Data Science is a relatively new academic field still developing its identity. The discipline initially grew rapidly at the graduate level, driven by strong industry demand beginning around 2012, but it has recently expanded to undergraduate programs. Between 2020 and 2022, the number of bachelor’s degrees in Data Science increased dramatically, reflecting both the field’s maturation and the growing recognition of data literacy as essential in the modern workforce. As Data Science becomes a standard part of undergraduate education, it has the chance to adopt proven methods from other established STEM fields. However, many programs have moved too quickly to meet demand, particularly for machine learning courses, without incorporating key educational best practices. A central principle that is often overlooked is the scientific method, which emphasizes testing assumptions, evaluating evidence, and adapting conclusions based on data. When this approach is not integrated into machine learning and related courses, students may miss out on opportunities to build essential critical thinking and problem-solving skills. This omission risks producing graduates who can use technical tools but lack the ability to plan, evaluate, and reason effectively about complex, real-world data problems. Embedding experimental reasoning and reflective practice into Data Science curricula would not only strengthen student learning but also ensure that the discipline develops with the rigor and intellectual foundations that define mature scientific fields. This presentation will discuss a paper written on this subject.

Authors:
Brian Wright, University of Virginia, United States

About the Presenter(s)
Dr. Brian Wright, Quantitative Foundation Associate Professor and Director of Undergraduate Programs, School of Data Science UVA. I'm interested in the intersection of technology (AI) and education. Focusing on self regulated learning and LLMs.

Connect on Linkedin
https://www.linkedin.com/in/brian-wright-ph-d-90063027/

See this presentation on the full schedule – Wednesday Schedule

Bookmark