Bridging Theory and Practice: Building an Inclusive Undergraduate Data-Science Program
- Conference
- Location
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Portland, Oregon
- Publication Date
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June 23, 2024
- Start Date
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June 23, 2024
- End Date
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July 12, 2024
- Conference Session
- Tagged Topics
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Diversity and Data Science & Analytics Constituent Committee (DSA)
- Permanent URL
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https://strategy.asee.org/48419
Paper Authors
Mehmet Ergezer Wentworth Institute of Technology
Mehmet Ergezer holds a Doctor of Engineering degree from the Department of Electrical and Computer Engineering at Cleveland State University, Cleveland, OH. Currently serving as an Associate Professor of Computing and Data Science at Wentworth Institute of Technology in Boston, MA, Dr. Ergezer's expertise lies at the intersection of embedded systems and computational intelligence. He has co-authored publications on artificial intelligence and computer science education and holds consumer electronics patents in the USA and Europe.
Beyond his technical pursuits, Dr. Ergezer is deeply committed to fostering intercultural competence among undergraduate students. He has spearheaded initiatives to broaden participation in artificial intelligence, including co-founding and co-chairing the AAAI Undergraduate Consortium. Additionally, he has led transformative study abroad programs, such as a semester-long immersion experience in Berlin, Germany, providing students with invaluable global perspectives.
Mark Mixer Wentworth Institute of Technology
Mark Mixer is an associate professor in the School of Computing and Data Science at Wentworth Institute of Technology. After completing a B.A. from Dartmouth College, he received his M.S. and Ph.D in Mathematics from Northeastern University. His research is in the fields of group theory, graph theory, combinatorics, and discrete geometry.
Weijie Pang
Wentworth Institute of Technology
orcid.org/0000-0002-7666-8248
Weijie Pang is an tenure-track assistant professor in School of Computing and Data Science at Wentworth Institute of Technology. After received B.S. and M.S. from Beijing University of Technology and Ph.D. from Worcester Polytechnic Institute, Dr. Pang finished the Post-doc program in Department of Mathematics and Statistics at McMaster University. Her research area is data science, financial mathematics, pandemic modeling and stochastic analysis.
Abstract
As the field of data science continues to evolve, institutions of higher education face the challenge of developing curricula that prepare students for the industry's rapidly changing landscape. In this paper, we will present a case study of the development and implementation of the undergraduate Bachelor of Science in Data Science (BSDS) program at a teaching-focused university. This new degree was developed by an interdisciplinary committee, including faculty members from computer science, humanities, management, mathematics, and sciences to underscore the importance of collaborative expertise in the field of Data Science. We will discuss the curricular development as well as our efforts required to successfully launch the new program. We will provide insights into the decision-making process for aligning the program with dynamic industry requirements.
A focus point for this program lies in fostering diversity and inclusivity, with a keen aim to amplify the presence of underrepresented and marginalized groups in computing, data analysis, and artificial intelligence. Our data science program offers a pathway for community college graduates to complete the program in a short time window. In particular, we offer a ``2+2'' option for students, where 2-year associate degrees from various local community colleges transfer effectively, only leaving 2 years left for completion of the BSDS degree for the students at our university. This initiative is not just about accessibility but is a deliberate strategy to welcome individuals from diverse educational backgrounds, thereby enriching the learning environment with a multiplicity of perspectives. Additionally, we focus on diversity and inclusion at the course design level, implementing pedagogical tools with this ideal in mind. These tools are tailored to create an environment that respects and values diversity, ensuring that our educational offerings are not only academically rigorous but also considerate of the varied experiences and perspectives that each student brings to the table. Through this holistic approach, we aim to cultivate a learning community where every individual, irrespective of their background, feels seen, heard, and empowered to contribute meaningfully to the field of data science. In this paper, we will present the challenges and triumphs encountered during the program's launch, shedding light on proactive measures addressing potential barriers to entry and participation. Our work can be of value to others who are interested in designing a program that combines theoretical depth in both mathematics and computer science with practical applicability along with a focus on diversity and inclusivity.
Ergezer, M., & Mixer, M., & Pang, W. (2024, June), Bridging Theory and Practice: Building an Inclusive Undergraduate Data-Science Program Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://strategy.asee.org/48419
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