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Presentation
Teaching the Foundations of Data Science: An Interdisciplinary Approach
ISSCM Faculty Publications
  • Daniel Asamoah, Wright State University - Main Campus
  • Derek Doran, Wright State University - Main Campus
  • Shu Z. Schiller, Wright State University - Main Campus
Document Type
Conference Proceeding
Publication Date
12-1-2015
Abstract
The astronomical growth of data has necessitated the need for educating well-qualified data scientists to derive deep insights from large and complex data sets generated by organizations. In this paper, we present our interdisciplinary approach and experiences in teaching a Data Science course, the first of its kind offered at the Wright State University. Two faculty members from the Management Information Systems (MIS) and Computer Science (CS) departments designed and co-taught the course with perspectives from their previous research and teaching experiences. Students in the class had mix backgrounds with mainly MIS and CS majors. Students' learning outcomes and post course survey responses suggested that the course delivered a broad overview of data science as desired, and that students worked synergistically with those of different majors in collaborative lab assignments and in a semester long project. The interdisciplinary pedagogy helped build collaboration and create satisfaction among learners.
Comments

Presented at the Special Interest Group on Decision and Support Analytics (SIGDSA) Business Analytics Congress, Ft. Worth, TX, December 12-13, 2015.

Citation Information
Daniel Asamoah, Derek Doran and Shu Z. Schiller. "Teaching the Foundations of Data Science: An Interdisciplinary Approach" (2015)
Available at: http://works.bepress.com/derek_doran/46/