性别和专业能否解释大学生商业统计成绩?

Q4 Business, Management and Accounting American Business Review Pub Date : 2022-11-16 DOI:10.37625/abr.25.2.253-269
Waros Ngamsiriudom, M. L. Devkota, Mohan K. Menon
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引用次数: 0

摘要

最近的讨论在教育、工业和政府关注干细胞领域的增长和多样化的需要。STEM教育和实践直接促进了一个国家的经济活力,并使其公民受益。然而,STEM教育和就业增长似乎在性别和多样性方面都是不平衡的。虽然研究人员已经研究了这一现象的各个方面,但本文试图通过分析性别和大学专业对统计相关课程的表现和态度的影响来增加知识基础。采用t检验、单因素方差分析和多元回归分析,探讨性别、专业和态度对商业统计课程成绩的影响。结果表明,在商业统计课程中,3个学期中有2个学期男女生的平均分没有显著差异。在市场研究课程中,采用了与商业统计课程中类似的统计概念,结果是相似的。然而,当考虑到学生的学术专业时,他们的分数就会有所不同。本研究的发现有助于发展有效和创新的统计学及相关学科的教学方法。
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Can Gender and Major Explain College Students’ Performance in Business Statistics?
Recent discussions in education, industry, and government have focused on the need for growth and diversity in STEM fields. STEM education and practice directly contribute to the economic vitality of a nation and benefit its citizens. Yet, STEM education and employment growth seem lopsided concerning both gender and diversity. While researchers have studied various dimensions of this phenomenon, this paper seeks to add to the knowledge base by analyzing the effects of gender and college major on performance and attitudes in statistics-related courses. T-tests, one-way analysis of variance, and multiple regression were used to investigate the effects of gender, major, and attitude on performance in business statistics courses. Results indicate that, in the business statistics course, there were no significant differences between the average score of male students and female students in 2 of 3 semesters. In the marketing research course, where similar statistical concepts as taught in the business statistics course were adopted, results were similar. However, there were differences in the students’ scores when their academic majors were considered. Findings from this study can contribute to developing effective and innovative pedagogical methodologies to teach statistics and related subjects.
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来源期刊
American Business Review
American Business Review Business, Management and Accounting-Business, Management and Accounting (miscellaneous)
CiteScore
1.00
自引率
0.00%
发文量
13
审稿时长
8 weeks
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