Team signal detection theory: objective team performance measurement using simulation telemetry

Current methods for evaluating team performance rely primarily on simple outcome measures and subjective ratings, which offer limited insight into the decision processes driving performance. This study extends signal detection theory (SDT) to teams, deriving sensitivity (d′) and response bias (c) from simulation telemetry. Twenty three-person teams completed five virtual reality tasks varying in interdependence and time pressure while self-reported workload, conventional and SDT metrics, and verbal communication were collected. Team-level sensitivity distinguished conditions that conventional metrics did not. High time pressure reduced sensitivity relative to baseline before task scores declined, suggesting sensitivity may indicate early performance degradation. Response bias became more conservative under combined high interdependence and time pressure, reflecting team strategy shifts. SDT metrics correlated with workload, particularly team-task balancing demands (rs=−0.68 for d′). Together, sensitivity and bias characterise team performance more completely than accuracy alone by separating discriminative ability from decision strategy.

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Publication Details

Journal
Ergonomics
Published
2026-10-14
DOI
https://doi.org/10.1080/00140139.2026.2740204
Primary Topic
Team Dynamics and Performance
Type
article
Field-Weighted Citation Impact
0.00

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article

Team signal detection theory: objective team performance measurement using simulation telemetry

Gregory J. Funke, Denny Yu, Ryan Thomas Villarreal
Ergonomics
Team Dynamics and Performance
article

Team signal detection theory: objective team performance measurement using simulation telemetry

Gregory J. Funke, Denny Yu, Ryan Thomas Villarreal
article en

Abstract

Current methods for evaluating team performance rely primarily on simple outcome measures and subjective ratings, which offer limited insight into the decision processes driving performance. This study extends signal detection theory (SDT) to teams, deriving sensitivity (d′) and response bias (c) from simulation telemetry. Twenty three-person teams completed five virtual reality tasks varying in interdependence and time pressure while self-reported workload, conventional and SDT metrics, and verbal communication were collected. Team-level sensitivity distinguished conditions that conventional metrics did not. High time pressure reduced sensitivity relative to baseline before task scores declined, suggesting sensitivity may indicate early performance degradation. Response bias became more conservative under combined high interdependence and time pressure, reflecting team strategy shifts. SDT metrics correlated with workload, particularly team-task balancing demands (rs=−0.68 for d′). Together, sensitivity and bias characterise team performance more completely than accuracy alone by separating discriminative ability from decision strategy.

Ergonomics
Purdue University West Lafayette (US), 711th Human Performance Wing
National Science Foundation, Agency for Healthcare Research and Quality, National Science Foundation Graduate Research Fellowship Program
Openalex Percentile: Top 8%
Team Dynamics and Performance
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