Business Analytics Competition (BAC@MC): A learning experience

IF 0.8 Q3 EDUCATION & EDUCATIONAL RESEARCH
Salwa Ammar, Min Jung Kim, Amir H. Masoumi, Alin Tomoiaga
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引用次数: 0

Abstract

Over the past few years, academics have undertaken initiatives to bridge the gap between theory and practice in the ever-growing field of business analytics, including implementing real-life student projects in all shapes and forms. Every year since 2015, Manhattan College has invited student teams from across North America and elsewhere in the world to its campus in order to participate in an intercollegiate business analytics competition (BAC@MC). This well-received event and the objectives behind it are described in this article. The program is shown to serve as an effective experiential learning adventure for the undergraduate students as it hones their data analytic skills in the context of an engaging real-world business problem. The roles various stakeholders play in this high-impact practice are highlighted. Furthermore, an example of a recent competition question is presented (along with a summary of the analytical approaches attempted) by the student teams. Descriptive visualizations, regression, and cluster algorithms implemented using python, R, Excel, or Tableau are among the typical analyses utilized by participating students. As witnessed by the students, faculty advisors, and the industry practitioners who attended the event, competitions such as BAC@MC can be rewarding, community-building, and transformative experiences for undergraduate students who will soon become tomorrow's business analysts.

商业分析竞赛(BAC@MC):学习经历
在过去的几年里,学者们已经采取措施,在不断发展的商业分析领域弥合理论与实践之间的差距,包括实施各种形式的现实生活中的学生项目。自2015年以来,曼哈顿学院每年都会邀请来自北美和世界其他地方的学生团队到校园参加校际商业分析竞赛(BAC@MC)。本文将描述这个广受欢迎的事件及其背后的目标。该计划被证明是为本科生提供有效的体验式学习冒险,因为它在一个引人入胜的现实世界商业问题的背景下磨练他们的数据分析技能。强调了各种利益相关者在这种高影响实践中发挥的作用。此外,学生团队还提供了一个最近竞赛问题的例子(以及对所尝试的分析方法的总结)。使用python、R、Excel或Tableau实现的描述性可视化、回归和聚类算法是参与学生使用的典型分析方法。正如参加此次活动的学生、教师顾问和行业从业者所见证的那样,BAC@MC等比赛对即将成为未来商业分析师的本科生来说是有益的、社区建设和变革的经历。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Decision Sciences-Journal of Innovative Education
Decision Sciences-Journal of Innovative Education EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
3.60
自引率
36.80%
发文量
25
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