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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, supporting faculty and students of Humboldt-Universität zu Berlin in integrating KI methods into teaching and learning settings. The target group includes faculty from all disciplines who wish to convey KI-based content in a research-oriented and practical manner. The main benefit for universities lies in the simplified creation, documentation, and reuse of learning materials through Jupyter Notebooks, as well as the introduction of Computational Essays as an examination format. This promotes the development of discipline-specific KI competencies and ensures a sustainable, agile implementation adapted to evolving needs.

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
  • Faculty of Philosophy
  • Digital Knowledge Management

Research Fields

  • Machine Learning
  • Symbolic AI
  • AI Didactics
  • 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 (e.g., 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 implementation of AI-specific teaching and learning settings
  • Use of JupyterHub for the integration of Jupyter Notebooks, computing power, and storage capacity
  • Introduction of Computational Essays as an assessment format to evaluate practical application competencies
  • Establishment of Communities of Practice in the fields of humanities, social sciences, and computer science/natural sciences
  • Promotion of Open Science principles through the dissemination and reuse of OER (Open Educational Resources)
  • Support for instructors through Community Catalysts in the development and further development of teaching materials
  • Integration of AI didactics with competence-oriented higher education didactics and agile IT infrastructure
  • Networking with central university institutions such as bologna.lab and CMS of Humboldt-Universität zu Berlin
  • Promotion of sustainability through continuous evaluation and institutionalization of measures

Keywords

-AI Skills
-JupyterHub
-Computational Essays
-Communities of Practice
-Open Science
-KI Didaktik
-Higher Education Teaching
-Machine Learning
-Symbolic AI
-OER (Open Educational Resources)

Funding

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

Team & Partners

Project Leadership

  • Lilian Löwenau (Humboldt-Universität zu Berlin)

Involved Persons

  • Lilian Löwenau (Community Catalyst Natural Sciences and Computer Science)
  • Anna Faust (Community Catalyst)
  • Martin Dröge (Community Catalyst)
  • Jan Krämer (Community Catalyst)

Affiliated Institutions

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External Partners

Project Contents

Goals

  • Support for teaching staff in the application-oriented dissemination of AI methods and technologies across all disciplines
  • Establishment of a sustainable, interdisciplinary infrastructure for AI-based teaching and learning settings with a focus on machine learning and symbolic AI
  • Promotion of Communities of Practice to connect teaching staff and jointly develop teaching materials
  • Introduction of Computational Essays as an assessment format to strengthen practical and reflective AI application
  • Systematic dissemination and reuse of Open Educational Resources (OER) in line with Open Science

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, Jupyter Notebooks, computing power, storage capacity)
  • WP3: Design and implementation of KI-specific teaching and learning settings in close collaboration with instructors
  • WP4: Introduction and evaluation of Computational Essays as an examination format
  • WP5: Identification, development, and dissemination of Open Educational Resources (OERs) and teaching modules
  • WP6: Establishment of a certification program “Artificial Intelligence” for instructors to recognize higher education didactic competencies
  • WP7: Systematic evaluation of measures and continuous improvement of infrastructure and didactic approaches
  • WP8: Public relations, networking, and knowledge transfer (e.g., panel discussions, workshops, poster presentations, events)

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 dissemination and reuse 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
  • Collegial consultation and exchange of experiences within communities
  • Practice-oriented workshops with hands-on elements (e.g. generative AI)
  • Lecture series with interdisciplinary access to KI topics
  • Panel discussions and information events on ethical, societal, and didactic aspects of KI
  • Evaluation of continuous measures to ensure sustainability and effectiveness

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 contents and teaching and learning settings for KI methods and technologies
  • Introduction of Computational Essays as an assessment format to evaluate practical, data- and code-based application competencies
  • Promotion of Open Science principles through the systematic dissemination and reuse of Open Educational Resources (OER) in the media repository of Humboldt-Universität zu Berlin
  • Development of a certificate program "Artificial Intelligence" to recognize higher education didactic competencies in conveying KI content
  • Sustainable embedding of KI didactics in university teaching through close integration of competence-oriented didactics, agile IT infrastructure, and continuous evaluation
  • Strengthening of KI competencies among students through research-oriented teaching and learning settings and the study focus "K

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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