The collaborative project “Personalised competence development through scalable mentoring processes – tech4comp” was launched in October 2018. Coordinated by Leipzig University, the project brings together the >TU Dresden, the Educational Technology Lab of the German Research Center for Artificial Intelligence (DFKI), Martin Luther University Halle-Wittenberg, Chemnitz University of Technology, Leipzig University of Applied Sciences, the Freie Universität Berlin and RWTH Aachen University. The partners are jointly developing concepts for personalised learning environments and mentoring for the students of today and tomorrow
Over the next six years, the collaborative project will receive up to 12.6 million euros in funding from the Federal Ministry of Education and Research (BMBF). “On the one hand, the project is a response to how learning realities, and the ways people access learning, are changing in the digital age. On the other, we want to do justice to the diversity of our students, using technology to enable personalised access to learning,” says consortium leader Professor Heinz-Werner Wollersheim, who holds the Professorship in General Pedagogy at Leipzig University.
Together with colleagues from different disciplines, he is thus addressing the question of how best to accompany student learning today. Professor Christoph Igel contributes one of these specialist perspectives. He is Scientific Director of the DFKI’s Educational Technology Lab and Professor of Educational Technology at Chemnitz University of Technology, and has a wealth of experience in the use of artificial intelligence to support learning processes. He emphasises the relevance of different disciplines for the project: “tech4comp’s interdisciplinary orientation allows us versatile access to the field of student learning. We can thus explore different subject areas and also gain access to a broad range of methodological and research approaches from the individual disciplines.”
Which methods and tools are suitable for teaching in the various disciplines, and just how artificial intelligence can accompany students in their learning process, will be investigated in the field and tested for practical suitability together with students. Following successful evaluation, the resulting resources will be made available in the long term as support systems for higher education.
