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大学数学公共基础课学习效果的统计分析方法与实践
Statistical Analysis Methods and Practice of Learning Effects of Common Mathematics Courses during College

DOI: 10.12677/CES.2023.114124, PP. 809-815

Keywords: 数学公共基础课程,相关分析,假设检验,聚类,灰色预测
Common Mathematcis Courses
, Correlation Analysis, Hypothesis Test, Cluster, Gray Forecast

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Abstract:

高等学校对大学数学公共基础课学情分析有助于理清教学对象的特征、督促教师改进数学公共基础课的教学方法,提升学生的学习效果。本文利用课程考核结果,使用相关分析、假设检验、聚类分析等方法挖掘数学公共基础课程成绩分布的统计特征。通过得出的统计结果,分析可能导致其分布特征的客观因素,为提升教与学的质量提供恰当的建议。利用灰色预测方法预判学生成绩趋势,提供教学过程的前置分析,为教学设计完善化给予支撑,从而进行差异化教学。该方法体系能够从宏观上进行学情分析,分析过程直观简洁、科学有效,可以滚动应用,可移植性强。
The analysis of the academic situation of public basic mathematics courses in colleges and universities is helpful to clarify the characteristics of teaching objects, urge teachers to improve the teaching methods of common mathematics courses, and improve students’ learning effects. This paper uses the results of course assessment to explore the statistical characteristics of the score distribution of public basic mathematics courses by correlation analysis, hypothesis test, and cluster analysis. Through the statistical results obtained, the objective factors that may lead to their distribution characteristics are analyzed, and appropriate recommendations are provided for improving the quality of teaching and learning. The gray prediction method is used to predict the trend of student performance, provide pre-analysis of the teaching process, and provide support for the improvement of teaching design, so as to carry out differentiated teaching. The method systems which have strong portability can analyze the academic situation on the macroscopic level, and the analysis process is intuitive, concise, scientific and effective, and can be applied to rolling analysis.

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