ZAKKI - Zentrale Anlaufstelle für innovatives Lehren und Lernen interdisziplinärer Kompetenzen der KI

ZAKKI aimed to equip lecturers and staff at Magdeburg-Stendal University of Applied Sciences with comprehensive competencies in the field of artificial intelligence and to develop corresponding study and professional development programs. Within subject-specific and interdisciplinary teaching and learning labs, formats were designed that addressed the technical, economic, ethical, and societal dimensions of AI and were intended to establish a central hub for innovative teaching and learning.

The project was part of the federal and state funding initiative “Künstliche Intelligenz in der Hochschulbildung”, was selected as one of 54 projects, and received approximately two million euros in funding until the end of 2025. Through ZAKKI and its participation in the joint project Ai.Engineering, the university strengthened its profile in the field of AI and positioned itself as a center of expertise in this area.

The image shows the heads of a human and a humanoid robot facing each other and looking into one another’s eyes.

Project results

Development of teaching and learning materials from which teaching modules across all disciplines benefit
Development of teaching and learning materials on general advisory topics, e. g. AI and academic writing
Launch of the website kiandme.h2.de, which provides a wide range of teaching and learning materials
Establishment of additional formats, such as the AI.CodingClub and the KI-Stamtisch. These formats will continue beyond the end of the project.
Implementation of the podcast KI Insights. Access the podcast here.
Design of self-study courses, e. g. Interdisciplinary Foundations of AI
Implementation and provision of technical tools, e. g. the AI assistant h2 Chat

Publications and Contributions

Andrae, V., Mäule, J. & Behrendt, F. (2025, Oktober). AI-Based Calibration by Using a Motion Capture System for Autonomous Mobile Robots. IFAC PapersOnLine, 59 (10), 903–908. 10.1016/j.ifacol.2025.09.153
Behrendt, F., Wollert, T., Schmidtke, N. & Weigert, D. (August 2024). Meeting the Complexity of Industrial Requirements – Digital Learning Platform for Innovative Application Domains. 7th International Conference on Logistics Operations Management (GOL’24), Volume: 7th. 10.1007/978-3-031-68628-3_37
Müller, L. M. & Enzberg, S. von. „KI für alle: verstehen, anwenden, reflektieren“: Ein interdisziplinäres Lernangebot der Hochschule Magdeburg Stendal im Bereich KI. In N. Kieseler & S. Schulz (Hrsg.), Workshopband der 22. Fachtagung der Bildungstechnologien (Delfi). Gesellschaft für Informatik e.V. 10.18420/delfi2024-ws-26
Müller, L. M., Hajji, R., Enzberg, S. von, Donner, R. & Döring, D. (im Erscheinen). Einfluss von KI-Nutzung und Integration von KI-Tools in die Lehre auf die studentische Leistung im Data-Science-Kontext. Tagungsband zur MINT digital – Digitale Lehre im Zeitalter der Künstlichen Intelligenz, September 2025.
Müller, L. M., Hajji, R., Enzberg, S. von & Döring, D. Die Entwicklung der Handlungsfähigkeit beim Einsatz von KI-Tools zur Python-Programmierung: Eine Grounded-Theory-Studie zum Einsatz von KI-Tools im projektbasierten Lernen an Hochschulen. Journal für allgemeine Didaktik, 13/2025, S. 37–59. 10.35468/jfad-13-2025-02
Sonnenberg, R. & Döring, D. (September 2023). Auswertung geot. Labor-Daten mit Methoden Künstlicher Intelligenz (KI). Deutsche Gesellschaft für Geotechnik e.V. (DGGT), Würzburg 2023. Fachsektionstage Geotechnik.
Scorna, U., Domine, I., Schäfer, J. & Voß, G. Multidisziplinarität, Interdisziplinarität und Transdisziplinarität. Formen kollaborativen Forschens im Rahmen von Design-Based Research- Projekten. die hochschullehre, 11, 167–180. 10.3278/HSL2455W
Scorna, U., Weigert, D. & Behrendt, F. KI in der Hochschulbildung. Von der Notwendigkeit und ersten Erfahrungen bei der kooperativen Entwicklung didaktisch innovativer KI-Lehr-Lernangebote nach dem Design-Based Research (DBR)-Ansatz. die hochschullehre, 11, 66–80. 10.3278/HSL2448W
Von Enzberg, S., Müller, L.M., Döring, D., Hajji, R. (im Erscheinen). Domänenadaptierte LLMs als Lernassistenten in der Hochschullehre: Fallstudie und Erfahrungen für die Lehre in IT und Data Science. Tagungsband zur MINT digital – Digitale Lehre im Zeitalter der Künstlichen Intelligenz, September 2025.
Voß, G., Hajji, R., Schäfer, J. & Müller, L. M. (2025). Lernpfade als Instrument zur ko-kreativen Gestaltung und Evaluation von Lehr-Lernangeboten im Rahmen des Design-Based Research-Ansatzes. In J. Jörissen, D. Möller, M. Grein, S. Kopczynski & D. A. Peters (Hrsg.), Evaluation von Studium und Lehre ko-kreativ gestalten. Waxmann Verlag GmbH.
Weigert, D., Scorna, U. & Behrendt, F. (2023). KI-Kompetenzen in ingenieurswissenschaftlichen Studiengängen entwickeln und fördern – Ein Praxisbeispiel für aktivierende Lehr-Lern-Angebote mittels Lerntagebuch. Informatik 2023 – Lecture Notes in Informatics (LNI), Gesellschaft für Informatik e. V. (GI). 10.18420/inf2023_50
Weigert, D. & Behrendt, F. (September 2022). Conceptual Framework of a Learning Experience Platform (LXP) to Strengthen AI Competence by Linking Simulation Technologies and AI. Proceedings of the 21st International Conference on Modelling and Applied Simulation (MAS 2022), 19th International Multidisciplinary Modeling & Simulation Multiconference (I3M 2022). 10.46354/i3m.2022.mas.024

AI.Analytics-Lab

[Translate to English:] Das Bild zeigt eine Grafik in 3D mit einer menschlichen Hand darüber.

The AI.Analytics Lab coordinated and consolidated teaching activities in the fields of artificial intelligence and data science across all disciplines. The developed teaching and learning content, as well as innovative teaching formats, particularly fostered competencies in data literacy, stochastic and statistical thinking, as well as algorithmic thinking and programming.

The focus was on a structured and algorithmic approach to the acquisition, analysis, and interpretation of large datasets using modern data analytics methods.

Lab supervisor
Prof. Dr. rer. nat. Reik Donner

AI.Tech-Lab

[Translate to English:] Das Bild zeigt Zahnräder. Der Hintergrund ist bunt und futuristisch.

The AI.Tech Lab coordinated and consolidated teaching activities in the fields of business, engineering, and sports sciences, as well as in the area of human–technology interaction. Existing offerings were systematically interconnected and complemented by interdisciplinary formats.

The developed teaching and learning content particularly fostered competencies in the technical implementation of AI and its integration into discipline-specific use cases across various practical fields within the university.

Lab supervisor
Prof. Dr.-Ing. Fabian Behrendt

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AI.Social-Lab

[Translate to English:] Das Bild zeigt die Hand eines Roboters und eines Menschen, die sich mit dem Zeigefinger berühren.

The AI.Social Lab coordinated and consolidated teaching activities in the social, educational, health, and humanities disciplines, while specifically promoting interdisciplinary exchange and the sustainable networking of existing and future initiatives. The developed teaching and learning content, as well as innovative teaching formats, particularly strengthened the ability for critical thinking in the context of artificial intelligence and questions concerning the reflective use and design of AI-based systems.

Lab supervisor
Prof. Dr.-Ing. Sebastian von Enzberg

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AI.Teach-Lab

[Translate to English:] Das Bild zeigt einen aufgeklappten Laptop.

The AI.Teach Lab coordinated the higher education didactic research accompanying the conditions for successfully teaching and learning AI competencies. In addition, it regularly conducted university-wide needs assessments in order to further develop the Lab’s offerings on an evidence-based basis.

The insights gained were published in numerous publications and presentations and were incorporated into the development of the guidelines for the use of generative AI. The primary focus was on generating knowledge to support well-founded pedagogical and didactic assessments of teaching and learning artificial intelligence.

Lab supervisor
Prof. Dr. Rahim Hajji

Professor Profile