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融入思政元素的矩阵向量乘算法教学实践
Teaching Practice of Matrix Vector Multiplication Algorithm with Ideological and Political Elements

DOI: 10.12677/ae.2024.14122350, PP. 855-861

Keywords: 思政教育,矩阵向量乘算法,数据轮换技术,矩阵分层结构
Ideological and Political Education
, Matrix Vector Multiplication Algorithm, Data Rotation Technology, Matrix Hierarchical Structure

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Abstract:

随着新时代教育理念的深入推进,将思政教育融入数学教学已成为一项重要的教学改革方向。本研究旨在探讨矩阵向量乘算法的教学实践中,如何有效融合思政元素,以提升学生的数学素养和思政素养。通过设计以实际应用为背景的课堂教学案例,如利用数据轮换技术和矩阵分层结构,采用情境教学、合作学习和讨论引导等多种教学策略,促使学生在学习矩阵向量乘算法的同时,理解其中蕴含的思想政治教育意义。实践结果表明,学生在掌握矩阵向量乘算法的同时,思政素养显著提升,学习积极性和主动性得到增强,建议进一步探索思政教育与其他教学内容的结合,以实现更为全面的教育目标。
With the deepening of the education concept in the new era, integrating ideological and political education into mathematics teaching has become an important teaching reform direction. This study aims to explore how to effectively integrate ideological and political elements in the teaching practice of matrix vector multiplication algorithm, so as to improve students’ mathematical literacy and ideological and political literacy. This study, by utilizing teaching cases based on practical applications such as data permutation techniques and matrix layered structures, employs multiple teaching strategies including situational teaching, cooperative learning, and discussion guidance. This approach aims to facilitate students’ understanding of the ideological and political education significance embedded in the matrix-vector multiplication algorithm while learning it. The practice results show that while students master the matrix vector multiplication algorithm, their ideological and political literacy is significantly improved, and their learning enthusiasm and initiative are enhanced. It is suggested to further explore the combination of ideological and political education with other teaching content to achieve more comprehensive education goals.

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