Project Overview
Adapt-AI is exploring how generative AI can transform education through adaptive learning environments and innovative assessment formats. The project develops practical concepts, tools, and professional development opportunities to ensure that AI is used responsibly, in a personalized manner, and effectively in the classroom. In this way, Adapt-AI bridges the gap between research and school practice and empowers teachers to navigate learning in the AI era.
Adapt-AI’s goals include defining a theoretical framework, creating a model for AI-supported learning, compiling best practices, testing AI-supported teaching strategies, and launching a self-paced course for teachers. This ensures that AI is used ethically, effectively, and inclusively to promote adaptive and personalized education.
Over the course of the project, adaptive learning arrangements will be created and assessment methods will be tested. The goal is to develop an online self-study course that helps teachers expand their digital competencies in the field of generative AI. The project promotes the ethical and inclusive use of AI and improves differentiation and assessment methods in various educational settings.
For more information and to learn about our international team, please visit the project’s homepage.
Overview of Work Packages
Work Package 2 forms the conceptual foundation of the Adapt-AI project. The goal is to develop a scientifically sound and practice-oriented framework for the use of artificial intelligence in adaptive learning environments and assessment formats within Adapt-AI and beyond. To this end, key terms, subject-specific and interdisciplinary criteria, as well as pedagogical guiding principles for AI-supported instruction and performance assessment will be defined. Particular emphasis is placed on taking into account existing competency models, curricular requirements, and ethical and data protection guidelines. The Adapt-AI framework developed supports researchers and educators in using generative AI in a responsible, inclusive, and learning-promoting manner. The involvement of experts and international collaboration among project partners ensures that the results are practical, scientifically sound, and compatible across Europe.
Work Package 2 is led by the University of Siegen.
Work Package 3 is developing an interdisciplinary GenAI framework that supports adaptive learning and assessment processes for various subjects, grade levels, and language contexts. The focus is on developing a flexible prompting model that supports teachers and researchers in creating appropriate AI-supported learning resources, while taking into account pedagogical, ethical, and data protection requirements in accordance with the framework established in WP2. To this end, existing AI applications will first be systematically analyzed before the model is developed in collaboration with project partners and tested in real-world school settings. Feedback from experts, teachers, and students will be directly incorporated into the model’s revision and optimization. The results will form an important foundation for the project’s subsequent components (e.g., in WP4) and for sustainable use beyond the scope of the project.
Work Package 3 is led by the University of Ljubljana.
Work Package 4 builds on the foundations developed in WP2 (framework) and WP3 (flexible prompting model) and translates them into concrete, subject-specific learning and assessment arrangements. Here, AI-supported teaching and assessment formats are developed, tested, and further refined for subjects such as mathematics, STEM, English, German, physics, technology, and engineering. A particular focus is on creating learning materials that are differentiated, flexible, and ready for immediate use in the classroom. During pilot phases at participating schools, the materials are tested in collaboration with teachers to assess their effectiveness, clarity, and suitability for different learning needs. The most successful approaches are turned into best-practice examples that serve as ready-to-use resources for teachers. In this way, WP4 contributes to the concrete implementation of adaptive and inclusive learning processes using AI in everyday school life and ensures their long-term usability.
Work Package 4 is led by the University of Siegen.
Work Package 5 focuses on the professional development of teachers and, to this end, is developing a self-directed online learning program on the use of GenAI in the classroom, drawing on the results of the previous work packages. The goal is to equip teachers with the necessary knowledge and practical tools to implement AI-supported learning and assessment processes in a safe and pedagogically sound manner, while adhering to ethical and data protection standards. To this end, at least five modules, multimodal learning materials such as video tutorials and interactive exercises, and a pilot run with pre-service teachers and practicing teachers will be created and tested. Feedback from the pilot will be incorporated into the revision and quality improvement of the course. This will result in a scalable, sustainable continuing education format that strengthens teachers’ digital and pedagogical competencies over the long term. The work package thus directly contributes to embedding GenAI in everyday educational practice in a way that is not only technically sound but, above all, pedagogically meaningful.
Work Package 5 is led by the Carinthia University of Education.
Work Package 6 brings together the project’s dissemination and sustainability efforts and ensures that the results of Adapt-AI remain visible, usable, and available in the long term. To this end, a clear project identity with branding, a dissemination plan, and a sustainability plan will be developed to ensure that all materials are communicated consistently and disseminated through appropriate channels. In addition, WP6 will organize multiplier and policy events that engage teachers, decision-makers, and institutions to embed the project results in educational structures. Another focus is on ensuring the long-term preservation of the materials, for example, by integrating them into platforms such as EPALE and into teacher training programs, as well as by establishing a sustainability network. In this way, WP6 ensures that the project results continue to be used and disseminated in practice even after the project ends. Overall, this work package lays the groundwork for Adapt-AI to have an impact beyond the scope and duration of the project.
Work Package 6 is led by the Carinthia University of Education.
