Research

Department of Teaching and Learning with Intelligent Systems (LLiS)

Our research deals with topics related to modeling human cognition and the derived design of responsible human-technology interaction.

Research focus

Our research is dedicated to various facets of the responsible, human-centered design of intelligent technical systems as well as potential opportunities, risks and changes that arise from their use. The focus is on the following questions, among others:

  • How can intelligent technology be adapted to the cognitive, affective and motivational states of users?
  • How can intelligent technical systems take users' cognitive differences into account?
  • In which ways can intelligent feedback promote self-regulated learning and work?
  • How does the use of intelligent technical systems change us as humans, our society and the world of work?
  • When do people trust intelligent technical systems?
  • How can different target groups be sensitized to the potential risks of intelligent technical systems?

Ongoing dissertations

Affect-adaptive systems detect the current emotional state of the user and are capable of adequately responding by adapting the interaction. Emotional user states such as anger or anxiety can influence performance in human-machine systems, which may have fatal consequences in safety-critical environments. The aim of this project is to develop emotional state diagnostics for this domain that allows for continuous discrimination of “critical emotional states” and “uncritical emotional states”. The diagnostics considers interindividual differences in the emotion-performance relationship in order to adjust adaptive mechanisms individually and thus achieve optimal support for the user.

This dissertation is conducted within the GS SimTech in collaboration with the Fraunhofer FKIE.

In learning contexts, interruptions are pervasive and often difficult to avoid, resulting in recurrent attentional shifts while performing a task. While learning constitutes a highly individualized endeavour, the influence of individual differences in how we resume from interruptions during learning tasks is largely unexplored. Moreover, individual differences have so far only been related to differences in working-memory capacity, cognitive workload and strategy consistency. Hence, this dissertation sheds light on additional individual factors can influence the process of resumption from interruptions, and further investigates types of task-internal characteristics that can facilitate the process of resumption from interruptions. It also explores how resumption strategies are characterized across different learning tasks.

This dissertation is conducted within the IMPRS-IS in co-supervision with Prof. Dr. Andreas Bulling.

Consumer behavior is crucial for a change to a more sustainable world. To develop interventions that promote pro-environmental behavior, we need to shed light on cognitive mechanisms underneath sustainable thoughts and how they stimulate actions. Individual differences in the factors and cognitive mechanisms of sustainable behavior are under-explored. Therefore, this dissertation examines cognitive factors that influence sustainability using a mixture of psychological and computational methods. Hence, special attention will be paid to these individual factors through clustering and elaboration of personas. Since the practical implementation of measures that promote sustainable behavior is also to be improved, the possible application of the research results is also considered.

This dissertation is conducted within the GS SimTech in collaboration with the Robert Bosch GmbH.

The usage of artificial intelligence (AI) improves the previously used methods to identify diseases, translate languages or save energy. Such improvements need specialized domain knowledge of the respective field. However, during their studies in those domains, students regularly do not learn a lot about AI. The correct usage of AI needs an understanding of how it works. In the context of AISA, we work on a didactic concept to improve the education about AI, especially for students working on their dissertation, to further enhance research using AIs.

This dissertation is conducted within the Artificial Intelligence Software Academy (AISA) in co-supervision with Prof. Dr. Steffen Becker.

Artificial Intelligence (AI) is a rapidly developing field. Intelligent systems such as AI-powered chatbots, autonomous vehicles, and virtual assistants for example, are becoming increasingly prevalent and indispensable in our daily lives. Despite the many benefits of AI, that make our lives easier, more productive and convenient, there are also concerns about its impact on society. Some people over-rely on AI in their daily tasks and others do not trust these new technologies at all. However, as we rely more and more on these systems, it is essential to understand the cognitive mechanisms underlying human trust in them. Trust is a complex phenomenon, shaped by various factors, i.e., transparency, risk and loss, emotions, biases, cognitive dissonance, expectations and many more. In order to create a cognitive model to predict trust in AI, as part of this project, these factors influencing trust need to be explored and analyzed further. Through experimental studies, this research aims to explore the cognitive mechanisms of trust in intelligent systems as well as the effect of manipulating these variables.

This dissertation is conducted within the GS SimTech and the Interchange Forum for Reflecting on Intelligent Systems (IRIS).

Ongoing funded projects

Project focus

The SRF IRIS aims to create a platform to stimulate, develop and effect critical reflection on intelligent systems and their impact on society. The goal is to take up exchanges on sensitive topics such as responsible human-computer interaction, ethical and societal challenges, and the risks and benefits of automated decision-making in various fields of application, and to integrate them into the university landscape in research, teaching, and dialogue with society.

Duration

11/2020 - 12/2025

Cooperation

(Executive Board of the SRF IRIS; all University of Stuttgart)

Funding

The project is funded by the excellence package of the German Research Foundation and the Research Council of the University of Stuttgart

Project focus

In the digit@L project, the University of Stuttgart aims to support students in their individual learning process with digitally enriched teaching-learning formats and adaptive systems in view of heterogeneous prerequisites. On the one hand, the focus is on students in the important first year of study and the group-specific differentiation of basic courses in digital settings. On the other hand, the University of Stuttgart is specifically expanding the competence profile of students and lecturers. In order to achieve these goals, the project builds and connects a didactic and (media) technical infrastructure for students and teachers. Taken together, this contributes to a culture of digital innovation.

Duration

08/2021 - 07/2025

Cooperation (Subproject SKILLS - Work packages M2.1, M2.4)
Funding

The project is funded by the Foundation for Innovation in Higher Education.

 

News Announcement: June 7, 2021, Nr. 44 University of Stuttgart successful in new federal-state funding program for digital teaching (German)

Project focus

The goal of the AISA project is to impart competencies in AI methods and software engineering to students at the University of Stuttgart across all fields of study, aligned with the particular needs of the target group. In addition to the pure transfer of knowledge, there is a considerable need for research in the triangle of AI, software engineering and engineering applications, including the tailored design of didactic approaches in the field of AI software engineering. We are addressing this issue in the subproject "Perspectives on the didactic design of domain-specific AI competencies in the context of software engineering".

Duration

08/2021 - 12/2025

Cooperation

(Executive Board; all University of Stuttgart)

Funding

The project is funded by the Ministry of Science, Research and the Arts Baden-Wuerttemberg.

Project focus

The project IKILeUS aims to bundle the existing expertise of many collaborating departments on AI in order to both communicate AI to the breadth of the student body in an interdisciplinary view and to use AI-based technologies in teaching to relieve the burden on teachers and to improve teaching. The topics will be addressed with a focus on specific courses and software solutions, while at the same time looking at further potential of other user groups and areas.

Duration

12/2021 - 11/2024

Cooperation
Funding

The project is funded by the Federal Ministry of Education and Research within the funding scheme "AI in Higher Education".

Project focus

Artificial intelligence (AI) influences all areas of our lives as a key technology. This project investigates how it can enrich our society in three subject areas that are being intensively shaped, if not revolutionized, by AI: diversity, demography, and democracy. In addition to three junior research groups, the project provides seed funding for several research projects.

Duration

04/2022 - 12/2026

Cooperation

Prof. Dr. Steffen Staab (University of Stuttgart, Institute for Parallel and Distributed Systems)

Funding

The project is funded by the Ministry of Science, Research and the Arts Baden-Wuerttemberg.

The BeeCreative project aims to integrate real nature experiences with technology-supported creativity processes to foster awareness for biodiversity. Urbanly integrated information boards are combined with an interactive AI-based sketchbook to create an innovative learning experience for a broad public.

Duration

01/2023 - 12/2024

Funding

The project is funded by the Baden-Württemberg Stiftung in cooperation with the Heidehof Stiftung in the funding scheme "Learning sustainabilty – children design future".

Project focus

Emerging from the EXC 2075 committee "Platform of Reflection", this project aims to develop a deeper understanding of systemic structures that govern dynamics of AI adoption within society and organizations, which will help to identify potential risks and opportunities, as well as propose actionable policies that will work for the betterment of our socio-economic systems. The project investigates this topic through conceptual analysis, system dynamics modeling and computer simulation, and laboratory experiments.

Duration

02/2023 - 01/2025

Cooperation

(Platform of Reflection; all University of Stuttgart)

Funding

The project is funded by the German Research Foundation within the Cluster of Excellence "Data-Integrated Simulation Science" (EXC 2075).

Completed funded projects

Project focus

The UFO project aims to promote occupational participation particularly for people with enhanced needs for socio-emotional support. By developing a novel training system building up competencies in the perception and interpretation of emotional states should be supported. The system captures brain signals and converts derived emotional states into tangible sensory perceptions. A tactile output enables to understand the emotional state of the interacting counterpart. A virtual environment provides a safe training space that can precisely support the needs of the target group. The approach contributes to social awareness and promotes empathy and mutual understanding in the society.

Duration (Project participation)

09/2021 - 08/2024

Cooperation

Funding

The project was funded by the Federal Ministry of Education and Research within the funding scheme "Interactive systems in virtual and real environments - Innovative technologies for the digital society".

Project focus

In our project "BeeLife", we developed an intelligent app with accompanying project workshops for schools to sensitize children and adolescents for the importance of wild bees for our ecosystem.

Duration

12/2020 - 05/2023

Cooperation

Prof. Dr. Günter Daniel Rey (Chemnitz University of Technology)

Funding

The project was funded by the German Federal Environmental Foundation.

Project focus

The MIkado project provided systematic insights into cognitive and affective facets of individual learning processes. The central goal was the systematic analysis of the interaction between cognitive and affective processes depending on the chosen indicatorization. In contrast to the predominance of artificial laboratory contexts, the project focused on cognitive-affective interactions in application-oriented task settings.

Duration

10/2020 - 09/2022

Cooperation

Prof. Dr. Kristina Kögler (University of Stuttgart)

Funding

The project was funded by the Ministry of Science, Research and Arts Baden-Wuerttemberg and the Research Council of the University of Stuttgart.

Project focus

The project focuses on the conception, implementation and evaluation of the Youth Study Baden-Wuerttemberg 2022 in cooperation with the State Pupil Advisory Council.

Duration

08/2021 - 07/2022

Cooperation

(all University of Stuttgart)

Funding

The project is funded by the Ministry of Education, Youth and Sports Baden-Wuerttemberg.

Project focus

The goal of the International Research Training Group 2198 "Soft Tissue Robotics" was to further develop simulation techniques and sensors to enable the development of new control techniques for robots interacting with soft materials.

Duration (Participation as Principal Investigator)

09/2020 - 08/2021

Cooperation
Funding

The IRTG 2198 "Soft Tissue Robotics" was funded by the German Research Foundation.

Project focus

The goal of the ACTrain project was to develop and evaluate a prototype for an AI-based training software that strengthens attentional control based on metacognitive feedback.

Duration

07/2019 - 03/2021

Cooperation

Max Planck Institute for Intelligent Systems, Tübingen Campus

Funding

The project was funded by the Cyber Valley Research Fund.

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