Description
Data Analysis Workflows (DAWs) undergo a step-by-step development process that involves continuous testing and re-implementation. While this process allows for early error detection and optimization, it is resource-intensive. The goal of this project is to extend existing workflow definition languages by DAW interfaces, investigate user interaction preferences when DAWs prompt user interaction, and conduct empirical user studies to assess user performance when using DAW interfaces.
Scientists
- Christopher Katins
- Christopher Lazik
Publications
2025
Shen, Chenxinran; Karpus, Jurgis; Kosch, Thomas; Fernandes, Daniela; Mello, Beatriz; Welsch, Robin; Villa, Steeven
The Impact of Asymmetric AI Assistance on Decision-Making in Social Dilemmas: A Study on Human Augmentation in Economic Games Proceedings Article
In: Proceedings of the Augmented Humans International Conference 2025, ACM, New York, NY, USA, 2025.
@inproceedings{shen2025the,
title = {The Impact of Asymmetric AI Assistance on Decision-Making in Social Dilemmas: A Study on Human Augmentation in Economic Games},
author = { Chenxinran Shen and Jurgis Karpus and Thomas Kosch and Daniela Fernandes and Beatriz Mello and Robin Welsch and Steeven Villa},
year = {2025},
date = {2025-01-01},
urldate = {2025-01-01},
booktitle = {Proceedings of the Augmented Humans International Conference 2025},
publisher = {ACM},
address = {New York, NY, USA},
series = {AHs ’25},
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pubstate = {published},
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Krauß, Veronika; McGill, Mark; Kosch, Thomas; Thiel, Yolanda Maira; Schön, Dominik; Gugenheimer, Jan
"Create a Fear of Missing Out" - ChatGPT Implements Unsolicited Deceptive Designs in Generated Websites Without Warning Proceedings Article
In: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery, New York, NY, USA, 2025, ISBN: 9798400713941.
@inproceedings{krauss2025create,
title = {"Create a Fear of Missing Out" - ChatGPT Implements Unsolicited Deceptive Designs in Generated Websites Without Warning},
author = { Veronika Krauß and Mark McGill and Thomas Kosch and Yolanda Maira Thiel and Dominik Schön and Jan Gugenheimer},
url = {https://doi.org/10.1145/3706598.3713083},
doi = {10.1145/3706598.3713083},
isbn = {9798400713941},
year = {2025},
date = {2025-01-01},
urldate = {2025-01-01},
booktitle = {Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
series = {CHI '25},
abstract = {With the recent advancements in Large Language Models (LLMs), web developers increasingly apply their code-generation capabilities to website design. However, since these models are trained on existing designerly knowledge, they may inadvertently replicate bad or even illegal practices, especially deceptive designs (DD). This paper examines whether users can accidentally create DD for a fictitious webshop using GPT-4. We recruited 20 participants, asking them to use ChatGPT to generate functionalities (product overview or checkout) and then modify these using neutral prompts to meet a business goal (e.g., “increase the likelihood of us selling our product”). We found that all 20 generated websites contained at least one DD pattern (mean: 5, max: 9), with GPT-4 providing no warnings. When reflecting on the designs, only 4 participants expressed concerns, while most considered the outcomes satisfactory and not morally problematic, despite the potential ethical and legal implications for end-users and those adopting ChatGPT’s recommendations.},
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pubstate = {published},
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With the recent advancements in Large Language Models (LLMs), web developers increasingly apply their code-generation capabilities to website design. However, since these models are trained on existing designerly knowledge, they may inadvertently replicate bad or even illegal practices, especially deceptive designs (DD). This paper examines whether users can accidentally create DD for a fictitious webshop using GPT-4. We recruited 20 participants, asking them to use ChatGPT to generate functionalities (product overview or checkout) and then modify these using neutral prompts to meet a business goal (e.g., “increase the likelihood of us selling our product”). We found that all 20 generated websites contained at least one DD pattern (mean: 5, max: 9), with GPT-4 providing no warnings. When reflecting on the designs, only 4 participants expressed concerns, while most considered the outcomes satisfactory and not morally problematic, despite the potential ethical and legal implications for end-users and those adopting ChatGPT’s recommendations.
Katins, Christopher; Strecker, Jannis; Hinrichs, Jan; Knierim, Pascal; Pfleging, Bastian; Kosch, Thomas
Ad-Blocked Reality: Evaluating User Perceptions of Content Blocking Concepts Using Extended Reality Proceedings Article
In: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery, New York, NY, USA, 2025, ISBN: 9798400713941.
@inproceedings{katins2025adblocked,
title = {Ad-Blocked Reality: Evaluating User Perceptions of Content Blocking Concepts Using Extended Reality},
author = { Christopher Katins and Jannis Strecker and Jan Hinrichs and Pascal Knierim and Bastian Pfleging and Thomas Kosch},
url = {https://doi.org/10.1145/3706598.3713230},
doi = {10.1145/3706598.3713230},
isbn = {9798400713941},
year = {2025},
date = {2025-01-01},
urldate = {2025-01-01},
booktitle = {Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
series = {CHI '25},
abstract = {Inspired by the concepts of diminishing reality and ad-blocking in browsers, this study investigates the perceived benefits and concerns of blocking physical, real-world content, particularly ads, through Extended Reality (XR). To understand how users perceive this concept, we first conducted a user study (N = 18) with an ad-blocking prototype to gather initial insights. The results revealed a mixed willingness to adopt XR blockers, with participants appreciating aspects such as customizability, convenience, and privacy. Expected benefits included enhanced focus and reduced stress, while concerns centered on missing important information and increased feelings of isolation. Hence, we investigated the user acceptance of different ad-blocking visualizations through a follow-up online survey (N = 120), comparing six concepts based on related work. The results indicated that the XR ad-blocker visualizations play a significant role in how and for what kinds of advertisements such a concept might be used, paving the path for future feedback-driven prototyping.},
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pubstate = {published},
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Inspired by the concepts of diminishing reality and ad-blocking in browsers, this study investigates the perceived benefits and concerns of blocking physical, real-world content, particularly ads, through Extended Reality (XR). To understand how users perceive this concept, we first conducted a user study (N = 18) with an ad-blocking prototype to gather initial insights. The results revealed a mixed willingness to adopt XR blockers, with participants appreciating aspects such as customizability, convenience, and privacy. Expected benefits included enhanced focus and reduced stress, while concerns centered on missing important information and increased feelings of isolation. Hence, we investigated the user acceptance of different ad-blocking visualizations through a follow-up online survey (N = 120), comparing six concepts based on related work. The results indicated that the XR ad-blocker visualizations play a significant role in how and for what kinds of advertisements such a concept might be used, paving the path for future feedback-driven prototyping.
Krämer, Thomas; Hienert, Daniel; Chiossi, Francesco; Kosch, Thomas; Kern, Dagmar
Escaping the Filter Bubble: Evaluating Electroencephalographic Theta Band Synchronization as Indicator for Selective Exposure in Online News Reading Proceedings Article
In: Extended Abstracts of the 2025 CHI Conference on Human Factors in Computing Systems, ACM, New York, NY, USA, 2025, ISBN: 979-8-4007-1394-1/25/04.
@inproceedings{kraemer2025escaping,
title = {Escaping the Filter Bubble: Evaluating Electroencephalographic Theta Band Synchronization as Indicator for Selective Exposure in Online News Reading},
author = { Thomas Krämer and Daniel Hienert and Francesco Chiossi and Thomas Kosch and Dagmar Kern},
doi = {10.1145/3706599.3720078},
isbn = {979-8-4007-1394-1/25/04},
year = {2025},
date = {2025-01-01},
urldate = {2025-01-01},
booktitle = {Extended Abstracts of the 2025 CHI Conference on Human Factors in Computing Systems},
publisher = {ACM},
address = {New York, NY, USA},
series = {CHI EA '25},
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pubstate = {published},
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Windl, Maximiliane; Amberg, Roman; Kosch, Thomas
The Illusion of Privacy: Investigating User Misperceptions in Browser Tracking Protection Proceedings Article
In: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery, New York, NY, USA, 2025, ISBN: 9798400713941.
@inproceedings{windl2025illusion,
title = {The Illusion of Privacy: Investigating User Misperceptions in Browser Tracking Protection},
author = { Maximiliane Windl and Roman Amberg and Thomas Kosch},
url = {https://doi.org/10.1145/3706598.3713912},
doi = {10.1145/3706598.3713912},
isbn = {9798400713941},
year = {2025},
date = {2025-01-01},
urldate = {2025-01-01},
booktitle = {Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
series = {CHI '25},
abstract = {Third parties track users’ web browsing activities, raising privacy concerns. Tracking protection extensions prevent this, but their influence on privacy protection beliefs shaped by narratives remains uncertain. This paper investigates users’ misperception of tracking protection offered by browser plugins. Our study explores how different narratives influence users’ perceived privacy protection by examining three tracking protection extension narratives: no protection, functional protection, and a placebo. In a study (N=36), participants evaluated their anticipated protection during a hotel booking process, influenced by the narrative about the plugin’s functionality. However, participants viewed the same website without tracking protection adaptations. We show that users feel more protected when informed they use a functional or placebo extension, compared to no protection. Our findings highlight the deceptive nature of misleading privacy tools, emphasizing the need for greater transparency to prevent users from a false sense of protection, as such misleading tools negatively affect user study results.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Third parties track users’ web browsing activities, raising privacy concerns. Tracking protection extensions prevent this, but their influence on privacy protection beliefs shaped by narratives remains uncertain. This paper investigates users’ misperception of tracking protection offered by browser plugins. Our study explores how different narratives influence users’ perceived privacy protection by examining three tracking protection extension narratives: no protection, functional protection, and a placebo. In a study (N=36), participants evaluated their anticipated protection during a hotel booking process, influenced by the narrative about the plugin’s functionality. However, participants viewed the same website without tracking protection adaptations. We show that users feel more protected when informed they use a functional or placebo extension, compared to no protection. Our findings highlight the deceptive nature of misleading privacy tools, emphasizing the need for greater transparency to prevent users from a false sense of protection, as such misleading tools negatively affect user study results.
Villa, Steeven; Krammer, Finn Jacob Eliyah; Weiss, Yannick; Welsch, Robin; Kosch, Thomas
Understanding the Influence of Electrical Muscle Stimulation on Motor Learning: Enhancing Motor Learning or Disrupting Natural Progression? Proceedings Article
In: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery, New York, NY, USA, 2025, ISBN: 9798400713941.
@inproceedings{villa2025understanding,
title = {Understanding the Influence of Electrical Muscle Stimulation on Motor Learning: Enhancing Motor Learning or Disrupting Natural Progression?},
author = { Steeven Villa and Finn Jacob Eliyah Krammer and Yannick Weiss and Robin Welsch and Thomas Kosch},
url = {https://doi.org/10.1145/3706598.3714183},
doi = {10.1145/3706598.3714183},
isbn = {9798400713941},
year = {2025},
date = {2025-01-01},
urldate = {2025-01-01},
booktitle = {Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
series = {CHI '25},
abstract = {Electrical Muscle Stimulation (EMS) induces muscle movement through external currents, offering a novel approach to motor learning. Researchers investigated using EMS as an alternative to conventional non-movement-inducing feedback techniques, such as vibrotactile and electrotactile feedback. While EMS shows promise in areas such as dance, sports, and motor skill acquisition, neurophysiological models of motor learning conflict about the impact of externally induced movements on sensorimotor representations. This study evaluated EMS against electrotactile feedback and a control condition in a two-session experiment assessing fast learning, consolidation, and learning transfer. Our results suggest an overall positive impact of EMS in motor learning. Although traditional electrotactile feedback had a higher learning rate, EMS increased the learning plateau, as measured by a three-factor exponential decay model. This study provides empirical evidence supporting EMS as a plausible method for motor augmentation and skill transfer, contributing to understanding its role in motor learning.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
Electrical Muscle Stimulation (EMS) induces muscle movement through external currents, offering a novel approach to motor learning. Researchers investigated using EMS as an alternative to conventional non-movement-inducing feedback techniques, such as vibrotactile and electrotactile feedback. While EMS shows promise in areas such as dance, sports, and motor skill acquisition, neurophysiological models of motor learning conflict about the impact of externally induced movements on sensorimotor representations. This study evaluated EMS against electrotactile feedback and a control condition in a two-session experiment assessing fast learning, consolidation, and learning transfer. Our results suggest an overall positive impact of EMS in motor learning. Although traditional electrotactile feedback had a higher learning rate, EMS increased the learning plateau, as measured by a three-factor exponential decay model. This study provides empirical evidence supporting EMS as a plausible method for motor augmentation and skill transfer, contributing to understanding its role in motor learning.
2024
Kosch, Thomas; Feger, Sebastian
Risk or Chance? Large Language Models and Reproducibility in HCI Research Journal Article
In: Interactions, vol. 31, no. 6, pp. 44–49, 2024, ISSN: 1072-5520.
@article{kosch2024risk,
title = {Risk or Chance? Large Language Models and Reproducibility in HCI Research},
author = { Thomas Kosch and Sebastian Feger},
url = {https://doi.org/10.1145/3695765},
doi = {10.1145/3695765},
issn = {1072-5520},
year = {2024},
date = {2024-10-01},
urldate = {2024-10-01},
journal = {Interactions},
volume = {31},
number = {6},
pages = {44–49},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Sänger, Mario; Mecquenem, Ninon De; Lewińska, Katarzyna Ewa; Bountris, Vasilis; Lehmann, Fabian; Leser, Ulf; Kosch, Thomas
A Qualitative Assessment of Using ChatGPT as Large Language Model for Scientific Workflow Development Journal Article
In: GigaScience, 2024, ISSN: 2047-217X.
@article{saenger2024a,
title = {A Qualitative Assessment of Using ChatGPT as Large Language Model for Scientific Workflow Development},
author = { Mario Sänger and Ninon De Mecquenem and Katarzyna Ewa Lewińska and Vasilis Bountris and Fabian Lehmann and Ulf Leser and Thomas Kosch},
url = {https://doi.org/10.1093/gigascience/giae030},
doi = {10.1093/gigascience/giae030},
issn = {2047-217X},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
journal = {GigaScience},
abstract = {Scientific workflow systems are increasingly popular for expressing and executing complex data analysis pipelines over large datasets, as they offer reproducibility, dependability, and scalability of analyses by automatic parallelization on large compute clusters. However, implementing workflows is difficult due to the involvement of many black-box tools and the deep infrastructure stack necessary for their execution. Simultaneously, user-supporting tools are rare, and the number of available examples is much lower than in classical programming languages.To address these challenges, we investigate the efficiency of large language models (LLMs), specifically ChatGPT, to support users when dealing with scientific workflows. We performed 3 user studies in 2 scientific domains to evaluate ChatGPT for comprehending, adapting, and extending workflows. Our results indicate that LLMs efficiently interpret workflows but achieve lower performance for exchanging components or purposeful workflow extensions. We characterize their limitations in these challenging scenarios and suggest future research directions.Our results show a high accuracy for comprehending and explaining scientific workflows while achieving a reduced performance for modifying and extending workflow descriptions. These findings clearly illustrate the need for further research in this area.},
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pubstate = {published},
tppubtype = {article}
}
Scientific workflow systems are increasingly popular for expressing and executing complex data analysis pipelines over large datasets, as they offer reproducibility, dependability, and scalability of analyses by automatic parallelization on large compute clusters. However, implementing workflows is difficult due to the involvement of many black-box tools and the deep infrastructure stack necessary for their execution. Simultaneously, user-supporting tools are rare, and the number of available examples is much lower than in classical programming languages.To address these challenges, we investigate the efficiency of large language models (LLMs), specifically ChatGPT, to support users when dealing with scientific workflows. We performed 3 user studies in 2 scientific domains to evaluate ChatGPT for comprehending, adapting, and extending workflows. Our results indicate that LLMs efficiently interpret workflows but achieve lower performance for exchanging components or purposeful workflow extensions. We characterize their limitations in these challenging scenarios and suggest future research directions.Our results show a high accuracy for comprehending and explaining scientific workflows while achieving a reduced performance for modifying and extending workflow descriptions. These findings clearly illustrate the need for further research in this area.
Rodrigues, Lucas Siqueira; Nyakatura, John; Zachow, Stefan; Israel, Johann Habakuk; Kosch, Thomas
Evaluating Visuohaptic Integration on Memory Retention of Morphological Tomographic Images Proceedings Article
In: Proceedings of the 19th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry, ACM 2024.
@inproceedings{rodrigues2024evaluating,
title = {Evaluating Visuohaptic Integration on Memory Retention of Morphological Tomographic Images},
author = { Lucas Siqueira Rodrigues and John Nyakatura and Stefan Zachow and Johann Habakuk Israel and Thomas Kosch},
doi = {10.1145/3703619.3706055},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
booktitle = {Proceedings of the 19th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry},
organization = {ACM},
keywords = {},
pubstate = {published},
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Chiossi, Francesco; Weiss, Yannick; Steinbrecher, Thomas; Mai, Christian; Kosch, Thomas
Mind the Visual Discomfort: Assessing Event-Related Potentials as Indicators for Visual Strain in Head-Mounted Displays Proceedings Article
In: 2024 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), IEEE, New York, NY, USA, 2024.
@inproceedings{chiossi2024mind,
title = {Mind the Visual Discomfort: Assessing Event-Related Potentials as Indicators for Visual Strain in Head-Mounted Displays},
author = { Francesco Chiossi and Yannick Weiss and Thomas Steinbrecher and Christian Mai and Thomas Kosch},
doi = {10.48550/arXiv.2407.18548},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
booktitle = {2024 IEEE International Symposium on Mixed and Augmented Reality (ISMAR)},
publisher = {IEEE},
address = {New York, NY, USA},
keywords = {},
pubstate = {published},
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}