DZdA: German Center for Digital Tasks in Higher Education Teaching

Funding: Stiftung Innovation in der Hochschullehre
Total funding: €11.9 million
Project duration: 1 October 2025 to 1 October 2031, subject to a successful interim evaluation

The German Center for Digital Tasks in Higher Education Teaching (DZdA) is a nationwide initiative for the sustainable development, provision, and maintenance of quality-assured, multilingual digital exercises and examination tasks. Its objective is to establish a permanent infrastructure through which universities across Germany can access and use advanced digital tasks based on technologies such as STACK, JSXGraph, and Moodle.

The DZdA will provide educators with on-demand support for creating and adapting digital tasks. A central repository will make didactically reviewed, multilingual, and systematically categorised tasks available for STEM and business-related subjects. These services will be complemented by training programmes, pedagogical guidance, and specialised centres for task development, didactics, AI innovation, knowledge transfer, and student support. In the long term, the DZdA aims to establish a sustainable infrastructure for digital teaching that can continue independently of project funding.

Within the project, our UniBw AIML group is responsible for the Center for AI and Innovation. We develop AI-supported methods and tools for generating and evaluating digital tasks, providing context-aware recommendations, and offering personalised hints and explanations to students. A particular focus is the development of intelligent tutoring chatbots that support both instructors and students throughout the teaching and learning process.

Our group will also provide the DZdA partners with adaptable AI solutions tailored to their specific requirements. These solutions will support activities such as digital task creation, automated and formative feedback, individual learning guidance, and the integration of AI-based assistance into existing higher-education platforms. Through this work, we aim to contribute scalable and pedagogically meaningful AI technologies that improve the quality, accessibility, and personalisation of digital higher education.