高等数学教学成效的困境分析与改进路径探析
Analysis of Challenges in Teaching Higher Mathematics and Exploration of Improvement Pathways
摘要: 本文聚焦大学生高等数学学习成效的影响因素,以滇西科技师范学院2022级工科与经管类学生为研究对象,通过问卷调查收集数据,运用层次分析法(AHP)构建多层次评价体系。研究将影响因素划分为个人、内在动机、班级、学校与外在条件五大类,并进一步细化至20项具体因子,依次建立判断矩阵并进行一致性检验,分别完成层次单排序与总排序,系统量化各因素的相对权重。结果表明:在准则层中,内在动机影响最为显著,个人因素次之;在方案层中,学习能力、个人职业规划、花在高数上的时间、邻里效应、教考分离实施及考研、考公压力等因素权重较高,都对高等数学成绩具有关键影响。基于分析结果,结合教育学与心理学相关理论,本文从课程设计、教学互动、评价体系与学生自主学习等方面提出针对性改进建议,旨在推动高等数学教学从以“教”为主向以“学”为中心转型,为本校及情况类似院校提升教学质量与学生学习成效提供实证依据与实践参考。
Abstract: This study focuses on the factors influencing college students’ learning outcomes in advanced mathematics. Taking engineering and business management students from the 2022 cohort at West Yunnan University as the research subjects, data was collected through questionnaire surveys. The Analytic Hierarchy Process (AHP) was employed to construct a multi-level evaluation system. The study categorizes influencing factors into five major groups: personal, intrinsic motivation, class, school, and external conditions. These are further refined into 20 specific factors. Judgment matrices were sequentially established and consistency tests conducted, followed by hierarchical single-ranking and overall ranking to systematically quantify the relative weights of each factor. Results indicate: At the criterion level, intrinsic motivation exerts the most significant influence, followed by personal factors. At the scheme level, factors such as learning ability, personal career planning, time spent on advanced mathematics, peer influence, implementation of teaching-assessment separation, and pressure from graduate school or civil service examinations carry higher weights, all critically impacting advanced mathematics performance. Based on these findings and drawing from educational and psychological theories, this study proposes targeted improvement recommendations across curriculum design, teaching interaction, assessment systems, and student self-directed learning. These aim to advance the transformation of higher mathematics instruction from teacher-centered to learner-centered approaches, providing empirical evidence and practical guidance for enhancing teaching quality and student learning outcomes at this institution and similar universities.
文章引用:陈秀芳. 高等数学教学成效的困境分析与改进路径探析[J]. 统计学与应用, 2026, 15(1): 227-239. https://doi.org/10.12677/sa.2026.151022

参考文献

[1] 马梦萍, 蒲和平, 王涛, 等. 新工科背景下高等数学课程的“四位一体”教学改革与实践[J]. 高等数学研究, 2025, 28(5): 39-42.
[2] 许鹏飞, 公徐路, 张权义. 基于BOPPPS模式的高等数学混合式教学设计与实践[J]. 大学数学, 2025, 41(4): 114-119.
[3] 呼娜. 基于SPSS软件的学生的高等数学成绩分析[J]. 山东工业技术, 2016(23): 102.
[4] 杨淑辉, 孔朝莉. 高等数学成绩影响因素分析——以沈阳师范大学为例[J]. 大学数学, 2016, 32(5): 37-44.
[5] 吴国荣, 刘宇菲, 杨彩琴, 等. 高等数学学习成绩影响因素的调查分析——以内蒙古农业大学农科类本科二批录取学生为例[J]. 内蒙古农业大学学报(社会科学版), 2019, 21(1): 19-23.
[6] 潘兴侠, 郭琦茹, 林楠. 本科生高等数学成绩影响因素调查——基于Logistic回归模型的分析[J]. 大学数学, 2021, 37(4): 60-69.
[7] 吴艳萍, 郑维, 孙菲, 等. 大学生数学成绩影响因素的灰色关联分析[J]. 数学学习与研究, 2017(15): 4-5.
[8] 徐乃楠, 刘鹏飞. 数学文化热: 历史、意义与反思[J]. 自然辩证法通讯, 2020, 42(8): 102-106.
[9] 夏世娇, 吴仁芳. 数学理解的生成逻辑、价值透视与时代使命[J]. 课程·教材·教法, 2023, 43(12): 110-116.
[10] 连高社, 陈小彪. 基于层次分析法的大学生高等数学成绩影响因素分析[J]. 大学数学, 2021, 37(4): 70-78.
[11] 王军鹏, 张克中, 鲁元平. 近朱者赤: 邻里环境与学生学习成绩[J]. 经济学(季刊), 2020, 19(2): 521-544.
[12] 李若泰, 戴金雨, 陈朝东. 基于HPM视角下高等数学课程教学的价值意蕴、应然特征与提升策略[J]. 黑龙江高教研究, 2025, 43(11): 32-36.
[13] 顾燕, 曹海霞. 以拔尖创新人才培养为导向的《高等数学》和《普通物理》课程深度融合的教学改革初探[J]. 高等数学研究, 2025, 28(6): 79-82+87.