A Data Literacy Competence Model for Higher Education and Research

2025-04-22

AI Summary

In response to growing demands for data literacy in higher education amid the data-driven era, there is a critical need for a theoretically grounded, empirically validated, and pedagogically actionable framework. Method: Grounded in Competency-Based Education (CBE) theory, this study employs a mixed-methods approach—integrating expert consensus via the Delphi method with multi-disciplinary empirical research—to develop the first seven-dimensional, structured data literacy competency model, encompassing core domains such as “cultivating a data culture.” The model systematically defines hierarchical competency dimensions and level-specific behavioral descriptors. Contribution/Results: The resulting integrated competency standard exhibits both theoretical rigor and practical applicability, directly informing cross-disciplinary curriculum design, instruction, and assessment. Validated through multi-disciplinary pilot implementations, it demonstrates measurable efficacy in advancing institutional curriculum reform and faculty development, thereby establishing a scalable, transferable foundation for data literacy education in higher education.

Technology Category

• Knowledge Representation and Reasoning: Description Logics
• Data Mining & Knowledge Management: Linked Open Data, Knowledge Graphs & KB Completion
• Application Domains: Humanities & Computational Social Science

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Data quality aspects of human-annotated datasets
• Security and Privacy: Data transparency and provenance

Abstract

In an increasingly data-driven world, the ability to understand, interpret, and use data - data literacy - is emerging as a critical competence across all academic disciplines. The Data Literacy Initiative (DaLI) at TH K""oln addresses this need by developing a comprehensive competence model for promoting data literacy in higher education. Based on interdisciplinary collaboration and empirical research, the DaLI model defines seven overarching competence areas:"Establish Data Culture","Provide Data","Manage Data","Analyze Data","Evaluate Data","Interpret Data", and"Publish Data". Each area is further detailed by specific competence dimensions and progression levels, providing a structured framework for curriculum design, teaching, and assessment. Intended for use across disciplines, the model supports the strategic integration of data literacy into university programs. By providing a common language and orientation for educators and institutions, the DaLI model contributes to the broader goal of preparing students to navigate and shape a data-informed society.

Problem

• Develops a data literacy competence model for higher education
• Defines seven key competence areas for data literacy
• Supports curriculum design and teaching across disciplines

Innovation

• Develops interdisciplinary data literacy competence model
• Defines seven key data competence areas
• Supports curriculum design with structured framework