2025 ASEE Annual Conference & Exposition

Background:
In recent years, the data revolution has sparked widespread interest in Data Science (DS) across numerous fields and disciplines [1]. As society becomes more reliant on data-driven decisions, the demand for professionals equipped to handle data challenges is rising. The need for skilled workers in diverse roles and capacities continues to grow as these demands evolve [2,3]. To meet the demand for skilled workers, training in the latest data science technologies has become a priority in colleges across the US and China. These colleges have established comprehensive data science programs to ensure students graduate with the expertise required in the field [4]. The core courses in these data science programs are designed to address standard competencies established by the ACM [5]. However, how these core courses differ between colleges and across countries is an area worth exploring.

Goal:
The goal of this research paper is to identify knowledge and skills in the core curriculum in Data Science undergraduate degree programs at leading colleges in the U.S. and China. The comparison reveals key thematic trends.

Research Questions:
The research questions of this study are: 1) What are the knowledge and skills in the core curriculum of Data Science undergraduate degree programs in the U.S. and China? 2) What are the thematic trends in the core curriculum of Data Science undergraduate degree programs in the U.S. and China?

Method:
Dataset: a sample of data science undergraduate degree programs from leading colleges in the U.S. and China were chosen based on the U.S. News Ranking and Shanghai Consultancy Ranking.
Data analysis: The core curricula of each selected program were analyzed in terms of total credits, knowledge areas, and required skills, as outlined in the course descriptions. A comparative cluster analysis of the thematic topics revealed both commonalities and differences between the leading programs in the U.S. and China.

Findings and Conclusion:
The results indicated that undergraduate data science programs in both the U.S. and China share similarities in core knowledge areas, such as mathematics and statistics, data management, data science technologies, and programming skills. However, notable differences emerged between the two countries. Chinese programs place a stronger emphasis on both data management and data science technologies, whereas U.S. programs primarily focus on data science technologies, with less consistency in data management across their curricula.

Work Cited
[1] L. Cao, "Data science: a comprehensive overview," ACM Computing Surveys (CSUR), vol. 50, no. 3, pp. 1-42, 2017.
[2] F. Berman, R. Rutenbar, B. Hailpern, H. Christensen, S. Davidson, D. Estrin, M. Franklin, M. Martonosi, P. Raghavan, V. Stodden, and A. S. Szalay, "Realizing the potential of data science," Communications of the ACM, vol. 61, no. 4, pp. 67–72, 2018.
[3] J. S. Saltz and N. W. Grady, "The ambiguity of data science team roles and the need for a data science workforce framework," in IEEE International Conference on Big Data, 2017.
[4] I.-Y. Song and Y. Zhu, "Big data and data science: what should we teach?," Expert Systems, vol. 33, no. 4, pp. 364-373, 2016.
[5] E. Milonas, D. Li, and Q. Zhang, "Content analysis of two-year and four-year data science programs in the United States," presented at the 2021 ASEE Virtual Annual Conference, Virtual Conference, July 2021. [Online]. Available: https://peer.asee.org/36842.