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Fri, Nov 7, 10:30 - 10:55, Pueblo A     Paper (refereed)
Recommended Citation: Jafar, M J, R Anderson, and A A Abdullat.  Data Mining Methods Course for Computer Information Systems Students.  In The Proceedings of the Information Systems Education Conference 2008, v 25 (Phoenix): §2313. ISSN: 1542-7382. (A later version appears in Information Systems Education Journal 6(48). ISSN: 1545-679X.)
 
Recipient of Distinguished Paper Award
 
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Data Mining Methods Course for Computer Information Systems Students

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Refereed10 pages
Musa J. Jafar    [a1] [a2]
CIS Department
West Texas A&M University    [u1] [u2]
Canyon, Texas, USA    [c1] [c2]

Russell Anderson    [a1] [a2]
CIS Department
West Texas A&M University    [u1] [u2]
Canyon, Texas, USA    [c1] [c2]

Amjad A. Abdullat    [a1] [a2]
CIS Department
West Texas A&M University    [u1] [u2]
Canyon, Texas, USA    [c1] [c2]

Although a Data Mining Methods course sequence is a late comer to the Information Systems curriculum, it is a natural fit in the discipline and students largely benefit from it. Students graduating with a BBA degree are well prepared for this area of specialization. They do understand business processes (approximately forty percent of their course work is in the business discipline and in quantitative analysis). Business knowledge coupled with knowledge of computing, and data management uniquely prepares those students for excellence in the discipline. In this paper, we present the implementation of a junior-senior level elective data mining methods course that we designed and offer as part of our BBA in Computer Information Systems. The course is business oriented. It emphasizes the conceptual understanding of data mining theory, practices and the current state of the underlying computing technology. We use off-the-shelf tools for the homework assignments and projects to perform the data mining tasks (cluster analysis, association analysis, decision tree analysis, na´ve Bayes, neural network, etc.). In this paper, we also present the supporting technologies and resources that we used for the course, along with lessons learned from teaching the course.

Keywords: Information Systems, Data Mining course, Business Intelligence, Data Modeling, Business Processes

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