消除方差分析手工计算预测本科统计学课程掌握能力的提高

Pub Date : 2023-06-27 DOI:10.1177/00986283231183959
Angela G. Pirlott, Jarrod C. Hines
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引用次数: 0

摘要

据推测,大多数统计学专业人员使用软件程序进行统计分析,但统计学教科书和课程通常教授手工计算。这项研究考察了在本科生心理学统计学课程中,手工计算是否与学生的概念和应用方差分析(ANOVA)素养有关。准实验性地,我们使用单元测验和SPSS数据分析实验室,在包括手工计算和不包括手工计算的部分之间,比较了95名学生对受试者之间和受试者内部一个因素方差分析的掌握情况。控制GPA、性别、种族、专业、年龄和数学准备,以抵消非随机分配到章节的影响,消除ANOVA手工计算,可以预测在测验中更好的表现8%,在SPSS实验室中更好的成绩6%。将教学重点从手工计算转移开,可以提高学生对单因素方差分析的概念和实践理解。考虑到时间限制,教师可能会放弃教授方差分析手工计算,而专注于概念信息和软件应用。
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Eliminating ANOVA Hand Calculations Predicts Improved Mastery in an Undergraduate Statistics Course
Presumably, most statistics professionals use a software program to perform statistical analyses, yet statistics textbooks and classes commonly teach hand calculations. This study examined whether, in an undergraduate psychology statistics course, hand calculations related to students' conceptual and applied analysis of variance (ANOVA) literacy. Quasi-experimentally, we compared 95 students’ mastery of one-factor between- and within-subjects ANOVAs, using the unit quiz and SPSS data analytics lab, between sections which did and did not include hand calculations. Controlling for GPA, gender, ethnicity, major, age, and math preparation to offset nonrandom assignment to section, eliminating ANOVA hand calculations predicted better performance on the quiz by 8% and on the SPSS lab by 6%. Shifting instructional focus away from hand calculations could enhance students’ conceptual and practical understanding of one-factor ANOVAs. Given time limitations, instructors might forgo teaching ANOVA hand calculations and focus on conceptual information and software applications.
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