bridgingAI
The project “bridgingAI: Building Brigdes to AI Across Disciplines” seeks to provide students with relevant AI competencies, regardless of the discipline studied. RWTH is thus tackling a challenge currently faced by many universities and numerous study programs.
Drawing on the University’s AI expertise, the goal is to develop scalable solutions that can be made available to other higher education institutions in the form of Open Educational Resources (OER).
The aim of bridgingAI is to provide students with the necessary skills to use, assess, and develop artificial intelligence applications, enabling them to contribute to shaping science, industry and society in the age of artificial intelligence. It is one of the strategic goals of RWTH as an interdisciplinary, integrated university of technology to develop and maintain interdisciplinary AI competencies. Specifically, a bridging course for Bachelor’s graduates who want to take up a master’s program shall be developed and made available to a broad range of disciplines.
This so-called Micro Bachelor’s program seeks to be attractive for as large a number of students as possible. To achieve this, representatives from several RWTH faculties will contribute to the program. Initially, it will consist of ten MOOCs – massive open online courses – and made available through the edX platform.
Program development is coordinated by the RWTH Center for Artificial Intelligence headed by Professor Bastian Leibe. RWTH professors Holger Rauhut, Erhard Cramer, Saskia Nagel, Wil van der Aalst, Sebastian Trimpe, and Ulrik Schroeder as well as Dr. Malte Persike will be closely involved in developing the course offerings.
Our share
As a member of the RWTH AI Center, we are participating in the project with our expertise in didactics and learning technology. On the one hand, we develop the learning module for the introduction to programming for AI applications (CodingAI), on the other hand, we advise the overall instructional and technological design. For the evaluation of the project, we develop learning analytics tools and integrate them into the RWTHanalytics infrastructure in cooperation with CLS.
Our project team
Prof. Dr. Ulrik Schroeder (Project lead)
N. N.
Projektpartnerinnen und Projektpartner
Prof. Dr. Bastian Leibe, Computer Vision Group (General project lead)
Prof. Dr. Holger Rauhut, Chair for Mathematics of Information Processing
Prof. Dr. Erhard Cramer, Chair for Applied Stochastics
Prof. Dr. Saskia Nagel, Research Group Applied Ethics
Prof. Dr. Wil van der Aalst, Chair for Process and Data Science
Prof. Dr. Sebastian Trimpe, Institute for Data Science in Mechanical Engineering
PD Dr. Malte Persike, Center für Lehr- und Lernservices