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Business Intelligence and Big Data in Higher Education: Status of a Multi-Year Model Curriculum Development Effort for Business School Undergraduates, MS Graduates, and MBAs

机译:高等教育中的商业智能和大数据:针对商学院本科生,硕士毕业生和MBA的多年模式课程开发工作的现状

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Business intelligence (BI), “big data”, and analytics solutions are being deployed in an increasing number of organizations, yet recent predictions point to severe shortages in the number of graduates prepared to work in the area. New model curriculum is needed that can properly introduce BI and analytics topics into existing curriculum. That curriculum needs to incorporate current big data developments even as new dedicated analytics programs are becoming more prominent throughout the world. This paper contributes to the BI field by providing the first BI model curriculum guidelines. It focuses on adding appropriate elective courses to existing curriculum in order to foster the development of BI skills, knowledge, and experience for undergraduate majors, master of science in business information systems degree students, and MBAs. New curricula must achieve a delicate balance between a topic’s level of coverage that is appropriate to students’ level of expertise and background, and it must reflect industry workforce needs. Our approach to model curriculum development for business intelligence courses follows the structure of Krathwohl’s (2002) revised taxonomy, and we incorporated multi-level feedback from faculty and industry experts. Overall, this was a long-term effort that resulted in model curriculum guidelines.
机译:商业智能(BI),“大数据”和分析解决方案正在越来越多的组织中部署,但最近的预测表明,准备在该地区工作的毕业生人数严重短缺。需要新的模型课程,可以将BI和分析主题适当地引入现有课程中。即使新的专用分析程序在世界范围内变得越来越重要,该课程也需要纳入当前的大数据发展。本文通过提供第一个BI模型课程指南为BI领域做出了贡献。它侧重于在现有课程中添加适当的选修课程,以促进商务智能,商务信息系统学位的学生以及MBA学生的BI技能,知识和经验的发展。新课程必须在与学生的专业水平和背景相适应的主题覆盖范围之间达到微妙的平衡,并且必须反映行业劳动力的需求。我们为商业智能课程开发课程模型的方法遵循Krathwohl(2002)修订的分类法的结构,并且我们结合了教师和行业专家的多级反馈。总体而言,这是一项长期的工作,从而产生了示范课程指南。

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