Within the junior research group „AI-based Coaching for Students, Adaptive User Interfaces, Human-centered AI“, 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, it 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.
Projects
Currently, the research group „AI-based Coaching for Students, Adaptive User Interfaces, Human-centered AI“ is working on two PHD Projects.
- AI-based mental health support for students – Multimodal delivery of personalized exercises and content to support the mental health of users through conversational agent-based CBT
- Investigating the impact of generative language models on students‘ learning
Additionally, the group is organizing several projects, among others the following two:
- AI-based coaching of women in STEM subjects to improve student success.
- Personalized AI-based recommendations of support services for immigrant students.
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
The junior research group leader, Dr.-Ing. Claudia Loitsch, started at ScaDS.AI Dresden in January 2023. She studied Media Computer Science at the TU Dresden and obtained a doctorate in engineering at TU Dresden 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 Members
Publications
By now, no papers have been publicated by the junior research group.