Measuring cognitive abilities in flight personnel:developments and challenges
YANG Liu
WANG Chao
GUO Xiaochao
Abstract：The cognitive abilities of flight personnel constitute the critical psychological foundation for ensuring flight safety and mission effectiveness.With the rapid advancement of aviation equipment and the increasingly complex operational environment,the demand for assessing pilots'cognitive abilities has shifted from traditional macro-level ability ranking to the fine-grained diagnosis of micro-level cognitive structures and their processing mechanisms.This paper systematically reviews the developmental trajectory and current practices of pilot cognitive ability measurement technologies both domestically and internationally.It traces the evolution from early methods based on paper-and-pencil tests,instrument-based examinations,and expert observation to the current diversified system that integrates computerized assessment,simulator evaluation,and cognitive neuroscience technologies.On this basis,it analyzes the achievements and limitations within the frameworks of classical test theory and item response theory.In response to the heightened requirements for human-machine system cognitive compatibility posed by high-performance fighter aircraft,traditional assessment paradigms exhibit a theoretical gap in achieving systematic diagnostic analysis of ability structures.Cognitive diagnosis theory(CDT),with its unique advantage in deconstructing cognitive attributes and processing mechanisms within specific tasks,offers a new paradigm for the precise assessment of pilots'cognitive abilities.Furthermore,drawing on preliminary explorations,this paper summarizes the core challenges encountered when applying CDT to the aviation field across three dimensions:data transformation,population adaptation,and model construction.Finally,it outlines future pathways for constructing a next-generation pilot cognitive diagnosis and predictive safety system,focusing on four key directions:intelligent data coding,adaptive models for high-ability populations,hybrid attribute model development,and a multi-source information fusion framework.
Keywords：flight personnelcognitive abilitiespsychological selectioncognitive diagnosismeasurement technologyassessment modelmulti-source information fusionhuman-machine system
Publication Date：2026-03-31
Online Publishing Date：2026-08-26(First online date of this platform, not the publication date of the document)
Pages：9( 318-326 )