PHD STUDENTS & POST-DOCS
TOPIC: FOSTERING FLOW IN ADAPTIVE SYSTEMS
Flow is the holistic sensation that people feel when they act with total involvement in an optimally challenging task. The experience is rewarding in itself and associated with performance, work engagement, health and general well-being. Therefore, interventions for fostering flow in knowledge work are highly desirable, especially if individualized through integration within flow-adaptive systems. In this dissertation project, different strategies for fostering flow in knowledge work are experimentally investigated and their influence on positive outcomes as performance or well-being is examined.
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TOPIC: HOW DO PEOPLE DECIDE?
We make thousands of decisions every day. Sometimes the number of options to choose from can be very large, especially in online environments. How do people adapt to such large assortments? Can they be overloaded with choice? What are the cognitive mechanisms behind this behavior? How can we help people to make better decisions? These and other questions at the intersection between psychology, cognitive science, economics, and information systems will be addressed in this dissertation project based on controlled and theory driven behavioral experiments in combination with mathematical cognitive models.
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TOPIC: SHAPING HEALTHY FOOD DECISION-MAKING
This desirable healthy behavior often relies on the control of conflicting or interfering streams of information processing. This dissertation project will focus on the identification of neuronal activity patterns as biosignals of disinhibitory behaviour in economic decision-making using the functional Magnetic Resonance Imaging (fMRI). Building on that data, the predictive value of inhibition and error signals on these kinds of decisions will be analysed. Further, it will be researched whether interactive feedback algorithms might modify and shape decision behavior.
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TOPIC: MENTAL STATES OF USERS OF COGNITIVE INTERACTION SYSTEMS
This dissertation aims to develop the foundation for the automatic adaptation of cognitive interaction systems to individual, dynamically changing, mental user states, such as the degree of attention, workload or distraction. Based on continously recorded biosignals from eye movements, brain activities, speech and muscle activities, machine learning based methods are to be developed to interpret user states using contextual knowledge. It should also be investigated whether results from lab conditions can be transferred to measurements in the field using mobile devices.
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TOPIC: EMOTION-ADAPTIVE PARTICIPATION PLATFORMS
Emotions are omnipresent in our lives. They influence our health, decision-making, and social interactions—bilateral as well as multilateral. Hence, also modern forms of opinion building and exchange, e.g., on e-participation platforms, should consider the effects of emotions on individual and group level. Previous research on group interactions demonstrated that providing the members with information about the affective state of the entire group reciprocally influences the affective states of the individuals. In this dissertation project, it will be investigated how real-time physiological information (e.g. heart rate changes as an indicator of activation/arousal) can influence platform participant's behaviors like conflict escalation and resolution or engagement in discussion processes.
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TOPIC: WEARABLES IN CUSTOMER-SALESPERSON INTERACTIONS
In interactions between customers and salespeople, both parties are oftentimes required to make far-reaching decisions with little time. Wearables could potentially provide both customers and salespeople with additional information about the situation in real time (e.g., tonality of the voice, mood, emotions, time spent listening, etc.). This could increase the adaptivity of decision-makers to the situation, aid them in the way they behave throughout the interaction, and support them in decision-making. This dissertation project will employ lab experiments and a field study to explore the way how wearables can be designed to transform speech data and biosignals into helpful feedback to customers and salespeople throughout customer-salesperson interactions. More generally, it may also provide some evidence as to whether wearable devices could potentially shift the power balance between customers and firms.
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TOPIC: EYE-BASED COORDINATION IN VIRTUAL TEAMS
The importance of virtual team work increased rapidly during the last years. Without face-to-face interactions, coordinating on joint activities can be more difficult because the non-verbal cues are missing. Visual cues, such as mutual gaze or joint attention might play a critical role in coordination. Eye-tracking technology allows to share gaze information in real-time and might help to overcome coordination failures and establish efficient outcomes. This PhD project will investigate eye-based coordination in virtual teams using state-of-the art eye-tracking technology. The project will be interdisciplinary and combine insights from economics, management, information systems, and human computer interaction.
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TOPIC: USING EVERYDAY LIFE AUDIO SIGNALS TO GENERATE AUTOMATED MOOD ASSESSMENTS FOR ADAPTIVE SYSTEMS
Whereas decision making is a frequent everyday life task, its scientific investigation is mainly done in lab studies. However, progress in mobile technology in recent years enables studying such processes in daily life, using digital phenotyping, smartphone technology and wearables. This dissertation project will focus on affect, one of the most central determinants of adaptive systems. Leveraging recent developments from affective computing, we will extract sentiment and voice features of spoken language from daily life assessments as input for adaptive systems. We will partly focus on mental health populations to achieve maximum differences in experienced affect in everyday life.
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TOPIC: USER-ADAPTIVE COLLABORATION SYSTEMS
In this project, we investigate the design of user-adaptive collaboration systems that aim to reduce the cognitive load and fatigue of virtual team members. We will first leverage multimodal biosignal data as well as supervised machine learning to train a classifier that is able to recognize corresponding states of virtual team members. Second, different adaptation strategies are designed and their impact on the virtual team member’s mental load and fatigue as well as individual and team performance will be explored through experimental studies.
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TOPIC: USING EVERYDAY LIFE AUDIO SIGNALS TO GENERATE AUTOMATED MOOD ASSESSMENTS FOR ADAPTIVE SYSTEMS
Whereas decision making is a frequent everyday life task, its scientific investigation is mainly done in lab studies. However, progress in mobile technology in recent years enables studying such processes in daily life, using digital phenotyping, smartphone technology and wearables. This dissertation project will focus on affect, one of the most central determinants of adaptive systems. Leveraging recent developments from affective computing, we will extract sentiment and voice features of spoken language from daily life assessments as input for adaptive systems. We will partly focus on mental health populations to achieve maximum differences in experienced affect in everyday life.
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TOPIC: PROVIDING INFORMATION IN ADAPTIVE COGNITIVE ASSISTANCE SYSTEMS FOR VR SHOPPING
Soon we might go shopping in virtual realities (VR). Intelligent systems that assist the consumers during their shopping process is a development that is particular useful in VR settings because eye-tracking is (or will soon be) an integral part of VR-technology and has been found to reveal a lot of information on the consumer’s decision process. The dissertation projects‘ goal is the design of a system that is able to adapt to the user's needs by measuring the degree of individual attention through eye-tracking and to provide the required product information at exactly the desired time with an optimal degree of complexity. The designed and implemented system will be evaluated in experiments at the DecIS-Lab in Gießen. This thesis is connected to and provides a use case for the thesis economic adaption.
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TOPIC: KD²SCHOOL AR/VR – LAB-LINKING IN VIRTUAL REALITY
This project will virtually interconnect the KD²School labs, i.e. KD²Lab, CSL, fMRI and DecIS labs. This task of “linking labs” is not limited to the technical or technological aspect but includes methodological and content-related contributions to multimodal cross-site experimental research. The KD²School considers LabLinking a crucial educational and experimental element which offers unique opportunities which would not arise without the establishment of the Research Training Group.
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