2024 ASEE Annual Conference & Exposition

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.