C3: User Centered Design for Data Analysis Workflow Languages

@article{fernandes2025ai,

title = {AI makes you smarter but none the wiser: The disconnect between performance and metacognition},

author = {Daniela Fernandes and Steeven Villa and Salla Nicholls and Otso Haavisto and Daniel Buschek and Albrecht Schmidt and Thomas Kosch and Chenxinran Shen and Robin Welsch},

url = {https://www.sciencedirect.com/science/article/pii/S0747563225002262},

doi = {https://doi.org/10.1016/j.chb.2025.108779},

issn = {0747-5632},

year  = {2026},

date = {2026-10-27},

urldate = {2026-02-01},

journal = {Computers in Human Behavior},

volume = {175},

pages = {108779},

abstract = {Optimizing human–AI interaction requires users to reflect on their performance critically, yet little is known about generative AI systems’ effect on users’ metacognitive judgments. In two large-scale studies, we investigate how AI usage is associated with users’ metacognitive monitoring and performance in logical reasoning tasks. Specifically, our paper examines whether people using AI to complete tasks can accurately monitor how well they perform. In Study 1, participants (N = 246) used AI to solve 20 logical reasoning problems from the Law School Admission Test. While their task performance improved by three points compared to a norm population, participants overestimated their task performance by four points. Interestingly, higher AI literacy correlated with lower metacognitive accuracy, suggesting that those with more technical knowledge of AI were more confident but less precise in judging their own performance. Using a computational model, we explored individual differences in metacognitive accuracy and found that the Dunning–Kruger effect, usually observed in this task, ceased to exist with AI use. Study 2 (N = 452) replicates these findings. We discuss how AI levels cognitive and metacognitive performance in human–AI interaction and consider the consequences of performance overestimation for designing interactive AI systems that foster accurate self-monitoring, avoid overreliance, and enhance cognitive performance.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{10.3389/frvir.2025.1645330,

title = {Shaping the future: principles for policy recommendations for responsible innovation in virtual worlds},

author = {Alicia G. Cork and Mike Richardson and Heide K. Lukosch and Mohamed Khamis and Christopher Katins and Veronika Krauβ and Lauren Ruffin and Sarah Papazoglakis and Victoria Sanchez and Xueni Pan and Michael J. Proulx and Danaë Stanton Fraser},

url = {https://www.frontiersin.org/journals/virtual-reality/articles/10.3389/frvir.2025.1645330},

doi = {10.3389/frvir.2025.1645330},

issn = {2673-4192},

year  = {2025},

date = {2025-10-06},

urldate = {2025-01-01},

journal = {Frontiers in Virtual Reality},

volume = {Volume 6 - 2025},

abstract = {Extended Reality (XR) technologies are beginning to enter the mainstream and have the potential to change the way humans interact with computers on a global scale. As with all powerful tools, XR not only has the potential for enormous good, but also brings in a new set of challenges for policy to guide its innovation and development. This paper draws on a wide range of expertise from academia, research and development, and industry to collectively provide guiding principles for XR policy. The authors began discussions and developed a framework at a workshop at ACM SIGCHI 2024 and the ideas presented here are the result of debate, discussion, refinement, and offer next steps for the development of pervasive XR. We present three main principles for XR policy: Trust, Agency, and Inclusivity, along with a cross-cutting theme of Future-Proofing. Each principle is broken down and we offer example implementations. This paper aims to build upon previous work and efforts for fair and equitable XR for all, and further dialogue towards tangible changes in policy to help guide responsible innovation in virtual worlds.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ruecker2025understanding,

title = {Understanding the Effect of Risk Perception on the Acceptance and Use of Large Language Models Among University Students},

author = {Michael T. Rücker and Carolin Büchting and Thomas Kosch},

url = {https://dl.acm.org/doi/abs/10.1145/3757693},

doi = {10.1145/3757693},

year  = {2025},

date = {2025-10-01},

urldate = {2025-10-01},

journal = {Proceedings of the ACM on Human-Computer Interaction},

volume = {9},

number = {CSCW512},

publisher = {New York, NY, USA},

keywords = {},

pubstate = {published},

tppubtype = {article}

}