Toward a Holistic Approach to Data Literacy Education: A Framework and Implementation in a Data Science Course for Business Management Students
Year: 2026
Type: article
Abstract: The rapid pace of digital transformation has created a pressing need for data literacy. While its importance is widely recognized, there is no clear consensus on the specific skills required. Current Data Literacy Education (DLE) approaches in data science and machine learning courses often focus on digital skills such as data preparation and analysis, overlooking essential foundational skills like creativity, agility, and collaboration. Moreover, as DLE spans beyond traditional STEM boundaries, there is a growing need for inclusive approaches that engage non-STEM learners and address students' diverse needs, interests, and goals. In response, we propose a practical framework for DLE in data science and machine learning courses that cultivates both digital and foundational skills within an inclusive learning environment. Our approach prioritizes active learning and coaching, leveraging our web application STATY to bridge the gap between theory and practice by engaging students in real-world data problem-solving. We illustrate its application through the master's-level course “Business Data Science – From Data to Forecasts and Decisions”, along with our experiences and lessons learned.
Authors: Danijela Markovic, Oskar Kärcher
Institutions: Hochschule Osnabrück, d-fine (Germany)
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W7140123452