Focus areas
Learning is hard work. We know this only too well from our own experience. Our research in the field of cognitive load deals with factors that are particularly strenuous and investigates how this effort can be continuously monitored. In addition to performance measures, behavioral parameters and physiological indicators, we also use cognitive modeling approaches (e.g., the cognitive architecture ACT-R) to formalize cognitive processes and mechanisms underneath.
The presented work emerged in collaboration with the Cognitive Modeling Group at the University of Groningen within the Research Training Group CrossWorlds at Chemnitz University of Technology. We thank the German Research Foundation and the Saxon State Ministry for Science, Culture and Tourism for supporting our research.
Learning material with high complexity or redundant information unnecessarily strains learners' cognitive resources, might lead to frustration and reduced learning gains. Therefore, adaptively aligned instructional support, e.g., with increasing expertise or in critical affective states, is beneficial. However, looking into current literature shows that structured and formalized metrics and diagnosis concepts are still missing. We approach such developments building on (neuro-)physiological markers and big data from intelligent learning platforms.
In our digital age, information is present everywhere. This often distracts us from our actual goals and interrupts our ongoing activities. In learning and working contexts, this has tremendously negative effects. Hence, building on formal models of cognitive control, we investigate approaches to strengthen attention control. We further explore beneficial resumption strategies and how they can be trained.
The presented research was conducted collaboratively with the Software Workshop and the Rationality Enhancement Group at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, with kind support from the Cyber Valley Research Fund.
In 2015, the member states of the UN adopted the Agenda 2030 for sustainable development, which among other things stipulates the protection and restoration of our ecosystem. In this context, digital media can help to raise awareness of environmentally friendly actions and bring about sustainable changes in behavior. We use a user-centered design approach to connect virtual and real learning environments and foster innovative learning concepts.
Technical devices can be used most effectively to support learning processes if they take into account that different people use them in different ways. We are therefore investigating the ways in which factors such as age, gender, affinity for technology or neurodiversity influence this and incorporate these parameters into the responsible design of assistive technology.
Artificial intelligence is part of our everyday life, a component of technical innovations and increasingly becoming part of education. Intelligent systems are often assumed to make objective decisions, but numerous examples demonstrate how such systems take over our conscious and unconscious stereotypes and biases. By initiating processes of reflection, we strive to sensitize people to societal implications of these stereotypes and biases in intelligent systems. Ongoing projects in this area relate to modelling mechanisms of metacognitive reflection, AI-generated biases, and human trust in AI-based systems.
Ongoing dissertations
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.
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.
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).
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.
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
- Prof. Dr. André Bächtiger
- Prof. Dr. Reinhold Bauer
- Prof. Dr. Sibylle Baumbach
- Dr. Gabriella Lapesa
- Prof. Dr. Steffen Staab
(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 - 07/2024
Cooperation (Subproject SKILLS - Work packages M2.1, M2.4)
Funding
The project is funded by the Foundation for Innovation in Higher Education.
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 - 12/2023
Cooperation
- Prof. Dr.-Ing. Steffen Becker
- Prof. Dr.-Ing. Felix Fritzen
- Prof. Dr. Steffen Staab
- Prof. Dr. Stefan Wagner
(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 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
09/2021 - 08/2024
Cooperation
- Institute of Educational Science (IfE), Department of Vocational Education focused on Teaching Technology
- Institute of Human Factors and Technology Management (IAT)
- Fraunhofer IAO
- auticon GmbH
- NIRx GmbH
- Sensovo GmbH
The Department of Teaching and Learning with Intelligent Systems (LLiS) is coordinating the project network.
Funding
The project is 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
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
- Prof. Dr.-Ing. Michael Resch, High Performance Computing Center Stuttgart (HLRS)
- Prof. Dr. Bernd Zinn, Institute of Educational Science (IfE)
- Dr.-Ing. Daniel Roth, Institute for Engineering Design and Industrial Design (IKTD)
- Prof. Dr. Steffen Staab, Institute for Parallel and Distributed Systems (IPVS)
- Dr. Andreas Kaminski, Institute for High-Performance Computing (IHR)
- Prof. Dr. Stefan Wagner, Institute of Software Engineering (ISTE)
- Prof. Dr. Alexander Brem, Institute of Entrepreneurship and Innovation Science (ENI)
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.
BeeCreative - Fostering awareness for sustainability with a creative AI-based educational technology
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 - 06/2024
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
The project aims to critically reflect on the societal implications of simulation science. This includes, but is not limited to, ethical and social concerns related to simulation science, such as data ethics, privacy issues, or the dual use of research findings; the function of various media (including literature and art) in critically reflecting on potential risks and impacts of simulation science; and empirically informed impact assessment of research approaches within EXC 2075.
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
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
- Prof. Dr. Oliver Röhrle (Spokesperson of the IRTG 2198, University of Stuttgart)
- Auckland Bioengineering Institute (University of Auckland, New Zealand)
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.