Ensuring training safety is paramount to flight schools. In response to the inadequacy of traditional flight training assessment for comprehensive quantitative evaluation of cadet competency, an initial flight training competency assessment standard based on behavioral indicators was developed and optimized using the VENN model. Firstly, the Assessor Score Measurement Form (ASMF) was constructed according to the requirements of the Training Evaluation Worksheet specification, such as typical subjects, observations, and completion criteria. Secondly, based on the basic principles of the experience of the flight expert and the Competency-Based Training and Assessment (CBTA), a matrix of correlations between the observations and each competency-based behavioral indicator was created to construct a competency assessment matrix. In addition, a two-dimensional model for representing competency items characterized by behavioral indicators was established and an optimization model for competency assessment criteria was constructed. Finally, through combining actual flight training data, the proposed method was validated in the flight screening check phase. The results show that the optimized flight training competency assessment scheme can be well quantified and matched to real instructor ratings with an accuracy of 84%. The assessment worksheet, the assessment matrix, and the VENN competency rating model can be adapted to the different teaching requirements of each flight phase, achieving a perfect match between the behavioral indicators and the competency items, which is highly versatile. The proposed model can more accurately reflect the core competencies of flight trainees, enable quantitative assessment of behavioral indicators and competency items, and provide support for subsequent training of trainees.

Due to the unavoidable operational risks and insufficient risk management capabilities of beginner pilots in flight training, the challenge of risk control in aviation schools has become increasingly prominent. To ensure the safety of flight training in aviation schools and to reduce costs and increase revenue, the essential prerequisite for improving efficiency is risk management. Therefore, it is necessary to explore risk identification and assessment methods. This paper adopts the holographic modeling (HHM) method and risk filtering, rating and management (RFRM) theory. First, the HHM idea is used to construct a risk identification framework (HHM-PAVE) for flight training. Second, based on the dual criteria, multiple criteria and cloud model (CM) in the RFRM approach, an improved risk assessment matrix-cloud model (IPC-CM) is proposed and combined with the N-K model and Bayes’ theorem to propose a coupled risk scenario hazard measurement model (CR-HM) based on the HHM-RFRM approach in risk assessment. In the assessment process, the impact of risk factors on system stability as well as the uncertainty problem and coupling–risk quantification problem in expert assessment are considered to obtain scientific and objective quantitative assessment results. Finally, the risk identification and assessment experiments were conducted using HHM-RFRM on the flight training. The results show that the method can more accurately identify critical risk factors in a flight training system and provide a new perspective for risk prevention and control.