Surveying industry advisors to select data analytics topics for all business majors

被引:9
作者
Pan, Kevin [1 ]
Blankley, Alan, I [2 ]
Mazzei, Matthew J. [3 ]
Lohrke, Cynthia Frownfelter [2 ]
Marshall, Jennings B. [1 ]
Carson, Charles M. [3 ]
机构
[1] Samford Univ, Dept Econ Finance & Quantitat Anal, Birmingham, AL 35229 USA
[2] Samford Univ, Dept Accounting, Birmingham, AL 35229 USA
[3] Samford Univ, Dept Entrepreneurship Management & Mkt, Birmingham, AL 35229 USA
关键词
Data analytics; Business education; Undergraduate curriculum; Survey; Industry advisors; Employers' needs; EDUCATION; STUDENTS;
D O I
10.1016/j.ijme.2018.09.001
中图分类号
F [经济];
学科分类号
02 ;
摘要
In an effort to expand data analytics instruction, universities have launched data analytics majors and graduate programs in data analytics. While this effort meets the need for developing data analytics specialists, an equally important need is to improve the data competencies of undergraduate business students who do not major in analytics but still need to have competencies with analytics. However, business students not majoring in data analytics have limited credit hours available for data analytics. Therefore, it is necessary to select data analytics topics that meet employers' needs. We hypothesized that surveying industry advisors would help us revise the current curriculum to incorporate data analytics learning objectives that are both necessary and sufficient. The results showed that the most important data competencies are basic spreadsheet skills (86%), intermediate spreadsheet skills (82%), retrieving relevant data (86%), documenting data (92%), and presenting data (96%). The least important area is teaching software programming to non-analytics majors (14.5%). As a result of this study, we were able to develop a new curriculum to meet employer needs by revising previous courses without increasing required credit hours.
引用
收藏
页码:483 / 492
页数:10
相关论文
共 25 条
[1]  
Aasheim C., 2015, J. Inf. Syst. Educ, V26, P103
[2]  
Agresti A., 1992, STAT SCI, V7, P131, DOI [10.1214/ss/1177011454, DOI 10.1214/SS/1177011454]
[3]  
[Anonymous], 2017, Forbes
[4]  
Ashraf R, 2017, J EDUC BUS, V92, P179, DOI 10.1080/08832323.2017.1323720
[5]   Competency development in business graduates: An industry-driven approach for examining the alignment of undergraduate business education with industry requirements [J].
Azevedo, Ana ;
Apfelthaler, Gerhard ;
Hurst, Deborah .
INTERNATIONAL JOURNAL OF MANAGEMENT EDUCATION, 2012, 10 (01) :12-28
[6]   A Data Science Course for Undergraduates: Thinking With Data [J].
Baumer, Ben .
AMERICAN STATISTICIAN, 2015, 69 (04) :334-342
[7]  
Cardenas-Navia I., 2015, Change: The Magazine of Higher Learning, V47, P25
[8]  
Dichev C., 2016, P S COMP MIN I ADMI, V346
[9]   MULTIPLE COMPARISONS AMONG MEANS [J].
DUNN, OJ .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1961, 56 (293) :52-&
[10]  
Enget K., 2017, Journal of Accounting, V38, P9, DOI [DOI 10.1016/J.JACCEDU.2016.12.003, 10.1016/j.jaccedu.2016.12.003]