研究生《数理统计》课程学习体验的群体差异性分析——以河北工程大学为例

Group Differences in Learning Experience of Graduate “Mathematical Statistic” Course—A Case Study of Hebei University of Engineering

摘要: 随着数理统计方法在日常生活的应用面逐渐扩大，广泛的应用使得《数理统计》成为高等院校的必备课程之一。本研究通过问卷调查获得数据，从学生的性别、年级、专业背景、学习史、兴趣以及对课程开设的态度这六个因素出发，探究造成不同学生群体产生学习体验差异的因素。首先通过卡方检验确定出性别、年级、专业这三个因素对学生学习数理统计课程是否感到困难存在显著性影响；接着利用K-Means聚类对调研的群体进行类别划分，最终将学生群体划分为三类：类别0：“学习不困难者”、类别1：“基础薄弱，困难较多”、类别2：“基础较好，重难点章节薄弱”；最后采用CRITIC权重法对这三类群体进行分析，确定出“专业”是影响学习困难程度的重要因素，尤其是在类别1的学生中影响最大。其次是“年级”和“对课程的态度”。最后依据研究结论提出改进建议与措施。

Abstract: With the increasing application of mathematical statistics methods in daily life, the widespread use has made “Mathematical Statistics” an essential course in higher education institutions. This study collects data through questionnaires, focusing on six factors: students’ gender, grade level, academic background, learning history, interest, and attitude toward the course offering, to explore the factors contributing to differences in learning experiences among different student groups. First, chi-square tests were used to identify that gender, grade level, and academic background significantly influence whether students find the mathematical statistics course difficult. Then, K-Means clustering was applied to categorize the surveyed students into three groups: Category 0: “Students with no learning difficulties”; Category 1: “Students with weak foundations and significant difficulties”; Category 2: “Students with solid foundations but weaknesses in key challenging chapters”. Next, the CRITIC weighting method was employed to analyze these three groups, revealing that “academic background” is the most critical factor affecting learning difficulty, particularly for students in Category 1, followed by “grade level” and “attitude toward the course”. Finally, based on the research findings, improvement suggestions and measures are proposed.