Content area

Abstract

Career choices are shaped by students’ experiences, knowledge, and skill sets across time, reflecting not only disciplinary interests but also exposure to evolving fields such as data science (DSC). Despite a surge in interest and enrollment in data science degrees, the United States faces a growing demand for data literacy across multiple sectors. Online learning environments have become entry points for students’ initial engagement with DSC, offering accessibility and supporting workforce needs. Nevertheless, the interdisciplinary essence of DSC means that clear career paths remain ambiguous, especially for those applying DSC knowledge within various disciplines. While national data sources provide valuable overviews of degree distributions, more granular analysis at the course level is warranted to understand nuanced student trajectories. Project-based online learning, though proven valuable in in-person settings, remains underexplored in online DSC education. This study employs curriculum analytics and Sankey diagram visualizations to investigate course enrollment patterns and career trajectories among students after enrolling in an introductory online project-based DSC course. We built a longitudinal dataset by following 35 students between Fall 2022 and Spring 2024, tracking their subsequent course enrollments over time. Demographic and academic data were sourced from institutional enrollment records, allowing subgroup analysis based on major, gender, race, first-generation status, and achievement. Our exploratory analysis reveals patterns indicating that continued DSC course enrollment appears prevalent among nonwhite, male, STEM-major, and academically proficient students, whereas first-generation students exhibit no persistence. We illustrate how Sankey diagrams, though not establishing causality, provide actionable insights for program and curriculum development in DSC education.

Details

1009240
Business indexing term
Title
Online project-based learning to foster students’ course choices in data science: a longitudinal case study using Sankey visualization
Author
Castellanos-Reyes, Daniela 1   VIAFID ORCID Logo  ; Leppard, Tom R. 2   VIAFID ORCID Logo 

 North Carolina State University, Teacher Education and Learning Sciences Department, College of Education, Raleigh, USA (GRID:grid.40803.3f) (ISNI:0000 0001 2173 6074) 
 North Carolina State University, Data Science and Artificial Intelligence Academy, Raleigh, USA (GRID:grid.40803.3f) (ISNI:0000 0001 2173 6074) 
Volume
22
Issue
1
Pages
63
Publication year
2025
Publication date
Dec 2025
Publisher
Springer Nature B.V.
Place of publication
Heidelberg
Country of publication
Netherlands
e-ISSN
23659440
Source type
Scholarly Journal
Language of publication
English
Document type
Case Study, Journal Article
Publication history
 
 
Online publication date
2025-10-20
Milestone dates
2025-09-10 (Registration); 2025-05-09 (Received); 2025-09-09 (Accepted)
Publication history
 
 
   First posting date
20 Oct 2025
ProQuest document ID
3262930515
Document URL
https://www.proquest.com/scholarly-journals/online-project-based-learning-foster-students/docview/3262930515/se-2?accountid=208611
Copyright
© The Author(s) 2025. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2025-11-14
Database
2 databases
  • Education Research Index
  • ProQuest One Academic