Is this project an undergraduate, graduate, or faculty project?
Undergraduate
Project Type
group
Campus
Daytona Beach
Authors' Class Standing
Tsumir Babakhanau, Senior Noah Clark Colby Keller Mary Grace Sorenson Zoe Tiede
Lead Presenter's Name
Tsimur Babakhanau
Lead Presenter's College
DB College of Arts and Sciences
Faculty Mentor Name
Barbara Chaparro
Abstract
This study implements a detailed naval scenario in which participants acted as operators on a Navy destroyer equipped with a Laser Weapon System (LaWS). Their task was to create a dashboard capable of stopping incoming suicide drone swarms while managing critical laser functions such as thermal constraints, threat prioritization, and adapting to attack dynamics. Poor management could leave the ship vulnerable. AI is increasingly integrated into design methods, fundamentally transforming the process of building user interfaces by compressing hours of work into minutes. Although AI design tools are becoming more common, little is known about how well beginners can use these systems in terms of time, quality, and task performance. A convenience sample of 31 students was randomly assigned to either a manual condition (paper and pencil or Figma) or an AI-assisted condition (Figma Make, Claude, or DeepSeek), with 50 minutes to complete their interface. Completion time was recorded, and participants completed a post-task survey measuring perceived performance, ease, and confidence. Both design mediums were analyzed through the maintenance of key elements, military standards, and human factor principles. Preliminary survey responses indicate that AI-assisted tools facilitated quicker idea generation and outcomes relative to manual methods, which required participants to invest significantly more time in repetitive tasks. However, AI users often felt limited in their creativity, indicating that while they were more productive, their success sometimes came with drawbacks such as stifled thoughts and a lack of personal expression. These findings have implications for integrating AI tools into novice design workflows and may inform future research on the relationship between tool type, creativity, and design outcomes.
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
No
Included in
Computer and Systems Architecture Commons, Operational Research Commons, Systems Science Commons
Designing Under Pressure: A Comparative Study of AI and Manual Interface Development in a Naval Weapon System Scenario
This study implements a detailed naval scenario in which participants acted as operators on a Navy destroyer equipped with a Laser Weapon System (LaWS). Their task was to create a dashboard capable of stopping incoming suicide drone swarms while managing critical laser functions such as thermal constraints, threat prioritization, and adapting to attack dynamics. Poor management could leave the ship vulnerable. AI is increasingly integrated into design methods, fundamentally transforming the process of building user interfaces by compressing hours of work into minutes. Although AI design tools are becoming more common, little is known about how well beginners can use these systems in terms of time, quality, and task performance. A convenience sample of 31 students was randomly assigned to either a manual condition (paper and pencil or Figma) or an AI-assisted condition (Figma Make, Claude, or DeepSeek), with 50 minutes to complete their interface. Completion time was recorded, and participants completed a post-task survey measuring perceived performance, ease, and confidence. Both design mediums were analyzed through the maintenance of key elements, military standards, and human factor principles. Preliminary survey responses indicate that AI-assisted tools facilitated quicker idea generation and outcomes relative to manual methods, which required participants to invest significantly more time in repetitive tasks. However, AI users often felt limited in their creativity, indicating that while they were more productive, their success sometimes came with drawbacks such as stifled thoughts and a lack of personal expression. These findings have implications for integrating AI tools into novice design workflows and may inform future research on the relationship between tool type, creativity, and design outcomes.