With digitalization, learning behavior and circumstances in Higher Education are changed. In addition, it is necessary to respond to the diversity of students by using technology to enable individual approaches for studying. Concepts for personalized learning environments and digital mentoring are necessary to promote the acquisition of skills and needs by a larger number of students.

Since 2018 an interdisciplinary consortium from several universities and institutions in Germany addresses the central research question: What must design concepts look like that make the quality of digitally supported, intelligent mentoring processes scalable within an intelligent educational environment?

The collaboration has contributed to the interdisciplinary integration of pedagogical theory, educational psychology, artificial intelligence (AI) and advanced computational methods. This has advanced the development and implementation of digitally supported intelligent mentoring processes within a collaborative education environment. Mainly the focus was to develop concepts for personalized learning environments and mentoring for students. A central aspect was research into how to best support students' learning processes with technology. Mentoring in higher education is changed through the integration of hybrid technologies and mixed reality. It focuses on creating a sophisticated digital ecosystem that combines human expertise with AI capabilities to deliver personalized mentoring experiences. The consortium defined a Mentoring Environment with a central Mentoring Workbench, which serves as the primary interface for teachers and students. It provides a dashboard that visualizes individual learning processes and suggests specific pedagogical interventions. Also emphasizes scalability by developing methods to transfer the quality of individual mentoring to larger groups of students. At the same time, this initiative brings together interdisciplinary experts to ensure that AI applications are based on effective pedagogical principles. Learning analytics plays a central role in the continuous evaluation and improvement of the mentoring system by tracking student progress and assessing the impact of different strategies. Particular attention is paid to data protection and ethical considerations. Key Point is to provide high quality and personalized support for all students, making expert support accessible regardless of the size or department of the institution. By addressing challenges such as dropout rates and learning outcomes, this initiative has the potential to significantly improve support services in higher education and redefine academic mentoring for the digital age.

In order to answer the research question, learning and assessment environments were systematically developed both didactically and technologically and institutionalized via test fields and academic semesters. Given the ongoing transformations in higher education and education policy, the guiding research question remains highly relevant to address the challenges of digital transformation in the university context. These results have helped to promote personalized learning environments and improve the quality of university teaching through technology-supported mentoring.

Keywords: Higher Education, Mentoring, Scalable, Personlized Skills.