Data Literacy



Laura Platte

Acting Project Manager




Interdisciplinary Data Literacy Education at RWTH – University-Wide – Digital

The data.RWTH project funded by the Digital University of North Rhine Westphalia and the Stifterverband aims to teach students data literacy on a broad scale. To this end, we develop courses that teach various aspects of data literacy.


Structure and Certificates

*** Video zur Projektvorstellung ***
data.RWTH - Data culture at RWTH Aachen University

Learning and applying data literacy – data.RWTH teaches future skills

The skills to appropriately and critically collect and evaluate, manage, analyze, and interpret data are key prerequisites for actively shaping the data-driven society 4.0. Within the framework of the data.RWTH project, competencies required for this are taught in an application-oriented and interdisciplinary manner and are systematically integrated into the curricula. Together with the data.RWTH project team, teachers and other stakeholders are working on the creation and implementation of a modular and multi-perspective teaching and learning program that forms both a common and subject-specific competence set among students.

In online courses, students learn how to proficiently handle data in a variety of processing and deployment contexts: from data collection to the use of appropriate strategies and tools for management, analysis, and visualization to data-based decision making. That way, students of today learn to understand the data of tomorrow!


Goals of the Project

  1. Learning – Students digitally acquire both basic and specialized data competencies as important future skills with the use of different methods and tools.
  2. Teaching – Teachers actively shape the conception, implementation, and curricular integration of new data literacy modules at RWTH Aachen University with subject-specific expertise.
  3. Applying – Using case studies and real-world data sets as well as software, students learn to apply acquired data skills in a practice-oriented manner.
  4. Networking – Experiences, teaching approaches, and materials are shared in the federal data literacy education network – so all network partners benefit from mutual exchange

Aspects of the Project

  • Gathering data literacy requirements and competencies in exchange with external stakeholders, students, and faculty
  • Conception of contents and methods of interdisciplinary modules
  • Developing and producing videos and other materials
  • Curricular embedding of the courses in all faculties
  • Promoting a university-wide implementation and certification of course modules
  • Providing courses as Moodle and edX courses in German and English
  • Continuous quality management and assurance
  • Developing an evaluation concept
  • Participating in the Data Literacy Education Network
  • Networking with partners from business, science, and industry