2025 ASEE Annual Conference & Exposition

Reinforcing curricular interventions in data science through an experiential learning internship program (NSF IUSE [GRANT NUMBER])

Presented at NSF Grantees Poster Session I

Experiential learning fosters engagement, deepens understanding, and enhances practical problem-solving skills in STEM education (Beier, 2019; Kolb, 1984; NAE, 2005). The [PROJECT] at [INSTITUTION] creates data science learning opportunities for undergraduates with diverse academic backgrounds and exposes them to the practical applications of data science within interdisciplinary contexts. Unlike traditional data science academic programs for students already interested in the field, [PROJECT] seeks to train a future workforce where data science skills are needed as a core attribute of most career paths. Two interventions created for students include 1) data science modules developed for and deployed in introductory STEM and social science courses, and 2) experiential learning opportunities in data science through internal and external internships that allow students to apply data science concepts to real-world projects.

This paper focuses on the latter component of the project. We use a qualitative case study approach to explore the personal and professional growth of four students—each serving in distinct roles during their internship. Through our analysis, we identify key themes related to personal and academic growth. Key findings include the significant enhancement of the interns’ abilities in teamwork, organizational skills, and leadership, as well as a marked increase in confidence in data analytics and data visualization. For example, interns who initially had moderate confidence in data-related work reported substantial improvement by the program's end, with their career goals in data science becoming clearer. Interns also highlight the program's effectiveness in providing networking opportunities and a sense of community, which were instrumental in shaping their professional development.

The program’s approach to integrating data science into broader fields demonstrates its potential as a model for interdisciplinary education. Experiential learning opportunities bridge the gap between theoretical knowledge and practical application. The research highlights the importance of such initiatives in fostering comprehensive skill development and confidence in STEM students and equips students—regardless of their primary discipline— with the skills needed for the modern workforce. This research is supported by the NSF IUSE program under [GRANT NUMBER].

References

Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice Hall.

National Academy of Engineering. (2005). Educating the Engineer of 2020: Adapting Engineering Education to the New Century. Washington, DC: The National Academies Press. https://doi.org/10.17226/11338.

Beier M.E., Kim M.H., Saterbak A., Leautaud V., Bishnoi S., & Gilberto J.M. (2019). The effect of authentic project-based learning on attitudes and career aspirations in STEM. Journal of Research in Science Teaching. 56 (1), 3–23. https://doi.org/10.1002/tea.21465

Authors

Prof. Petra Bonfert-Taylor http://orcid.org/0009-0001-0869-5439 Dartmouth College [biography]

Petra Bonfert-Taylor received her Ph.D. in Mathematics from Technical University of Berlin (Germany), was a postdoctoral fellow at the University of Michigan and a faculty member in the Mathematics Department at Wesleyan University before accepting her current faculty position at the Thayer School of Engineering at Dartmouth. She was elected a Fellow of the Association for Women in Mathematics in the Class of 2020. Her mathematics research is in geometric function theory and discrete groups; she also has a strong interest in broadening access to high-quality higher education and pedagogical innovations that aid in providing equal opportunities to students from all backgrounds. This passion led her to design and create a seven-MOOC Professional Certificate on C-programming for edX for which her team won the “2019 edX Prize for Exceptional Contributions in Online Teaching and Learning”. Previously she designed a MOOC “Analysis of a Complex Kind” on Coursera. Petra is the recipient of the New Hampshire High Tech Council 2018 Tech Teacher of the Year Award, the Binswanger Prize for Excellence in Teaching at Wesleyan University and the Excellence in Teaching Award at Thayer. She recently co-designed and piloted a Foreign Studies Program focussed on green and sustainable engineering in collaboration with the German department at Dartmouth. At Thayer she furthermore leads an AAU funded Teaching Evaluation Project to develop, implement, and document a more effective and holistic teaching evaluation system.

Petra has served as Associate Dean for Diversity and Inclusion at Thayer since 2020. In this role she plans, leads and oversees diversity and inclusion efforts at Thayer and in coordination with other organizations internal and external to Dartmouth. Thayer was recently recognized with the ASEE Silver Diversity Award for our progress in increasing diversity and inclusion of our program.
Dr. Laura E. Ray Dartmouth College [biography]

Dr. Ray is a professor of engineering sciences at the Thayer School of Engineering, Dartmouth College. She received her B.E. and Ph.D. degrees from Princeton Univ. and her M.S. degree from Stanford University. She is a co-founder of two companies. Her re
Scott Pauls Dartmouth College

Note

The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025

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