概率论与数理统计课程是一门在高校中广泛开设的公共基础课程,其在信息技术背景下开展课程思政建设有着重大的意义。知识图谱作为一种信息技术手段,其知识网格可视化、联想等功能应用于教育领域有着不可忽视的优势。因此,文章基于知识图谱的语义化组织特性及概率论与数理统计课程自身的特点,提出了“1 + 2 + 3”课程思政教学模式及课程思政知识图谱的构建路径,为全面落实以学生为主体的教学方针提供了新的思路和方法。The Probability and Statistics is a fundamental subject extensively taught in higher education institutions. It plays a pivotal role in the development of course-based ideological and political education, especially in the context of information technology. Knowledge graph, as a technological tool, offers unique advantages in education through its visualization of knowledge networks and associative capabilities. Leveraging these strengths, the article introduces an innovative “1 + 2 + 3” model for course-based ideological and political education, along with a construction path for a curriculum civics knowledge graph. This approach offers a fresh perspective and methodology for the comprehensive implementation of student-centered teaching strategies.
高等数学是高等院校工科专业的必修课,思政教育目的是引导学生树立正确的世界观、人生观、价值观,更好地认识世界、改造世界。本文基于高等数学的课程特点,从分层教学、融合教学和生动教学三个方面,以哲学理念为“神”、数学分析方法为“形”开展教学实践,将思想政治教育中哲学、时政和人生观等要素融入高等数学的课程中。根据高等数学的知识结构,以章节为基础引入思想政治要素点,完成高等数学的总体思政课程设计,为广大高等数学教学工作者的教学实践提供参考。Advanced mathematics is a required course for science and engineering majors in universities. The aim of ideological and political education is to guide students to set up correct values, understand and reform the world. Based on the characteristics of advanced mathematics course, this paper conducts teaching practice from three aspects: hierarchical teaching, integrated teaching and vivid teaching. With philosophical concepts as the “connotation” and mathematical analysis methods as the “form”, we integrate elements such as philosophy, current affairs, and outlook on life in ideological and political education into the curriculum of higher mathematics. Moreover, based on the knowledge structure of advanced mathematics, this paper introduces ideological and political elements based on chapters, completes the overall ideological and political curriculum design of advanced mathematics, and provides references for the teaching practice of advanced mathematics teachers.
数据挖掘是统计学、数据科学和计算机科学与技术等专业开设的专业课。数据挖掘课程的实践教学质量是专业素养培养的重要内容。为了进一步提高课程实践教学质量,本文将探讨企业课堂与校园课堂并行的“双课堂”教学模式。在课程新模式下,改革了实践教学的教学内容、授课教师、学业评价和教学环境。问卷调查显示:(1) 企业课堂不仅让学生体验到了企业数据挖掘的真实场景,也帮助他们更好地理解了算法原理。(2) 学生认为在线的企业课堂不仅节约时间而且灵活性高,是校内课堂的有益补充。(3) “双课堂”模式下的实践教学获得了学生的好评,学生愿意向同学和朋友推荐企业课堂。Data mining is a specialized course offered in many majors such as statistics, data science and computer science and technology. The quality of practical teaching in data mining courses is an important aspect of cultivating professional competence. In order to further improve the quality of practical teaching in the course, this article will discuss the “dual classroom” teaching model of parallel company classroom and campus classroom. In the new model, the teaching content, instructors, academic evaluation, and teaching environment of practical teaching have been reformed. The questionnaire survey shows that: (1) The company classroom not only allows students to experience the real scenarios of company data mining, but also helps them understand the principles of algorithms better. (2) Students believe that online company classrooms are not only time-saving but also flexible. Company classroom is a useful supplement to campus classrooms. (3) Practical teaching under the “dual classroom” model receives positive feedback from students. Students are willing to recommend the company classroom to their classmates and friends.
