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Application of Canonical Correlation Analysis to study the influence of mathematics on engineering programs: A case study

机译:典型相关分析在研究数学对工程程序影响中的应用:案例研究

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Mathematical knowledge is essential to improve the analytical thinking of engineering undergraduates. Exploring more information from existing academic data is an essential aspect of the educational research. The objective of this study is to explore the impact of mathematics performance on different engineering programs. The study was conducted with 626 engineering students from seven different disciplines at the Faculty of Engineering, University of Moratuwa, Sri Lanka. Canonical Correlation Analysis (CCA) was employed to investigate the relationship between mathematics courses and other engineering courses with respect to their disciplines. Results of CCA revealed that the mathematics performance in both semester 1 and 2 influences significantly on the students' academic performance in Level 2 of the seven engineering disciplines considered. Wilk's lambda test statistic confirmed that only the first canonical variate pair is significant for all disciplines. The squared canonical correlations of first canonical variate pair indicated that the amount of variance between the mathematics performance and academic performance in Level 2 explained varied among seven disciplines from 42% to 68%. The impact is higher from mathematics in semester 2 than that from semester 1 in all disciplines except for Material Science and Engineering discipline. The explainable variability of student academic performance in Level 2 by the canonical variate of mathematics is varied from 27% to 50% among seven disciplines. Based on preliminary analysis, it can be concluded that the performance in mathematics in Level 1 could indicate the trend towards the student academic performance in all engineering programs.
机译:数学知识对于改善工科学生的分析思维至关重要。从现有的学术数据中探索更多信息是教育研究的重要方面。这项研究的目的是探讨数学性能对不同工程程序的影响。这项研究是与来自斯里兰卡莫拉图瓦大学工程学院的来自七个不同学科的626名工程专业学生进行的。典型相关分析(CCA)用于研究数学课程与其他工程课程之间的关系。 CCA的结果表明,第一学期和第二学期的数学成绩对所考虑的七个工程学科的第二级学生的学业成绩有显着影响。 Wilk的lambda检验统计数据证实,只有第一个规范变量对对所有学科都有意义。第一个规范变量对的规范相关系数的平方表明,在7级学科中,解释的2级数学成绩与学业成绩之间的差异程度从42%变为68%。除了材料科学和工程学科以外,所有学科的数学影响都比第二学期的数学影响大。在7门学科中,数学的正则变量可以解释第二级学生学习成绩的可解释性差异,从27%到50%不等。根据初步分析,可以得出结论,第1级的数学成绩可以表明在所有工程课程中学生学习成绩的趋势。

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