Asee peer logo

Creating a Multi-College Interdisciplinary B.S. Data Science Program with Concentrations

Download Paper |


2021 ASEE Virtual Annual Conference Content Access


Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

Multidisciplinary Curriculum and Course Development

Tagged Division

Multidisciplinary Engineering

Tagged Topic


Page Count




Permanent URL

Download Count


Request a correction

Paper Authors


Karl D. Schubert FIET University of Arkansas Orcid 16x16

visit author page

Dr. Karl D. Schubert is a Professor of Practice and serves as the Associate Director for the Data Science Program for the University of Arkansas College of Engineering, the Sam M. Walton College of Business, and the J. William Fulbright College of Arts & Sciences.  His research interests include data science and analytics, innovation, technology, and interdisciplinary project-based active learning methodologies.  As part of his current role, Karl is leading a State-wide multi-college faculty and administration workgroup, with the Arkansas Center for Data Science as the Education & Workforce Development Research Theme for the NSF EPSCoR grant, to develop a consistent and collaborative interdisciplinary multi-college B.S. and Associate degree, and certificate program in Data Science, and leading a team developing a State-wide High School path for Data Science for the Arkansas Department of Education, and he is developing an interdisciplinary multi-college Innovation Curriculum.
Prior to his appointment at the University, in senior-level corporate roles that include CIO, CTO, Global SVP of Engineering, and General Manager, Karl has developed a steadfast reputation for driving strategic business growth and technology innovation.  He has strong experience in interdisciplinary data science, innovation and technology, and lifecycle management, operations, global business, through working in companies including IBM, Dell, Lifetouch, midrange companies and start-ups and his own company, TechNova Consulting, LLC. 
Dr. Schubert has authored two books and has been awarded patents for early work in storage systems architecture, storage area networks, data analysis methods, touch screen technologies, and other technology areas.  He is an elected member of the Arkansas Academy of Chemical Engineers, a 2008 recipient of the College of Engineering Distinguished Alumni Award, was elected a Fellow of the Institute of Engineering & Technology (IET) in 2015 and inducted as a charter member of the University of Arkansas Academy of Computer Science and Computer Engineering in 2017.  He established an endowed faculty award in Computer Science, an endowed undergraduate scholarship in Chemical Engineering and an endowed undergraduate scholarship to attract under-represented students to Engineering to help establish the College of Engineering’s Early Career Awareness Program (ECAP).

Dr. Schubert lives in Tontitown, AR, USA with his wife Kathryn, and son Tucker.

visit author page


Manuel D. Rossetti P.E. University of Arkansas

visit author page

MANUEL D. ROSSETTI is a Professor in the Industrial Engineering Department at the University of Arkansas. He received his Ph.D. in Industrial and Systems Engineering from The Ohio State University. His research and teaching interests are in the areas of simulation modeling, logistics optimization, and inventory analysis applied to manufacturing, distribution, and health-care systems. He serves as an Associate Editor for the International Journal of Modeling and Simulation and is active in IIE, INFORMS, and ASEE.

visit author page

Download Paper |


This paper describes the development of a multi-college interdisciplinary undergraduate program in data science that culminates in a bachelors of science degree. Data science programs across the nation have focused primarily on graduate degrees, either research based or professionally oriented. These programs build on the knowledge base of undergraduate degrees in order to provide skills, techniques, and domain knowledge within data science. Because of the evolving nature of data science and the tremendous interest by employers, there is a growing need for workforce development involving the skills of a data scientist, which is not being met by graduate programs. This paper presents the motivation, background, and need for undergraduate degrees in data science. In addition, we describe, in detail, a newly created interdisciplinary program that uniquely integrates business, arts and sciences, and engineering disciplines while meeting the needs of industry stakeholders. The development process, the curriculum, and the launch of the program are described. Lessons learned are summarized to assist other universities contemplating similar programs. Finally, we discuss our vision for the future of such programs.

Schubert, K. D., & Rossetti, M. D. (2021, July), Creating a Multi-College Interdisciplinary B.S. Data Science Program with Concentrations Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. 10.18260/1-2--36868

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2021 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015