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。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3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地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。

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. A novel mathematical model based on the VENN model was introduced to evaluate behavioral indicators displayed during flight training across three dimensions: quantity, frequency, and the outcomes of threat and error management. Transforming the examination of subjects in flight training into a quantitative evaluation of abilities, and combining historical inspection work sheet data, an optimization method for competency evaluation standards was proposed. Finally, the effectiveness of the proposed method was validated using an actual manual flight control skill evaluation as an example. 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.