KI-Komp: AI Competence in Digital Education (KI Komp)

Third party funded individual grant


Acronym: KI Komp

Start date : 01.04.2024

End date : 31.03.2026


Project details

Short description

KIKomp – AI Competence in Digital Education
KIKomp supports both students and teachers in professionally addressing the opportunities and challenges of using AI in higher education. The project embraces the multidimensional nature of the topic and is based on a co-creation approach, fostering collaboration among students, teachers, and external experts, with a strong focus on co-learning. Together, they develop, share, and advance AI-related competencies, applying principles of project-based, collaborative, problem-based, and reflective learning.

The project outcomes include courses for students, a seminar series for teaching staff, a modular toolbox, open exchange formats, and research on success factors for AI use in education. All materials and insights are designed for interdisciplinary and cross-institutional use.

The project is funded by the Freiraum 2023 program of the Stiftung Innovation in der Hochschullehre (StIL).

Project Objectives and Implementation Measures

Main Objective
The project’s main goal is to promote the competent and responsible use of AI technologies and applications in education by both teachers and students, and to explore the opportunities and framework conditions for their effective integration.

Sub-Objectives

  1. Enhancing AI and media literacy among students
    Students gain the necessary knowledge and skills to use AI tools critically and effectively in their academic fields and future careers.

  2. Enhancing AI and media literacy among teachers
    Teachers are empowered to integrate AI tools competently into their teaching and to support students in developing a critical and constructive approach to AI technologies.

  3. Defining success factors for the use of AI in education
    The project identifies the necessary conditions for successfully using AI in education, considering framework conditions, competency requirements, and ethical issues. This helps teachers plan and implement AI use in a responsible and effective way.

  4. Establishing and sharing good practices for AI use in teaching and learning
    By collecting and disseminating best practices, teachers receive inspiration and guidance to promote the effective use of AI technologies in education.

Each sub-objective contributes to the overarching goal of fostering a broader and more effective use of AI tools in education. The project is based on co-creative collaboration, critical reflection, and peer exchange among all stakeholders.

Key Measures

In addition, informational events, exchange opportunities, consulting, and co-creation formats bring together students, teachers, and experts to share experiences and needs and to co-design innovative formats.

Target Groups

Teachers
The seminar series equips teachers with skills to integrate AI tools into teaching, learning, and assessment scenarios. Topics include personalized learning, automated assessment, exam design, media production, ethics, and data protection. The interdisciplinary series is offered via the ProfiLehrePlus program of Bavarian universities and uses a blended learning concept, combining self-paced modules with synchronous phases designed as co-creation labs. These labs foster networking and build a community of practice around AI in teaching.

Students
The student course focuses on developing fundamental AI competencies for higher education. Initially piloted in the MA Learning Design (Innovation module), it will later be offered as a key competence module for students from other disciplines.

Scientific Abstract

 KIKomp – AI Competence in Digital Education

KIKomp supports both students and teachers in professionally addressing the opportunities and challenges of using AI in higher education. The project embraces the multidimensional nature of the topic and is based on a co-creation approach, fostering collaboration among students, teachers, and external experts, with a strong focus on co-learning. Together, they develop, share, and advance AI-related competencies, applying principles of project-based, collaborative, problem-based, and reflective learning.

The project outcomes include courses for students, a seminar series for teaching staff, a modular toolbox, open exchange formats, and research on success factors for AI use in education. All materials and insights are designed for interdisciplinary and cross-institutional use.

The project is funded by the Freiraum 2023 program of the Stiftung Innovation in der Hochschullehre (StIL).

Project Objectives and Implementation Measures

Main Objective
The project’s main goal is to promote the competent and responsible use of AI technologies and applications in education by both teachers and students, and to explore the opportunities and framework conditions for their effective integration.

Sub-Objectives

  1. Enhancing AI and media literacy among students
    Students gain the necessary knowledge and skills to use AI tools critically and effectively in their academic fields and future careers.

  2. Enhancing AI and media literacy among teachers
    Teachers are empowered to integrate AI tools competently into their teaching and to support students in developing a critical and constructive approach to AI technologies.

  3. Defining success factors for the use of AI in education
    The project identifies the necessary conditions for successfully using AI in education, considering framework conditions, competency requirements, and ethical issues. This helps teachers plan and implement AI use in a responsible and effective way.

  4. Establishing and sharing good practices for AI use in teaching and learning
    By collecting and disseminating best practices, teachers receive inspiration and guidance to promote the effective use of AI technologies in education.

Each sub-objective contributes to the overarching goal of fostering a broader and more effective use of AI tools in education. The project is based on co-creative collaboration, critical reflection, and peer exchange among all stakeholders.

Key Measures

In addition, informational events, exchange opportunities, consulting, and co-creation formats bring together students, teachers, and experts to share experiences and needs and to co-design innovative formats.

Target Groups

Teachers
The seminar series equips teachers with skills to integrate AI tools into teaching, learning, and assessment scenarios. Topics include personalized learning, automated assessment, exam design, media production, ethics, and data protection. The interdisciplinary series is offered via the ProfiLehrePlus program of Bavarian universities and uses a blended learning concept, combining self-paced modules with synchronous phases designed as co-creation labs. These labs foster networking and build a community of practice around AI in teaching.

Students
The student course focuses on developing fundamental AI competencies for higher education. Initially piloted in the MA Learning Design (Innovation module), it will later be offered as a key competence module for students from other disciplines.

Involved:

Contributing FAU Organisations:

Funding Source