Method, system and storage medium for assessing and training personnel performance

Abstract

This invention provides a method, system, and storage medium for assessing and training personnel's operational capabilities. The training method first tests and evaluates the operational capabilities of relevant personnel, then selects the operational capabilities that need improvement based on the test and evaluation results. Next, a targeted training program is established to improve the operators' operational skills. This invention establishes targeted training programs by assessing operators' operational capabilities and adjusts the difficulty of each training task in real time, effectively improving the convenience and effectiveness of personnel operational capability training and accelerating the enhancement of operators' operational abilities. The training device improves the flexibility of the training site through an ergonomically designed operating console, obtains more accurate training data, and, in conjunction with training tasks involving multiple dimensions configured in the training server, achieves multi-dimensional training of personnel's operational capabilities.

Description

Technical Field

[0001] This invention relates to the field of information technology in education and training, and in particular to a method, system, and storage medium for assessing and training personnel's operational skills. Background Technology

[0002] Sensation is the initial cognitive process, a reflection of the individual attributes of objective things by the human brain, and the foundation of complex cognitive activities. When operators work with equipment, they need to receive, distinguish, and judge sensory information from various sources and make corresponding operations. They acquire a large amount of information through their various sensory organs. For example, a driver perceives color, brightness, and obstacles with their eyes; feels the pressure of the steering wheel and levers with their hands and manipulates them or presses function buttons; feels vibrations in the car with their buttocks; presses or lifts the pedals with their feet; and listens to horn sounds and engine noises. Similarly, factory equipment operators observe the operation of equipment with their eyes and listen to whether there are any abnormalities in the sounds of the equipment.

[0003] Operators obtain the vast majority of external information through their senses, with vision accounting for over 80% of all information. Hearing plays a crucial supplementary role to vision; its rapid response and high accuracy can quickly arouse alertness and provide direction for visual identification of specific targets. Therefore, during operation, the level of an operator's visual, auditory, and other sensory abilities directly affects their performance and the smoothness of equipment operation. Based on the various sensory information received, operators need to determine the next action and transform visual, auditory, or other information into a series of countermeasures to ensure the normal and safe operation of the equipment. For example, a driver, upon seeing a traffic light, must decide whether to brake or continue driving normally; upon seeing a vehicle behind them attempting to overtake and hearing its horn, should they steer to the other side? How should they safely avoid pedestrians or vehicles suddenly running out at an intersection? Similarly, equipment operators should make adjustments when they see equipment malfunctions or conduct timely checks upon hearing abnormal sounds during equipment operation.

[0004] Assessing and training operators' skills from their perspective is crucial for preventing and reducing traffic accidents.

[0005] There are many factors affecting operators' operational abilities, including their visual, auditory, coordination, and reaction skills. Simultaneously, there are various training methods for operational abilities. However, existing on-the-spot training methods for operational abilities still have several shortcomings, including: training methods are relatively limited, often relying on computers for one-on-one testing and training, which has significant limitations, such as limitations in long-distance testing, simultaneous testing with multiple participants, and testing environments; training content is limited, focusing primarily on individual operational skills training, such as the nine-horse test, wedge groove, and curved trajectory for drivers, failing to comprehensively reflect the tested driver's operational abilities; the equipment used is inconvenient, mostly using traditional hardware for individual operational skills, making it difficult to conduct assessments and training anytime, anywhere, or for multi-person assessments and training, and it lacks the ability to adjust experimental difficulty and parameter configurations, while data processing and statistics are cumbersome; and there is a lack of scientific testing schemes, with existing training methods mostly lacking scientific training models and processes, and without a systematic training and assessment system, they can only achieve basic training, lack overall logic, and are difficult to achieve effective training results. Summary of the Invention

[0006] In view of this, embodiments of the present invention provide a method, system and storage unit for assessing and training personnel's operational capabilities, in order to eliminate or improve one or more defects existing in the prior art.

[0007] One aspect of the present invention provides a method for assessing and training personnel's operational skills, comprising the following steps:

[0008] The testing steps involve selecting training tasks that match the operational abilities of the participants from multiple training tasks involving various training dimensions, based on the participants' operational capabilities, and configuring the task parameters for each training task. The participants are then tested using each selected training task to obtain their performance results. Based on the performance results for each training task, training tasks that the participants cannot meet are selected and added to their training plan. The performance results for each training task include the indicator data for each task metric. The training steps involve training the participants according to their training plan, focusing on each training task within the plan. The difficulty of the training task in the next training round is adjusted based on the task results in the current training round. In each training round, the subject sequentially executes all training tasks in the training plan, obtaining the task results corresponding to each training task in the current training round, until all training tasks in the subject's training plan are completed through multiple training rounds. In the evaluation step, the subject's operational ability is verified using the training task with the difficulty of the last training round in the training step, and the task results used to display the subject's operational ability after training are obtained. Combined with the task results of each training task in the training step, the training effect of the subject is evaluated.

[0009] In some embodiments of the present invention, the step of adjusting the task difficulty of the training task in the next training round based on the task result of each training task in the current training round includes:

[0010] In the current training round, the indicator data of each task metric obtained by the subject in performing each training task is compared with the corresponding norm result. For a training task with only one task metric, if the indicator data of the task metric is lower than the corresponding norm result, the task difficulty of the training task is reduced; otherwise, the task difficulty of the training task is increased. For a training task with multiple task metrics, if more than half of the task metrics have indicator data lower than the corresponding norm result, the task difficulty of the training task is reduced; otherwise, the task difficulty of the training task is increased. If the number of task metrics with indicator data lower than the corresponding norm result and the number of task metrics with indicator data higher than the corresponding norm result are the same, the difference between the standard score value of each task metric data and 0 is compared. If the difference between the standard score value of the task metrics with indicator data lower than the corresponding norm result and 0 is larger, the task difficulty of the training task is reduced and used as the corresponding training task in the next training round; otherwise, the task difficulty of the training task is increased.

[0011] In some embodiments of the present invention, the step of adjusting the task difficulty of the training task in the next training round based on the task result of each training task in the current training round includes:

[0012] Based on the task parameters and task indicators of each training task in the training steps, the task parameters are used as independent variables and the task indicators are used as dependent variables. A multiple regression model is created for each training task in the training plan. The experimenter selects the task indicators of each training task that the subjects need to achieve in each training stage. Based on the multiple regression model of each training task, multiple sets of task parameters for the training task that meet the current task indicators are calculated. The set of task parameters with the highest difficulty is selected as the task parameters for the training task in the current training round.

[0013] In some embodiments of the present invention, the step of adjusting the task difficulty of the training task in the next training round based on the task result of each training task in the current training round includes:

[0014] Based on the machine learning models of each training task created according to the task parameters and task indicators of each training task in the norm database, the machine learning models of each training task are adjusted in real time according to the task parameters and task difficulty of each training task performed by the subjects in the current training round, and the task parameters of each training task in the next training round are automatically adjusted according to the adjusted machine learning models.

[0015] In some embodiments of the present invention, each training task includes one or more task parameters and one or more task metrics.

[0016] In some embodiments of the present invention, the training task that the subject needs to perform involves multiple training dimensions, and each training dimension includes more than one training task.

[0017] In some embodiments of the present invention, the step of evaluating the training effect of the subject includes: using the task results used to display the subject's operational ability after training and the task results of each training task in each training round of the training step, calculating the standard score value of the indicator data of each task indicator of each training task in the training scheme, and performing a t-test to obtain the evaluation result of the subject's training effect in the training step.

[0018] Another aspect of the present invention provides a system for assessing and training personnel operational skills, characterized in that it includes a processor and a memory, wherein the memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the device implements the steps of any of the above-described assessment and training methods.

[0019] In some embodiments of the present invention, an operating console and a training server are further included; the training server stores multiple training tasks involving various training dimensions for training operators' operational capabilities; the operating console is configured with operating components corresponding to the training tasks in the training server; the operating console is connected to the training server, enabling subjects to execute the corresponding training tasks in the training server by operating the operating components in the operating console.

[0020] Another aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the program is executed by a processor, it implements the steps of any of the above-described evaluation and training methods.

[0021] The technical effects of the present invention regarding a method, system, and storage medium for assessing and training personnel operational skills include: First, the assessment and training method tests and evaluates the operational skills of relevant personnel. Based on the test and evaluation results, it identifies the operational skills that need improvement. Then, it establishes targeted training programs to enhance the operational skills of the personnel. The assessment and training method in this invention establishes targeted training programs by assessing the operational skills of personnel. During the execution of the training programs, it combines the training method with the ability to freely adjust parameter configurations, real-time adjusting the difficulty of each training task, effectively improving the convenience and effectiveness of personnel operational skill training, and accelerating the enhancement of operational skills. Furthermore, based on various training tasks involving multiple dimensions, from simple to complex, and from basic to advanced dimensions, it achieves multi-dimensional training of personnel operational skills, overcoming the problem of single training methods. The training and assessment system in this invention improves the flexibility of the training site through an operating console that conforms to ergonomic principles, obtains more accurate training data, and, in conjunction with training tasks involving multiple dimensions configured in the training server, achieves multi-dimensional training of personnel operational skills.

[0022] Additional advantages, objects, and features of the invention will be set forth in part in the description which follows, and will also become apparent in part to those skilled in the art upon studying the description, or may be learned by practice of the invention. The objects and other advantages of the invention can be realized and obtained by means of the structures specifically pointed out in the description and drawings.

[0023] Those skilled in the art will understand that the objectives and advantages achievable with the present invention are not limited to those specifically described above, and that the above and other objectives achievable with the present invention will become clearer from the following detailed description. Attached Figure Description

[0024] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, are not intended to limit the scope of the invention. The components in the drawings are not drawn to scale but are merely illustrative of the principles of the invention. For ease of illustration and description of certain parts of the invention, corresponding portions in the drawings may be enlarged, i.e., may appear larger relative to other components in an exemplary device actually manufactured according to the invention. In the drawings:

[0025] Figure 1 A flowchart for training operators' operational skills;

[0026] Figure 2 A schematic diagram of a training device for operators' operational skills;

[0027] Figure 3 This is a schematic diagram of the operation panel of the training device in the embodiment. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the embodiments and accompanying drawings. Here, the illustrative embodiments and descriptions of this invention are used to explain the invention, but are not intended to limit the invention.

[0029] It should also be noted that, in order to avoid obscuring the invention with unnecessary details, only the structures and / or processing steps closely related to the solution according to the invention are shown in the accompanying drawings, while other details that are not closely related to the invention are omitted.

[0030] It should be emphasized that the term "including / comprises" as used herein refers to the presence of a feature, element, step, or component, but does not exclude the presence or addition of one or more other features, elements, steps, or components.

[0031] It should also be noted that, unless otherwise specified, the term "connection" in this article can refer not only to a direct connection, but also to an indirect connection involving an intermediary.

[0032] In the following description, embodiments of the invention will be illustrated with reference to the accompanying drawings. In the drawings, the same reference numerals represent the same or similar parts, or the same or similar steps.

[0033] During driving, operators typically rely on sight and hearing to gather information and make judgments about subsequent actions. This requires a combination of visual, auditory, coordination, and reaction abilities. In traffic accidents, the time allotted for operators is often extremely short, demanding quick judgment and correct action, which severely tests their skills. Besides years of experience, individual operational ability plays a decisive role. This invention targets the operator's visual and auditory abilities, training them through perceptual dimension training tasks. Visual training enhances the operator's ability to capture information from the external environment, while auditory training supplements visually captured information, quickly arousing alertness and providing visual target direction. For coordination, training tasks improve hand-eye-hand and hand-eye-foot coordination, arm stability, and finger, wrist, and arm flexibility. Finally, for reaction ability, training tasks enhance the operator's reaction speed in the face of unexpected situations.

[0034] In response to the aforementioned training of operators' operational skills, this invention provides a method for assessing and training personnel's operational skills, such as... Figure 1 As shown, steps S110-S130 are included:

[0035] In step S110, the testing step involves selecting a training task that matches the operator's operational ability from multiple training tasks involving various training dimensions, based on the operator's operational ability, and configuring the task parameters for each training task. The participant is then tested using each selected training task to obtain the task results. Based on the task results for each training task, training tasks that the participant cannot meet are selected and added to the participant's training plan. The task results for each training task include the indicator data for each task indicator.

[0036] In step S110 above, the subject's training plan includes multiple training tasks that the subject needs to train on; task parameters are used to adjust the difficulty of the corresponding training tasks; task indicators are used to reflect the task results of each training task, and each training task includes one or more task parameters and one or more task indicators. The multiple training tasks involving various training dimensions include perceptual dimensions, coordination dimensions, and reaction dimensions. Training tasks involving the perceptual dimension train the subject's basic perceptual abilities; training tasks involving the coordination dimension train the subject's eye-hand-foot coordination; and training tasks involving the reaction dimension train the subject's rapid visual or auditory response abilities. Each training dimension includes one or more training tasks. For example, one or more training tasks, such as 2D / 3D multi-object tracking tasks, 2D / 3D visual spatial tasks, and visual search tasks, can train the subject's basic perceptual abilities in the perceptual dimension. The specific training content for the 2D / 3D multi-object tracking task is as follows: multiple objects are presented on a 2D / 3D screen, with the target objects briefly highlighted in red. Participants need to remember which objects are which. After the objects move and stop, participants need to select the moved target object based on their memory. The specific training content for the 2D / 3D visual-spatial task is as follows: two rotating figures at different angles are presented on a 2D / 3D screen, and participants need to determine whether the two figures are identical. The specific training content for the visual search task is as follows: a rapidly moving matrix of numbers randomly jumps on the screen. When a target number appears in the current matrix, participants need to immediately select the matrix containing the target number. Furthermore, one or more training tasks, such as sensorimotor coordination and motion tracking tasks, are used to train participants' eye-hand-foot coordination in the motor coordination dimension. The specific training content for the sensorimotor coordination task is as follows: different shaped tracks are presented sequentially on the screen, and participants need to control a ball to move from the starting point to the ending point of the track without touching the edge of the track. The specific training content of the motion tracking task is as follows: A training graphic is displayed on a screen, and the participant needs to control a sight to aim at the moving training graphic. Additionally, visual-auditory rapid response tasks are used to train the participant's rapid visual or auditory response abilities in the response dimension. Specifically, multiple black circles, two black rectangles, and an audio stimulus are presented on the screen. When the black circles or rectangles on the screen change color or an audio stimulus appears, the participant needs to perform the corresponding prescribed operation to demonstrate their response to the change.

[0037] In one embodiment, a training server stores multiple training tasks across various training dimensions. The experimenter selects training tasks from the stored tasks based on the operator's required skills, and configures task parameters to adjust difficulty and statistical indicators to reflect task results for each task. Before training, each selected task is used to test the subject, thus verifying and evaluating their current operational ability. Based on this ability, training tasks requiring enhanced training are selected, creating a tailored training plan for each subject. During testing, the subject executes the required training tasks by controlling the corresponding operating components on the console, obtaining task indicator data for each task. This data serves as the subject's task result, providing a comprehensive evaluation of their current operational ability. The subject's initial operational level is recorded, and training tasks that do not meet the required level are added to their training plan, thus creating a tailored training plan for each subject. For each training task, a normative result is obtained based on statistical analysis of a large amount of historical training data. This normative result indicates that the subject's operational ability meets the requirements of the corresponding training task. The steps of establishing a targeted training plan for the subject based on their initial operational ability include: comparing the indicator data of each task indicator for each training task with the corresponding normative result; when only one task indicator is used to reflect the task result of the training task, if the indicator data obtained by the subject after the training task is less than the corresponding normative result, it indicates that the subject's operational ability cannot meet the requirements of this training task, and this training task is added to the subject's training plan; when there are multiple... When task indicators are used to reflect the results of a training task, if more than half of the task indicator data are lower than the corresponding norm results, it indicates that the subject's operational ability cannot meet the requirements of this training task, and this training task is added to the subject's training plan. If the number of task indicators with data lower than the corresponding norm results and the number of task indicators with data higher than the corresponding norm results are the same, then the difference between the standard score of each task indicator data and 0 is compared. If the difference between the standard score of the task indicator data with data lower than the corresponding norm results and 0 is larger, it indicates that the subject's operational ability cannot meet the requirements of this training task, and this training task is added to the subject's training plan.

[0038] Taking the training of subjects using the motion tracking task in the above embodiments as an example, the motion tracking task is as follows:

[0039] Difficulty level: The difficulty level is determined by a custom or equally spaced division method. The task parameters that affect the difficulty level include the aiming time required for the subject to achieve the aiming result, the minimum distance coverage accuracy between the target and the crosshair required for successful aiming, and the target's movement speed.

[0040] Stimulus material: The corresponding training graphic can be changed according to the needs. In this embodiment, the training graphic is set to an airplane graphic.

[0041] Stimulus color: The training color can be changed as needed. In this embodiment, the target color is set to blue.

[0042] The area of ​​the displayed screen can vary within the range of (400-2000)*(400-2000). In this embodiment, the area of ​​the displayed screen is set to 1000*700.

[0043] Aiming star sensitivity: The aiming star's movement speed must be greater than the maximum target movement speed at the current difficulty level. The aiming star's movement speed is set to a range of 30-100px / s.

[0044] Movement modes include horizontal movement, vertical movement, four-dimensional movement, and two-handed movement. In this embodiment, the movement mode is set to vertical movement.

[0045] Joystick control includes standard mode and reverse mode. In standard mode, the actual movement of the aiming star is the same as the operation of the joystick. In reverse mode, the actual movement of the aiming star is the opposite of the operation of the joystick. In this embodiment, the joystick control mode is set to standard mode.

[0046] Maximum allowable reaction time during aiming: can be set in the range of 1-200s, and the maximum reaction time set in this embodiment is 120s.

[0047] This motion tracking task modifies the difficulty of the training task by setting task parameters such as the aiming time required for the subject to achieve the aiming result, the minimum distance coverage accuracy between the target and the crosshair required for successful aiming, and the speed of the target's movement. The subject controls the crosshair to aim at the target as much as possible, and the task results in the motion tracking task are reflected by task indicators such as the success rate of target aiming, average reaction time, average correct reaction time, horizontal threshold, and average correct distance.

[0048] In step S120, the training step involves training the subject according to the subject's training plan. For each training task in the training plan, the difficulty of the training task in the next training round is adjusted based on the task result in the current training round. In each training round, the subject executes all the training tasks in the training plan in sequence to obtain the task result corresponding to each training task in the current training round, until all the training tasks in the subject's training plan are completed through multiple training rounds.

[0049] In step S120 above, in each training round during the subject's training process, the task difficulty of each training task is adjusted by adjusting the task parameters of each training task; the subject executes training tasks for multiple training rounds according to the training plan, executes each training task in the training plan in each training round in sequence, and records the task results obtained by the subject in each training round for each training task.

[0050] In one embodiment, the step of adjusting the task difficulty of each training task in the next training round based on the task result of each training task in the current training round includes: comparing the indicator data of each task metric of the training tasks added to the training scheme in the testing step with the corresponding norm result, and adjusting the task difficulty of each training task in the first training round of the training scheme according to the comparison result; comparing the indicator data of each task metric obtained by the subject in performing each training task in the current training round with the corresponding norm result, and adjusting the task difficulty of each training task in the next training round of the training scheme according to the comparison result; for a training task with only one task metric, if the indicator data of the task metric is lower than the corresponding norm result, then in the next training round... Adjust the difficulty of the training task; conversely, increase the difficulty. For training tasks with multiple indicators, if more than half of the indicator data are lower than the corresponding norm result, decrease the difficulty; conversely, increase the difficulty. If the number of indicator data lower than the corresponding norm result and the number of indicator data higher than the corresponding norm result are the same, compare the difference between the standard score of each indicator data and 0. If the difference between the standard score of the indicator data lower than the corresponding norm result and 0 is greater, decrease the difficulty of the training task and use it as the corresponding training task in the next training round; conversely, increase the difficulty. Use the training task with adjusted difficulty as the training task for the subject in the next training round of the training plan. Repeat this process for all training tasks in the subject's training plan until the difficulty of each training task in the training plan reaches its maximum value, and the task results reflect that the subject's operational ability meets the requirements of the training task. The subject's training plan is then completed.

[0051] Taking the motion tracking task in the above embodiment as an example, the task difficulty is matched by setting the range of each task parameter of the motion tracking task. In each training round, the task difficulty of the motion tracking task in the next training round is determined by comparing the target aiming success rate, average reaction time, average correct reaction time, horizontal threshold, and average correct distance with the corresponding norm results. Task indicators that are higher than the norm results are recorded as green, and task indicators that are lower than the norm results are recorded as red. If more than 3 task indicators are red, the training task is cancelled. The difficulty of the task is adjusted to 75% of the difficulty of the task in the current training round, and any decimal is rounded up; for example, if the speed of the motion tracking task in the current training round is 100-300, then the speed after adjusting the difficulty is 75-225. Otherwise, the difficulty of the task is adjusted to 125% of the difficulty of the task in the current training round, and any decimal is rounded up; for example, if the speed of the motion tracking task in the current training round is 100-300, then the speed after adjusting the difficulty is 125-375.

[0052] The subject was trained in the next training round using a motion tracking task with increased difficulty. If more than three task indicators in the motion tracking task were red, the overall difficulty of the training task was restored to the level before the increase. For example, when the subject was trained in the next training round using a training task with a difficulty of 125% of the initial difficulty, if more than three task indicators in the motion tracking task were red, the difficulty of the training task was restored to the level before the increase, i.e., the initial difficulty. The subject is trained on a motion tracking task with reduced difficulty for the next training round. If more than three task indicators are green in the training task, the overall difficulty of the motion tracking task is restored to the level before the reduction. For example, if the subject is trained on a training task with a difficulty of 75% of the initial difficulty for the next training round, and more than three task indicators are green in the training task, the difficulty of the corresponding training task in the training plan is restored to the level before the increase, i.e., the initial difficulty. This process continues until the parameter configuration of each training task in the training plan reaches its maximum value based on the adjustment of the task difficulty, or the number of training rounds performed by the subject reaches the maximum threshold.

[0053] In another embodiment, the step of adjusting the difficulty of a training task in the next training round based on the task result of each training task in the current training round includes: creating a multiple regression model for each training task in the training scheme, using the task parameters as independent variables and the task indicators as dependent variables, based on the task parameters and task indicators of each training task in the testing step; having the experimenter select the task indicators for each training task that the subject needs to perform in each training stage; calculating multiple sets of task parameters for the training task that meet the current task indicators based on the multiple regression model of each training task; and selecting the set of task parameters with the highest difficulty as the task parameters for the training task in the current training round.

[0054] Taking the motion tracking task in the above embodiment as an example, based on the task parameters and task indicators of the motion tracking task in the testing steps, each task indicator corresponds to a fixed set of task parameters, and five multiple regression models for the motion tracking task are established:

[0055] Y1 = a1x1 + a2x2 + a3x3 + m;

[0056] Y2=b1x1+b2x2+b3x3+m

[0057] Y3=c1x1+c2x2+c3x3+m

[0058] Y4=d1x1+d2x2+d3x3+m

[0059] Y5=e1x1+e2x2+e3x3+m

[0060] Where Y1-Y5 are the dependent variables in the regression model, corresponding to the statistical indicators in motion tracking: target aiming success rate, average reaction time, average correct reaction time, horizontal threshold, and average correct distance; x1-x3 are the independent variables in the regression model, corresponding to the task parameters in the motion tracking task: aiming time required for successful aiming, minimum distance coverage accuracy between the target and the crosshair required for successful aiming, and the target's movement speed; a, b, c, d, and e are the regression coefficients corresponding to the calculated independent variables; and m is the intercept.

[0061] After the testing phase, the experimenter sets the target that the subjects should achieve in the first training session, i.e., setting the values ​​of Y1-Y5. For example, if the goal is to improve all task metrics by 25%, that is, Y1-Y5 should be 1.25 times that of the first training task. The system automatically calculates the task parameter set corresponding to each task metric under this condition, and selects the task parameter set with the highest difficulty to configure as the task parameter for that motion tracking task in the first training round of the training step (i.e., combining the set of x1, x2, x3 with the largest values ​​among the five sets to configure the corresponding task parameters). After each training round, the system builds a new multivariate regression model based on the task metrics of the motion tracking task in that training round. The experimenter resets the new task metrics and calculates and configures the task parameters for the next training round based on the new multivariate regression model, restarting a new round of training, thereby achieving controllability of the training process.

[0062] In another embodiment, the step of adjusting the task difficulty of each training task in the next training round based on the task result of each training task in the current training round includes: setting the task parameters of each training task in the first training round of the training scheme based on the machine learning model of each training task created according to the task parameters and task indicators of each training task in the norm database; adjusting the machine learning model of each training task in real time according to the task parameters and task difficulty of each training task performed by the subject in the current training round; and automatically adjusting the task parameters of each training task in the next training round according to the adjusted machine learning model.

[0063] Taking the motion tracking task in the above embodiment as an example, a machine learning model for the motion tracking task is created using the task parameters and metrics of the motion tracking task in the norm database. The algorithms of the machine learning model include SVM, random forest, KNN, Naive Bayes, etc. Based on the task parameters and metrics of the motion tracking task in the testing step, the machine learning model of the motion tracking task is automatically adjusted according to the corresponding algorithm, and the task parameters of the motion tracking task are automatically adjusted to the corresponding parameter values. In the training step, the task parameters of each training task in each training round are automatically adjusted based on the real-time adjusted machine learning model, thereby achieving adaptive training for different difficulty levels of each training task.

[0064] Corresponding to the motion tracking task in the aforementioned embodiments, the task difficulty index of the corresponding training task is matched using the parameter configuration set above: the difficulty level of the task is divided into 1-100. If the success rate of the subject aiming at the target with the aiming star in the training task of the current difficulty level is greater than or equal to 50%, the task difficulty of the motion tracking task is increased by adjusting the above parameter configuration accordingly until the task difficulty of the motion tracking task performed by the subject is the highest, and then training is stopped; the threshold range of the maximum number of execution rounds of the training task is set to 1-100. If the number of times the subject performs the motion tracking task reaches the highest threshold but the task difficulty is not the highest difficulty, training is also stopped.

[0065] The evaluation step in step S130 uses the training task with the difficulty level of the last training round in the training step to verify the subject's operational ability, obtains the task results used to display the subject's operational ability after training, and evaluates the training effect of the subject by combining the task results of each training task in the training step.

[0066] In step S130 above, the operational ability of the subject after training is verified using each training task in the training program. The task parameters of the training tasks used to verify the subject's operational ability are the same as the task parameters of each training task in the last training round of the training program. The result of each training task includes indicator data of one or more task indicators selected by the experimenter to reflect the results of each training task. The step of evaluating the training effect of the subject includes: using the task results used in the evaluation step to display the subject's operational ability after training and the task results of each training task in each training round of the training step, calculating the standard score of the indicator data of each task indicator in the training program, and performing a t-test to obtain the evaluation result of the subject's training effect in the training step.

[0067] The formula for calculating the standard score of each task indicator is: Z = (x - μ) / σ, where Z represents the standard score of each task indicator for each training task obtained by the subject during the execution of the training plan in the training step, x represents the corresponding task indicator data for each task indicator obtained by the subject during the validation step, μ represents the average of all indicator data for the corresponding task indicator for each training task obtained by the subject during the execution of the training plan in the training step, and σ represents the standard deviation of all indicator data for the corresponding task indicator for each training task obtained by the subject during the execution of the training plan in the training step.

[0068] Taking the aforementioned motion tracking task as an example, in the formula for calculating the standard score Z of the target aiming success rate index data of the motion tracking task, x represents the target aiming success rate index data obtained by the subject in the verification step when performing the motion tracking task, μ represents the average value of the target aiming success rate index data obtained by the subject in multiple training rounds of the motion tracking task in the training step, and σ represents the standard deviation of the target aiming success rate index data obtained by the subject in multiple training rounds of the motion tracking task in the training step.

[0069] In one embodiment, the assessment scheme for the subject can be set according to the subject's actual operational ability. Taking the execution steps in the assessment scheme as including the testing step, the first week training step, the first verification step and assessment step, the second week training step and the second verification and assessment step as an example, the subject is trained and the training effect of the training phase is assessed.

[0070] The evaluation method for the training effect of the first week's training steps is as follows: calculate the standard score of the indicator data for each task in each training round of the first week's training steps, and perform a t-test. The evaluation method for the training effect of the second week's training steps is as follows: calculate the standard score of the indicator data for each task in each training round of the second week's training steps, and perform a t-test. The evaluation method for the overall training effect of the scheme is as follows: calculate the standard score of the indicator data for each task in the first and second week's training steps, and perform a t-test. Thus, the standard score of the indicator data for each task in each week's training steps and the significance results of the t-test demonstrate the training effect obtained by the operators in this training phase.

[0071] The aforementioned method for assessing and training operational skills involves evaluating the training effect after the subjects complete their training steps, thereby determining the effectiveness of the training program in improving their operational skills. Based on the task results of the assessment system, a targeted training plan is developed for the following week's training phase, enabling subjects to improve their operational skills by executing the plan. Furthermore, the task results of the testing steps, the first verification step, and the second verification step in the embodiment can be presented as line graphs to show the changes in the subjects' operational skills throughout the entire assessment process. In the embodiment, the process of training subjects' operational skills includes: the experimenter selects the desired training task from all training tasks on the training server based on the subjects' actual situation and operational skill requirements. Before executing the training task, subjects log in to the local area network or cloud by copying a link to a browser, scanning a QR code, or downloading and logging into an app, creating an independent personal account for each operator and completing personal information, including name, gender, age, occupation, and driving experience. After the participants have filled in their personal information, the selected training tasks are tested using the control panel to obtain the task results for each training task. Based on the task results, the selected training tasks are added to the participants' training plan. The control panel then executes the training tasks in each training round to obtain the corresponding task results.

[0072] Based on the above-mentioned method for assessing and training personnel operational skills, the present invention also provides a system for assessing and training personnel operational skills, including a processor and a memory. The memory stores computer instructions, and the processor is used to execute the computer instructions stored in the memory. When the computer instructions are executed by the processor, the device implements the steps in the above-mentioned method for assessing and training personnel operational skills.

[0073] The above training and assessment system, such as Figure 2 As shown, it also includes an operating console and a training server; the training server stores multiple training tasks involving various training dimensions for training personnel's operational abilities; the operating console is configured with operating components corresponding to the training tasks in the training server; the operating console is connected to the training server, enabling subjects to execute the corresponding training tasks in the training server by operating the operating components in the operating console.

[0074] In one embodiment, the training tasks configured in the training server range from simple to complex tasks, and from basic to complex dimensions, enabling multi-dimensional training of operators' operational abilities and overcoming the problem of limited training methods. For example, training tasks include those for measuring and training operators' visual search and spatial abstract thinking abilities (2D and 3D), reaction time tasks combining visual and auditory tasks, measuring operators' dynamic tracking ability of multiple moving objects (2D and 3D), and a series of operational tasks measuring operators' hand-eye-hand, eye-hand-foot coordination, arm stability, and finger-wrist-arm flexibility. The control panel includes an ergonomically designed control panel, such as... Figure 3 As shown, the control panel includes circular color keys, circular response keys, 0-9 number keys, a delete key, directional keys, an confirm key, and two joysticks for performing various button and joystick operations corresponding to the training tasks. The control panel also includes a foot pedal attached to the outside of the control panel for performing pedal operations during the simulated driving process corresponding to the training tasks.

[0075] In the above embodiments, the control panel of the control console is appropriately enlarged according to actual applications to ensure proper spacing between different buttons and avoid accidental touches; the response speed of the button control components is set to less than 1ms; a joystick is used to simulate complex operational tasks during the operation of a human operator, and a foot pedal is used to simulate stepping tasks in the structure of the equipment. By simply simulating real-world application scenarios, the participants' sense of immersion is enhanced, thereby reducing operational errors caused by different models of operating equipment, controlling individual differences, and obtaining more reliable and accurate training experimental data.

[0076] Based on the aforementioned method for assessing and training personnel operational skills, another aspect of the present invention provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the aforementioned method for assessing and training personnel operational skills. This computer-readable storage medium can be a tangible storage medium, such as random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, floppy disks, hard disks, removable storage disks, CD-ROMs, or any other form of storage medium known in the art.

[0077] Those skilled in the art will understand that the exemplary components, apparatuses, and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software, or a combination of both. Whether implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention. When implemented in hardware, it can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this invention are programs or code segments used to perform the desired tasks. The programs or code segments can be stored in a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried in a carrier wave.

[0078] It should be clarified that the present invention is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of the present invention.

[0079] In this invention, features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, and / or combined with or in place of features of other embodiments.

[0080] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, various modifications and variations of the embodiments of the present invention are possible. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for assessing and training personnel's operational skills, characterized in that, Includes the following steps: The testing process involves selecting a training task that matches the operator's operational ability from multiple training tasks involving various training dimensions, based on the operator's operational ability, and configuring the task parameters for each training task. The subjects were tested using each selected training task to obtain the task results of the subjects performing each training task; Based on the results of each training task, select the training tasks that the subject cannot meet and add them to the subject's training plan. The results of each training task include the indicator data for each task indicator for each training task. The training steps involve training the subjects according to their training plan, and for each training task in the training plan, adjusting the task difficulty in the next training round based on the task results in the current training round. In each training round, the subject sequentially performs all the training tasks in the training plan and obtains the task results corresponding to each training task in the current training round until all the training tasks in the subject's training plan are completed through multiple training rounds. The assessment steps involve using a training task of the highest difficulty level from the last training round in the training steps to verify the subject's operational ability, obtaining task results that demonstrate the subject's operational ability after training, and combining the task results from each training task in the training steps to assess the subject's training effectiveness. The step of adjusting the task difficulty of each training task in the next training round based on the task result of each training task in the current training round includes: Based on the task parameters and task indicators of each training task in the training steps, the task parameters are used as independent variables and the task indicators are used as dependent variables to create a multiple regression model for each training task in the training scheme. The experimenter selects the task indicators for each training task that the subject needs to achieve in each training phase. Based on the multiple regression model of each training task, multiple sets of task parameters for the training task are calculated under the condition that the current task indicator is met. The set of task parameters with the highest difficulty is selected as the task parameters for the training task in the current training round. Based on the machine learning models of each training task created according to the task parameters and task indicators of each training task in the norm database, the machine learning models of each training task are adjusted in real time according to the task parameters and task results of the subjects in the current training round. The task parameters of each training task in the next training round are automatically adjusted according to the adjusted machine learning models.

2. The assessment and training method according to claim 1, characterized in that, The step of adjusting the task difficulty of each training task in the next training round based on the task result of each training task in the current training round includes: Compare the indicator data of each task indicator obtained by the subject in the current training round with the corresponding norm results; For a training task with only one metric, if the metric data is lower than the corresponding norm result, the task difficulty of the training task is reduced; otherwise, the task difficulty of the training task is increased. For training tasks with multiple metrics, if more than half of the metric data are lower than the corresponding norm results, the difficulty of the training task is reduced; otherwise, the difficulty of the training task is increased. If the number of metric data lower than the corresponding norm results and the number of metric data higher than the corresponding norm results are the same, the difference between the standard score of each metric data and 0 is compared. If the difference between the standard score of the metric data lower than the corresponding norm results and 0 is larger, the difficulty of the training task is reduced and it is used as the corresponding training task in the next training round; otherwise, the difficulty of the training task is increased.

3. The assessment and training method according to claim 1, characterized in that, Each training task includes one or more task parameters and one or more task metrics.

4. The assessment and training method according to claim 1, characterized in that, The training tasks that the subjects need to perform involve multiple training dimensions, and each training dimension includes one or more training tasks.

5. The assessment and training method according to claim 1, characterized in that, The steps for evaluating the training effect of the subjects include: using the task results used to display the subjects' operational ability after training and the task results of each training task in each training round of the training steps, calculating the standard score value of the indicator data of each task indicator of each training task in the training scheme, and performing a t-test to obtain the evaluation result of the subjects' training effect in the training steps.

6. A system for assessing and training personnel's operational skills, characterized in that, The system includes a processor and a memory, the memory storing computer instructions, the processor executing the computer instructions stored in the memory, and when the computer instructions are executed by the processor, the system implements the steps of the method as described in any one of claims 1-5.

7. The training and evaluation system according to claim 6, characterized in that, It also includes an operating console and a training server; the training server stores multiple training tasks involving various training dimensions for training operators' operational abilities; the operating console is configured with operating components corresponding to the training tasks in the training server; the operating console is connected to the training server, so that the subject can execute the corresponding training task in the training server by operating the operating components in the operating console.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the method as described in any one of claims 1-5.

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