基于VENN模型的民航飞行员胜任力评估标准优化

传统的飞行训练评估依赖教员的主观评价，且对能力的量化评估标准模糊，难以保证评估的一致性和有效性。本文基于VENN模型对飞行训练中行为指标展现的数量、频次及威胁与差错管理结果三个胜任力特征进行数学建模，将飞行训练中对科目的检查转化为对能力的量化评估，并结合历史检查工作单数据，提出了一种胜任力评估标准优化方法。最后，以实际的手动飞行操纵技能评估为例，验证了提出方法的有效性。测试结果表明：由算法得出的评分标准获得的技能评分与教员经验给出的评级结果显著相关，且评分保持一致的样本占比83.3%，其余样本评分偏差均在1级以内，表明了提出方法能有效的从历史检查单数据中提取对能力的评估标准，为数据驱动的胜任力量化评估标准制定提供了理论支撑及新方法。

VENN model-based competencies assessment criteria optimization for civil aviation pilots

Ensuring consistency and validity in flight training assessment proves challenging due to the traditional reliance on instructors'' subjective evaluations and the imprecise quantitative criteria for competencies. This paper introduces a novel mathematical model based on the VENN model to evaluate behavioral indicators displayed during flight training across three dimensions: quantity, frequency, and the outcomes of threat and error management. This model maps these indicators to a quantified assessment of competencies, and historical checklist data is integrated to propose an optimization method for competency assessment criteria. Actual manual flight maneuver training serves as an example to verify the effectiveness of the proposed method. The results demonstrate a significant correlation between the final assessment criteria derived from the algorithm and the ratings provided by instructors, with 83.3% of the samples exhibiting rating consistency and the remaining samples deviating by no more than one level. This suggests that the proposed method adeptly transforms historical checklist information into assessment criteria for competency, offering theoretical support and a new data-driven approach for formulating competency assessment criteria.