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Congratulations to Xiaoyun Yin, PhD student at Human Systems Engineering Arizona State University, for winning the 2026 Dieter W. Jahns Student Award.  Dr. Jamie Gorman is Xiaoyun’s major professor. The award and check will be presented to Xiaoyun during the 2026 Aspire Human Factors and Ergonomics Society meeting in Reno, Nevada.  A second $1,000 check will be sent to Professor Gorman.  Xiaoyun stated “I am deeply honored to receive the 2026 Dieter W. Jahns Student Award, and I am very grateful to … the Directors of the Foundation for Professional Ergonomics for this recognition … “

Xiaoyun’s project, Trust and Distrust Spreading in Interconnected Human–AI Teams: An Ergonomics Approach to Analyzing, Designing, and Evaluating Multi-Team Collaboration with AI Agents investigated the mechanisms of trust and distrust spreading in a Team of Teams structure where two human–AI teams worked together on simulated reconnaissance missions. The goal was to understand how manipulating trust or distrust toward one AI agent in one team affects trust attitudes, coordination patterns, and performance not just within that team but also across teams that only interact through communication channels.

Xiaoyun Yin – winner of the 2026 Dieter W. Jahns Student Award.

The laboratory study was designed to capture the co re dynamics of this applied problem in a controlled setting, so that the findings could be translated into design recommendations for real multi-team AI deployments. The design principles, theories, and evaluation methods were chosen specifically to ensure this translation from lab to field. This study demonstrates the full ergonomics practice cycle applied to a pressing challenge in human–AI teaming. 

The trust/distrust manipulation successfully altered trust attitudes. The trust effect was 1.45 for Team A (direct manipulation) and 0.47 for Team B (communication only). The contagion ratio was 0.32, meaning about 32% of the trust/distrust effect transferred across teams through communication alone. Not all trust measures detected the manipulation equally. Cognitive Trust (McAllister, 1995) was the most sensitive, showing a large Condition effect for Team A members rating AVO-A and a large Condition × Mission interaction. There was a difference across teams, meaning the manipulation affected system-level trust perceptions even for the non-manipulated team. This is important for practitioners:  different trust measures capture different aspects, and the choice of measure affects what you can detect.

Sensitivity of Trust Measures to Experimental Manipulation (Partial Eta Squared)

Note. ** p < .01, * p < .05. C × M = Condition × Mission interaction.

The most practically important finding was the dissociation between behavioral coordination and self-reported trust. The manipulation significantly affected trust ratings but did not significantly alter patterns. Even when people reported lower trust, their actual behavioral coordination did not change. For practitioners, this means that survey-based trust monitoring alone will miss whether teams are actually changing their behavior in response to trust concerns. Even more striking: in the Distrust condition, maintaining high trust in the unreliable AI was associated with worse performance. Over-reliance on a malfunctioning AI is an active performance liability, not just a theoretical concern.

Click here for Xiaoyun’s project write-up.

Runner Up

• Puspendu Adhikari, Soham Mohanty, Kashika Chawla, and Tanishka Chavan, Indian Institute of Technology; Oxyquiz: Design of a Board Game to Reinforce Oxygen Gas Cylinder Handling Knowledge; Professor Vivek Kant was the advisor. Click here for Puspendu’s project write-up.

 Previous winners include: 

• 2025: Atif Mohammed Ashraf, Texas A&M University
• 2024:  Zahra Vahedi, Mohammad Shakiba, and Setareh Kazemi Kheiri, SUNY Buffalo, New York
• 2023:  Guoyang Zhou, Purdue University, Indiana
• 2022:  Siobhan Merriman, University of South Hampton, United Kingdom
• 2021:  Anita Ney and Lillian Lacey (coauthors), University of Cincinnati and Bhawana Rathore National Institute of Industrial Engineering Mumbai, India
• 2020:  Sara Wolf and Franzisca Maas, Institute Human-Computer-Media, Julius-Maximilians-Universität Würzburg, Germany
• 2019:  Husam Muslim, University of Tsukuba, Japan
• 2018:  Paul Schlosser, Institute Human-Computer-Media, Julius-Maximilians- Universität Würzburg, Germany
• 2017:  Carly Warren, Abeera Ali, David Gafni, Daipayan Guha, Mayan Murray, and Hendrik Ophardt, University of Toronto
• 2016:  Hyungil Kim, Virginia Polytechnic Institute and State University
• 2015:  Moritz Albert, Daniel Reinhardt, and Ann-Kathrin Kraft Institute Human-Computer-Media, Julius-Maximilians-Universität Würzburg,
• 2014:  Denny Yu, University of Michigan
• 2013:  Kapil Chalil Madathil, Clemson University
• 2012:  Mohd Nasrull Abdol Rahman, Universiti Teknologi Malaysia
• 2011:  Radin Umar, Ohio State University
• 2010:  Augusto Espinosa, Embry-Riddle Aeronautical University