Needs-Oriented AI-Coaching
for Students (NAIC)

Within the junior research group “Needs-oriented AI-Coaching for Students”, the team is investigating the use and efficacy of AI-driven coaching methodologies in higher education. The primary focus is on exploring and developing intelligent and adaptive conversational agents to enable tailored learning journeys and personalized coaching support.

Furthermore, the group is investigating the use of AI and specifically NLP technologies for mental health support. In this new and fast-growing research field, the team is focusing on voice assistant-based interventions for mental health support of students as well as on the tracking of emotional and mental health states through conversational agents.

AI research in this research group is application-oriented, adhering to the human-centered design process and placing a strong emphasis on the diverse profiles of our target audience. This includes their sensory and cognitive (learning) abilities, as well as the scope of their individual and mental resources.

There is a widely shared consensus that AI technologies, particularly adaptive learning systems and the personalized delivery of optimized learning content, have the potential to enhance learning success. However, there is currently a lack of sound empirical studies on the use and impact of AI technologies in higher education — a gap that our research seeks to address.

Focus topics: Adaptive user interfaces, human-computer interaction, human-centered AI, participatory design, NLP, LLMs

The image is a graphic illustrating the concept of "Needs-oriented AI-Coaching for Students (NAIC)." It shows a large laptop with the text "NAIC" on its screen. A small figure sits on top of the laptop screen, touching a signal icon, while a female figure with glasses and a graduation cap waves in front of the laptop. A bearded male figure stands to the left, looking at the laptop. The background features a cloud shape with arrow patterns and signal icons, indicating connectivity. On the right, there are two speech bubbles that say "Support mental health" and "Self-directed learning & studying success." At the bottom, the text reads "Needs-oriented AI-Coaching for Students (NAIC)."

Projects

Furthermore, the group is partnering with research groups of the Karolinska Institute in Sweden with the long-term goal of applying our research to internet-based therapy platforms.

Junior Research Group Leader

Portrait of Dr.-Ing. Claudia Loitsch

Dr.-Ing. Claudia Loitsch

Research Group Leader

TU Dresden

claudia.loitsch@tu-dresden.de

The junior research group leader, Dr.-Ing. Claudia Loitsch, started at ScaDS.AI Dresden in January 2023. She studied Media Computer Science at the TUD Dresden University of Technology and obtained a doctorate in engineering at TUD Dresden University of Technology on the topic of “Designing Accessible User Interfaces for All by Means of Adaptive Systems”. For this work, Loitsch was awarded by the 3m5 Excellence award.

Since 2010, Loitsch delved into digital accessibility, human-computer interaction, adaptive user interfaces, and the fascinating field of artificial intelligence. Her research is on Diversity-aware design – an endeavor where technology adapts itself to human abilities and needs, not the other way around. It’s not just about those with disabilities. It’s about each of us, with our ever-changing needs and skills, whether in a specific moment, environment or across a lifetime.  This research lays the foundation for the design and development of adaptive AI-driven UIs that groove with the disparities in human capacities, diverse work methodologies or learning behaviors, or individual preferences and requirements in the context of digital technologies.

Her scientific achievement is centered on enhancing the field of accessible User Interface (UI) engineering by integrating user-adaptive design and knowledge-based modeling to cater to the needs of people with diverse needs, including people with disabilities. Loitsch developed an integrated semantic knowledge base for computation and automation of User Interface (UI) adaptation in the scope of eAccessibility and Usability. The core contribution of this achievement lies in addressing the heterogeneity and complexity of customization options of ICT as well as the fragmented nature of existing know-how across various user domains and target groups, while also formalizing a structured approach to extend this knowledge for effective UI adaptation and scalability to other contexts.

Team

Team Members

Portrait of Julian Striegl

Julian Striegl

TU Dresden

julian.striegl@tu-dresden.de

Portrait of Chrakhan Barzanji

Chrakhan Barzanji

TU Dresden

chrakhan.barzanji@tu-dresden.de

Advisor

Portrait of Prof. Dr. rer. nat. habil. Gerhard Weber

Prof. Dr. rer. nat. habil. Gerhard Weber

TU Dresden

gerhard.weber@tu-dresden.de

Publications

Events

TU
Universität
Max
Leibnitz-Institut
Helmholtz
Hemholtz
Institut
Fraunhofer-Institut
Fraunhofer-Institut
Max-Planck-Institut
Institute
Max-Plank-Institut