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AI-SKILLS

Humboldt-Universität zu Berlin

AI-SKILLS

Institution: Humboldt-Universität zu Berlin Category: Project
Website: https://www.ai-skills.hu-berlin.de/

Short Description

The service provides an application-oriented IT infrastructure based on a JupyterHub for university teaching. Target users are faculty and students from all disciplines who wish to apply KI methods in research-based teaching and learning settings. The main benefit for universities is the centralized provision of computing power, storage capacity, and Jupyter Notebooks, which facilitate the development and use of Computational Essays as well as the reuse of teaching materials.

General Description

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Thematic Classification

Subject Areas

  • Computer Science
  • Natural Sciences
  • Humanities
  • Social Sciences
  • Digital History
  • Media Studies
  • Linguistics and Literary Studies
  • Physics
  • Digital Knowledge Management

Research Fields

  • Machine Learning
  • Symbolic AI
  • AI Pedagogy
  • Open Educational Resources (OER)
  • Computational Essays
  • Research-Oriented Teaching with AI
  • Digital Education and Higher Education Didactics
  • Interdisciplinary AI Applications in Humanities and Natural Sciences
  • Ethics and Societal Implications of AI
  • Generative AI in Teaching
  • Sustainable Reuse of Teaching and Learning Materials
  • Community of Practice in Higher Education Context
  • AI-Based Teaching and Learning Infrastructure (JupyterHub)

Specializations

  • Application-oriented transfer of AI methods and AI technologies in university teaching
  • Focus on methods of machine learning and symbolic AI
  • Development and use of Jupyter Notebooks and a JupyterHub for the teaching and learning infrastructure
  • Introduction of Computational Essays as an assessment format to evaluate practical AI applications
  • Establishment of Communities of Practice in the fields of humanities, social sciences, and computer science/natural sciences
  • Promotion of Open Educational Resources (OER) and sustainable reuse of teaching and learning materials
  • Integration of AI competencies into research-oriented teaching and learning settings according to the Humboldtian ideal of education
  • Support for educators through Community Catalysts in developing discipline-specific AI teaching offerings
  • Integration of competence-oriented didactics with AI research methods and agile advancement of IT infrastructure
  • Promotion of sustainability and effectiveness through continuous evaluation and networking with central university institutions (bologna.lab, CMS)

Keywords

-AI Skills
-JupyterHub
-Computational Essays
-Communities of Practice
-Open Science
-KI Didaktik
-Teaching with KI
-Higher Education Didactics
-OER (Open Educational Resources)
-Research-Oriented Teaching

Funding

Funding Provider: -
Funding Program: AI-SKILLS
Funding Reference: 2023-2025
Funding Period: 2023–2026
Project Volume: Das Volumen oder "INSUFFICIENT"

Team & Partners

Project Leadership

Lilian Löwenau (Humboldt-Universität zu Berlin)

Involved Persons

  • Lilian Löwenau, M.Sc. (Community Catalyst Natural Sciences and Computer Science)
  • Anna Faust, M.A. (Community Catalyst Humanities)
  • Martin Dröge, M.Sc. (Community Catalyst Natural Sciences / Mathematics / Computer Science)
  • Jan Krämer, M.A. (Community Catalyst Social Sciences)

Affiliated Institutions

-

External Partners

Project Contents

Goals

  • Support for teaching staff in the application-oriented delivery of AI methods and technologies in university teaching
  • Establishment of an application-oriented IT infrastructure (e.g. JupyterHub) for AI-based teaching and learning settings
  • Promotion of Communities of Practice in the fields of humanities, social sciences, and natural sciences/computer science
  • Development and dissemination of Open Educational Resources (OER) and Computational Essays as examination formats
  • Sustainable embedding of AI competencies in teaching through interdisciplinary exchange and higher education didactic further training

Work Packages

  • WP1: Establishment and promotion of Communities of Practice (Humanities, Social Sciences, Computer Science/Natural Sciences)
  • WP2: Development and provision of an application-oriented IT infrastructure (JupyterHub with computing power, storage capacity, Jupyter Notebooks)
  • WP3: Design and implementation of KI-specific teaching and learning settings in research-oriented contexts
  • WP4: Introduction and evaluation of Computational Essays as an examination format
  • WP5: Development and dissemination of Open Educational Resources (OERs) and teaching-learning modules
  • WP6: Qualification and support of teaching staff through Community Catalysts and the certification program “Artificial Intelligence”
  • WP7: Public relations, events, and networking (workshops, lecture series, panel discussions, poster presentations)

Methods

  • Application-oriented infrastructure for KI communities in teaching and learning settings
  • Community of Practice (CoP) approach
  • JupyterHub infrastructure with Jupyter Notebooks
  • Computational Essays as assessment format
  • Open Science principles for reuse and dissemination of teaching and learning materials
  • Agile further development of IT infrastructure
  • Competency-oriented didactics
  • Research-based teaching with focus on „learning AI by doing AI“
  • Interdisciplinary exchange between humanities, social sciences, and natural sciences
  • Development and provision of Open Educational Resources (OERs)
  • Use of „Learning Bricks“ as small, reusable teaching and learning building blocks
  • Collaboration with central university institutions (bologna.lab, CMS)
  • Certification program „Artificial Intelligence“ for teaching staff
  • Lecture series on KI with interdisciplinary approach
  • Hands-on workshops on generative AI and Large Language Models
  • Collegial consultation and exchange of experiences within communities
  • Systematic evaluation of measures
  • Networking of teaching staff through regular community meetings and workshops

Expected Outcomes

  • Development and implementation of an application-oriented IT infrastructure based on a JupyterHub to support KI-based teaching and learning settings
  • Establishment of Communities of Practice in the fields of humanities, social sciences, and computer science/natural sciences to ensure sustainable networking and further development of KI didactics
  • Identification and joint further development of generic and discipline-specific learning content as well as teaching and learning modules (e.g., “Learning Bricks”, OERs)
  • Introduction of Computational Essays as an innovative assessment format to evaluate the practical and reflective application of KI technologies
  • Promotion of the sustainable integration of KI methods and technologies into university teaching across all disciplines
  • Strengthening of discipline-specific and interdisciplinary KI competencies among students through research-oriented teaching and learning settings ("learning AI by doing AI")
  • Systematic integration of central university institutions (bologna.lab, CMS) to support and disseminate the developed materials in accordance with Open Science principles
  • Establishment of a certification program “Artificial Intelligence” for teaching staff to recognize higher education didactic competencies in the field of KI
  • Dissemination and reuse of the developed teaching and learning materials via OER platforms and media repositories of Humboldt-Universität
  • Continuous evaluation and agile further development of the infrastructure

Contact

Contact Person: Community Katalysatorin Naturwissenschaften und Informatik: Lilian Löwenau
Email: -
Project Website: https://www.ai-skills.hu-berlin.de/

Recorded: 2026-01-11
Source: https://www.ai-skills.hu-berlin.de/

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