本研究通过剖析传统教学的弊端,梳理国内外关于Python语言教学改革的成果,提出了基于强化学习行为模型(RLBM)行为模式的教学改革思路。RLBM由:智能体(agent)、环境(environment)、动作(action)和奖励(reward)四大核心要素构成,学生通过不断试错,依据环境反馈的奖励信号来学习最优策略。该教学方法在四川大学锦江学院进行了教学实践,结果表明,此方法极大提升了教学成效、并有效激发了学生自主学习能力,为程序设计类课程教学改革提供创新性的思路与实践参考。With the rapid development of information technology, learning the Python language has become increasingly crucial. However, the traditional teaching model is gradually showing its inadequacy in cultivating students’ practical abilities. This research analyzes the drawbacks of traditional teaching, sorts out the achievements of Python language teaching reform both at home and abroad, and puts forward the ideas for teaching reform based on the behavior mode of the Reinforcement Learning Behavior Model (RLBM). The RLBM consists of five core elements: agent, environment, state, action, and reward. Students learn the optimal strategies by constantly making trial-and-error attempts and relying on the reward signals fed back by the environment. This teaching method has been implemented in teaching practice at Jinjiang College of Sichuan University. The results show that this method has significantly improved teaching effectiveness and effectively stimulated students’ autonomous learning ability, providing innovative ideas and practical references for the teaching reform of programming courses.
