A method and system for evaluating the training effect of tactical decision-making based on human-computer interaction

Abstract

The present invention relates to a method and system for evaluating the training effect of tactical decision-making based on human-computer interaction. The method includes: obtaining a training video set corresponding to the initial training plan in a preset training video library according to the initial training plan of the trainee; receiving a target training video selected from the training video set, playing the target training video to the trainee, and based on a human-computer interaction device, obtaining the first tactical decisions selected by the trainee in each tactical scenario of the target training video, and obtaining the tactical decision-making data of the trainee according to all the first tactical decisions; substituting the tactical decision-making data of the trainee and the initial training plan into a preset training effect evaluation model to generate an initial evaluation result of the trainee. By means of human-computer interaction, the present invention improves the trainee's observation ability of the game scenario and instant tactical decision-making ability, and also tests the training effect of the trainee's tactical decision-making.

Description

Background Art

[0002] With the continuous development of high and new technologies, more and more human-computer interaction devices have emerged. However, in most cases, human-computer interaction devices are only used for controlling virtual scenarios, etc. Currently, in competitive sports, especially in the field of football, the training of tactical decision-making is particularly important. There are more or less problems with athletes' observation ability, physical adjustment ability, and tactical decision-making ability during the game, and conventional training methods for tactical decision-making are difficult to have an obvious effect, lacking an innovative training effect evaluation scheme. Therefore, there is an urgent need to provide a method for evaluating the training effect of tactical decision-making to solve the above problems. Summary of the Invention

[0003] To solve the above technical problems, the present invention provides a method and system for evaluating the training effect of tactical decision-making based on human-computer interaction.

[0004] The technical solution of a method for evaluating the training effect of tactical decision-making based on human-computer interaction according to the present invention is as follows:

[0005] According to the initial training plan of the trainee, obtain a training video set corresponding to the initial training plan in a preset training video library, and the training video set includes training videos in multiple different training scenarios;

[0006] Receive the target training video selected from the training video set, play the target training video to the trainee, and based on the human-computer interaction device, obtain the first tactical decision selected by the trainee in each tactical scenario of the target training video, and obtain the tactical decision data of the trainee according to all the first tactical decisions;

[0007] Substitute the tactical decision data of the trainee and the initial training plan into a preset training effect evaluation model to generate an initial evaluation result of the trainee.

[0008] The beneficial effects of a method for evaluating the training effect of tactical decision-making based on human-computer interaction according to the present invention are as follows:

[0009] The method of the present invention obtains the tactical decision-making choices made by the trainee in the training video through the human-computer interaction device to generate tactical decision data, and generates an evaluation result of the trainee according to the training effect evaluation model. Through the human-computer interaction method, while improving the trainee's observation ability and instant tactical decision-making ability in the game scenario, it also tests the training effect of the trainee's tactical decision-making.

[0010] On the basis of the above solution, a method for evaluating the training effect of tactical decision-making based on human-computer interaction according to the present invention can also be improved as follows.

[0011] Further, after generating the initial evaluation result of the trainee, it further includes:

[0012] Based on the initial evaluation result, modifying the initial training plan of the trainee to generate a target training plan, so that the trainee conducts training according to the target training plan.

[0013] Further, the training plan includes: role type, training difficulty, and attack / defense type.

[0014] Further, the target training video includes: at least one tactical scenario, and each tactical scenario corresponds to multiple alternative tactical decisions;

[0015] The obtaining of the first tactical decision selected by the trainee in each tactical scenario of the target training video specifically includes:

[0016] When the target training video plays to any tactical scenario, displaying the multiple alternative tactical decisions corresponding to the any tactical scenario to the trainee;

[0017] Obtaining the first tactical decision selected by the trainee from the multiple alternative tactical decisions corresponding to the any tactical scenario, until obtaining the first tactical decision selected by the trainee according to each tactical scenario in the target training video.

[0018] Further, the tactical decision data includes: total decision time and the decision result corresponding to each first tactical decision, where the total decision time is: the sum of the time durations respectively corresponding to determining each first tactical decision, and the decision result is: whether the first tactical decision is correct.

[0019] Further, it further includes:

[0020] Constructing an evaluation index system for the training effect of tactical decisions;

[0021] Based on the analytic hierarchy process, determining and generating the preset training effect evaluation model according to the weight of each evaluation index in the evaluation index system for the training effect of tactical decisions;

[0022] Among them, the evaluation index system for the training effect of tactical decisions includes multiple evaluation indexes, and the evaluation indexes are: the role type, the training difficulty, the attack / defense type, the total decision time, and the decision result corresponding to each first tactical decision.

[0023] Further, the human-computer interaction device includes: VR glasses or a human-computer interaction carpet.

[0024] Further, it further includes: using an electronic curtain wall to display the target training video.

[0025] Further, the initial evaluation result of the trainee is: the tactical decision-making training score obtained according to the tactical decision-making data, the initial training plan, and the preset training effect evaluation model.

[0026] The technical solution of a tactical decision-making training effect evaluation system based on human-computer interaction of the present invention is as follows:

[0027] It includes: a matching module, an acquisition module, and an evaluation module;

[0028] The matching module is used to: according to the initial training plan of the trainee, obtain a training video set corresponding to the initial training plan in the preset training video library, and the training video set includes training videos in multiple different training scenarios;

[0029] The acquisition module is used to: receive the target training video selected from the training video set, play the target training video to the trainee, and based on the human-computer interaction device, obtain the first tactical decision selected by the trainee in each tactical scenario of the target training video, and obtain the tactical decision-making data of the trainee according to all the first tactical decisions;

[0030] The evaluation module is used to: substitute the tactical decision-making data of the trainee and the initial training plan into the preset training effect evaluation model to generate the initial evaluation result of the trainee.

[0031] The beneficial effects of a tactical decision-making training effect evaluation system based on human-computer interaction of the present invention are as follows:

[0032] The system of the present invention obtains the tactical decision-making choices made by the trainee in the training video through the human-computer interaction device to generate tactical decision-making data, and generates the evaluation result of the trainee according to the training effect evaluation model. Through the human-computer interaction method, while improving the trainee's observation ability of the game scenario and instant tactical decision-making ability, it also tests the training effect of the trainee's tactical decision-making.

[0033] The technical solution of a storage medium of the present invention is as follows:

[0034] Instructions are stored in the storage medium, and when the computer reads the instructions, the computer is made to execute the steps of a tactical decision-making training effect evaluation method based on human-computer interaction of the present invention.

[0035] The technical solution of an electronic device of the present invention is as follows:

[0036] It includes a memory, a processor, and a computer program stored on the memory and executable on the processor. The characteristic is that when the processor executes the computer program, the computer is made to execute the steps of a tactical decision-making training effect evaluation method based on human-computer interaction of the present invention. Description of the Drawings

[0037] Figure 1 It is a schematic flowchart of a method for evaluating the training effect of tactical decision-making based on human-computer interaction according to an embodiment of the present invention;

[0038] Figure 2 It is a schematic structural diagram of a system for evaluating the training effect of tactical decision-making based on human-computer interaction according to an embodiment of the present invention. Detailed Embodiments

[0039] As Figure 1 shown, a method for evaluating the training effect of tactical decision-making based on human-computer interaction according to an embodiment of the present invention includes the following steps:

[0040] S1. According to the initial training plan of the trainee, obtain a training video set corresponding to the initial training plan in a preset training video library, and the training video set includes training videos under multiple different training scenarios.

[0041] Among them, the trainee is an athlete to be trained. In this embodiment, football players are mainly taken as an example, but when applied to other types of sports or other fields, it should also be protected by the technical solutions of this embodiment.

[0042] Among them, the initial training plan is set according to the trainee's own situation.

[0043] Among them, the preset video library includes multiple training video sets, and each different initial training plan corresponds to a training video set. The videos in the preset video library are all from the game clips of professional games, such as large cup competitions or leagues like the Premier League, the Champions League, the World Cup or the European Cup. The classification criteria for different training video sets in the training video library are jointly set by professional football analysts and football coaches at home and abroad, and the classification of the training video sets has a certain degree of authority and fairness.

[0044] Among them, each training video set includes: training videos under multiple different training scenarios. The training scenario is determined according to the source of the video. The training scenario is: large cup competitions or leagues, such as the Premier League and the World Cup, etc.; the training video is: a certain game clip in a large cup competition or league, such as a certain game clip in a Premier League game or a certain game clip in the World Cup.

[0045] Specifically, according to the initial training plan set by the trainee, the initial training plan is matched in a preset training video library. The preset training video library stores training video sets corresponding one by one to the training plans according to different training plans (for example, when the role type of the trainee is: forward, the training difficulty is: difficult, and the offense-defense type is: offense, then the corresponding training video set is matched according to the corresponding role type, training difficulty, and offense-defense type) to obtain the training video set corresponding to the initial training plan.

[0046] S2. Receive the target training video selected from the training video set, play the target training video to the trainee, and based on the human-computer interaction device, obtain the first tactical decision selected by the trainee in each tactical scenario of the target training video, and obtain the tactical decision data of the trainee according to all the first tactical decisions.

[0047] Among them, the target training video selected by the user may include one or more training videos. When the target training video selected by the user includes multiple training videos, each training video is played one by one (either in sequence or randomly) until each training video selected by the user is played.

[0048] Among them, each training video includes multiple tactical scenarios. For example, the tactical scenario is: at this time, the trainee needs to pass the ball, and there are multiple passing routes on the current court for the trainee to choose.

[0049] Among them, the first tactical decision is: the tactical decision selected by the trainee from the multiple tactical decisions in any tactical scenario of the target training video. Continuing with the above example, at this time, the terminal device sends multiple passing routes for the trainee to choose (A, B, C). If the trainee chooses route B at this time, the tactical decision corresponding to route B is the first tactical decision of the trainee.

[0050] Specifically, the terminal device will randomly play the target training video in the training video set corresponding to the initial training plan of the trainee through human-computer interaction. When the target training video is played to the first tactical scenario, the terminal device will pause the video (during the video pause, at this time, it can be prompted through text, or shown to the trainee in the form of a tactical decision preview animation, or other methods, without limitation here), and let the trainee make a first tactical decision in this tactical scenario. After the trainee makes a tactical decision in this tactical scenario, continue to play the target training video, and repeat the above steps until all the first tactical decisions in the target training video are obtained.

[0051] S3. Substitute the tactical decision data of the trainee and the initial training plan into a preset training effect evaluation model to generate the initial evaluation result of the trainee.

[0052] Among them, the tactical decision-making data includes various data of the trainee during the training in the training video. Such as: the total decision-making duration and the decision-making results corresponding to each first tactical decision, etc.

[0053] Among them, the preset training effect evaluation model is: a model generated by a pre-constructed model index system, which is used to generate an initial evaluation result according to the tactical decision-making data of the trainee during this training process and the corresponding index parameters in the initial training plan.

[0054] Among them, the initial evaluation result includes: the training score of the trainee in this tactical decision-making training and whether this training process meets the needs of the trainee. For example, when the training plan selected by the trainee this time is too simple or difficult, resulting in too low or too high a final evaluation score for this training, the terminal device will make a judgment. Specifically, it can be judged in combination with the trainee's historical training plan, historical training evaluation score, etc. When it exceeds a certain threshold, it will be determined that there is an abnormality in this training process.

[0055] Specifically, the terminal device obtains the initial evaluation result of the trainee by substituting the trainee's tactical decision-making data and the initial training plan into the preset training effect evaluation model set in advance.

[0056] Preferably, after generating the initial evaluation result of the trainee, it further includes:

[0057] Based on the initial evaluation result, the initial training plan of the trainee is corrected to generate a target training plan, so that the trainee can train according to the target training plan.

[0058] Specifically, when the initial evaluation result is abnormal, the trainee is prompted to correct the initial training plan to obtain a corrected target training plan, so that the trainee can retrain according to the new target training plan. Among them, the abnormal judgment condition is: the training score exceeds the threshold range, and the threshold range is the floating range of the average score corresponding to the original training plan. For example, if the average score is 70 points and the floating range is 20, and if the trainee's score is 95 at this time, it is determined that the initial evaluation result is abnormal.

[0059] Preferably, the original training plan includes: role type, training difficulty, and offense and defense type.

[0060] Among them, the role type specifically includes: defender, midfielder, forward, and goalkeeper; the training difficulty specifically includes: simple, ordinary, professional, or difficult; the offense and defense type includes: offense and defense.

[0061] For example, the specific original training plan selected by a trainee is: forward, difficult, offensive; then a training video set corresponding to the initial training plan will be obtained from the preset training video library according to this original training plan.

[0062] It should be noted that the role type, training difficulty, and offensive and defensive types are not limited to the above selections and can be changed according to the actual situation without limitation here. For example, the role type of forward can be further divided into center forward and winger, and the offensive and defensive type can also be set with offensive and defensive transitions, etc.

[0063] Preferably, the target training video includes: at least one tactical scenario, and each tactical scenario corresponds to multiple candidate tactical decisions.

[0064] Among them, by default, there are three candidate tactical decisions corresponding to each tactical scenario, and it can also be changed according to requirements.

[0065] The obtaining of the first tactical decision selected by the trainee in each tactical scenario of the target training video specifically includes:

[0066] When the target training video plays to any tactical scenario, multiple candidate tactical decisions corresponding to the any tactical scenario are shown to the trainee.

[0067] Among them, when playing to any tactical scenario, the target training video will pause, and the candidate tactical decisions corresponding to the tactical scenario are shown to the trainee through the man-machine interaction device.

[0068] For example, when the tactical scenario is the passing tactical decision of the attacking side, there are three candidate tactical decisions for passing on the field at this time, such as: passing to A to the left, passing to B forward, and passing back to C.

[0069] The first tactical decision selected by the trainee among the multiple candidate tactical decisions corresponding to the any tactical scenario is obtained until the first tactical decisions selected by the trainee according to each tactical scenario in the target training video are obtained.

[0070] Among them, when the trainee makes a tactical decision in a certain tactical scenario, the target training video will continue to play until the trainee makes tactical decisions for each tactical scenario in the target training video and then stops playing.

[0071] Preferably, the tactical decision data includes: the total decision duration and the decision result corresponding to each first tactical decision. Among them, the total decision duration is: the sum of the time durations respectively corresponding to determining each first tactical decision, and the decision result is: whether the first tactical decision is correct.

[0072] Among them, the decision-making duration of each first tactical decision is the time duration from the moment when any tactical scenario in the target training video starts to appear (the video is paused) until the trainee makes the first tactical decision in that tactical scenario; the decision-making result of each first tactical decision is whether the first tactical decision selected by the trainee for each first tactical decision is correct, and each first tactical decision corresponds to a different weight score, which is convenient for calculating the evaluation result later.

[0073] Among them, the total decision-making duration is the sum of the time durations corresponding to determining the first tactical decisions respectively. For example: there are three tactical scenarios in the training video, and the times when the trainee makes the first tactical decisions in the three tactical scenarios are 3S, 2S, and 4S, then the total decision-making duration of this trainee is 9S.

[0074] In addition, each of the above-mentioned tactical scenarios corresponds to multiple alternative tactical decisions, including: the optimal tactical decision, the sub-optimal tactical decision, and the worst tactical decision;

[0075] When the first tactical decision selected by the trainee is the optimal tactical decision, obtain the training result corresponding to the first tactical decision, and control the target training video to continue playing;

[0076] When the first tactical decision selected by the trainee is the sub-optimal tactical decision, obtain the training result corresponding to the first tactical decision, send a prompt message for the option corresponding to the optimal tactical decision to the trainee, and control the target training video to continue playing;

[0077] When the first tactical decision selected by the trainee is the worst tactical decision, obtain the training result corresponding to the first tactical decision, and send a prompt message for the trainee to re-select the first tactical decision until the first tactical decision selected by the trainee is the optimal tactical decision or the sub-optimal tactical decision, and then control the target training video to continue playing.

[0078] Preferably, it further includes:

[0079] Construct an evaluation index system for the training effect of tactical decisions.

[0080] Based on the analytic hierarchy process, determine and generate the preset training effect evaluation model according to the weight of each evaluation index in the evaluation index system for the training effect of tactical decisions.

[0081] Among them, the tactical decision-making training effect evaluation index system includes multiple evaluation indexes, and the evaluation indexes are: the role type X1, the training difficulty X2, the offense and defense type X3, the total decision-making duration X4, and the decision-making result X5 of each tactical decision. The corresponding weights are: the role type weight R1, the training difficulty weight R2, the offense and defense type weight R3, the total decision-making duration weight R4, and the decision-making result weight R5 of each tactical decision. There are also sub-weights under some weights.

[0082] Specifically, the expert scoring method in the analytic hierarchy process is used to determine the weight of each index. The value of the corresponding weight is obtained according to the average score of multiple experts for each weight.

[0083] Preferably, the human-computer interaction device includes: VR glasses or a human-computer interaction carpet.

[0084] Among them, when the human-computer interaction device is a human-computer interaction carpet, the trainee can step on the corresponding area of the human-computer interaction carpet to select the first tactical decision.

[0085] It should be noted that the specific type of the human-computer interaction device is not limited to the above types and is not restricted here.

[0086] Preferably, it further includes: using an electronic curtain wall to display the target training video.

[0087] Among them, display screens (electronic curtain walls) are arranged around the trainee to project a real three-dimensional game scenario, so that the trainee, as a player on a certain team, is placed in the real game scenario.

[0088] Preferably, the initial evaluation result of the trainee is: the tactical decision-making training score obtained according to the tactical decision-making data, the initial training plan, and the preset training effect evaluation model.

[0089] Specifically, the tactical decision-making data of the trainee and the initial training plan are substituted into the preset training effect evaluation model to obtain the tactical decision-making training score (the tactical decision-making training score is obtained by accumulating the product of each weight and the corresponding score).

[0090] In this embodiment, the human-computer interaction device is used to obtain the tactical decision-making selection made by the trainee in the training video to generate tactical decision-making data, and the evaluation result of the trainee is generated according to the training effect evaluation model. The technical solution of this embodiment, through the human-computer interaction method, improves the trainee's observation ability of the game scenario and instant tactical decision-making ability, and also tests the training effect of the trainee's tactical decision-making.

[0091] Such as Figure 2As shown in the figure, a training effect evaluation system 200 for tactical decision-making based on human-computer interaction according to an embodiment of the present invention includes: a matching module 210, an acquisition module 220, and an evaluation module 230;

[0092] The matching module 210 is configured to: according to the initial training plan of the trainee, obtain a training video set corresponding to the initial training plan in a preset training video library, and the training video set includes training videos in multiple different training scenarios;

[0093] The acquisition module 220 is configured to: receive a target training video selected from the training video set, play the target training video to the trainee, and based on a human-computer interaction device, obtain the first tactical decisions selected by the trainee in each tactical scenario of the target training video, and obtain the tactical decision data of the trainee according to all the first tactical decisions;

[0094] The evaluation module 230 is configured to: substitute the tactical decision data of the trainee and the initial training plan into a preset training effect evaluation model to generate an initial evaluation result of the trainee.

[0095] In this embodiment, the tactical decision-making data made by the trainee in the training video is obtained through a human-computer interaction device to generate tactical decision data, and the evaluation result of the trainee is generated according to the training effect evaluation model. The technical solution of this embodiment, through the human-computer interaction method, while improving the trainee's observation ability and instantaneous tactical decision-making ability in the game scenario, also tests the training effect of the trainee's tactical decision-making.

[0096] For the parameters and the steps for each module in the above-mentioned training effect evaluation system 200 for tactical decision-making based on human-computer interaction according to this embodiment to implement corresponding functions, reference can be made to the parameters and steps in the embodiment of the training effect evaluation method for tactical decision-making based on human-computer interaction in the above text, and details will not be elaborated here.

[0097] A storage medium provided by an embodiment of the present invention includes: instructions are stored in the storage medium, and when a computer reads the instructions, the computer is made to execute the steps of a training effect evaluation method for tactical decision-making based on human-computer interaction. Specifically, reference can be made to the parameters and steps in the embodiment of the training effect evaluation method for tactical decision-making based on human-computer interaction in the above text, and details will not be elaborated here.

[0098] Computer storage media such as: USB flash drives, external hard drives, etc.

[0099] An electronic device provided by an embodiment of the present invention includes a memory, a processor, and a computer program stored on the memory and executable on the processor. It is characterized in that when the processor executes the computer program, the computer is made to execute the steps of a method for evaluating the training effect of tactical decision-making based on human-computer interaction. Specifically, reference can be made to the parameters and steps in the embodiments of the method for evaluating the training effect of tactical decision-making based on human-computer interaction in the foregoing text, which will not be elaborated herein.

[0100] Those skilled in the art of the present technology field know that the present invention can be implemented as a method, a device, a storage medium, and an electronic device.

[0101] Therefore, the present invention can be specifically implemented in the following forms, that is: it can be completely hardware, can also be completely software (including firmware, resident software, microcode, etc.), or can also be a combination of hardware and software, which is generally referred to as "circuit", "module" or "system" in this article. In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable media contains computer-readable program code. Any combination of one or more computer-readable media can be adopted. The computer-readable media can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination of the above. More specific examples (non-exhaustive list) of the computer-readable storage medium include: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or combined with an instruction execution system, device, or component. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for evaluating the training effect of tactical decision-making based on human-computer interaction, characterized in that, Including: According to the initial training plan of the trainee, obtain a training video set corresponding to the initial training plan in a preset training video library. The training video set includes training videos in multiple different training scenarios. Among them, the initial training plan includes: role type, training difficulty, and offense-defense type. The role type specifically includes: goalkeeper, defender, and forward. The training difficulty specifically includes: easy, normal, professional, or difficult. The offense-defense type includes: offense and defense. The videos in the preset video library are all sourced from game clips of professional matches. Receive the target training video selected from the training video set, play the target training video for the trainee, and based on the human-computer interaction device, obtain the first tactical decisions selected by the trainee in each tactical scenario of the target training video, and obtain the tactical decision data of the trainee according to all the first tactical decisions. The human-computer interaction device is: VR glasses or a human-computer interaction carpet. It also includes: using an electronic curtain wall to display the target training video. Among them, an electronic curtain wall is arranged around the trainee for projecting a real game three-dimensional scene. Substitute the tactical decision data of the trainee and the initial training plan into a preset training effect evaluation model to generate the initial evaluation result of the trainee. The target training video includes: at least one tactical scenario, and each tactical scenario corresponds to multiple candidate tactical decisions. The obtaining of the first tactical decisions selected by the trainee in each tactical scenario of the target training video specifically includes: When the target training video plays to any tactical scenario, control the target training video to pause, and display the multiple candidate tactical decisions corresponding to the any tactical scenario to the trainee through the human-computer interaction device. Obtain the first tactical decisions selected by the trainee from the multiple candidate tactical decisions corresponding to the any tactical scenario until the first tactical decisions selected by the trainee according to each tactical scenario in the target training video are obtained. The tactical decision data includes: the total decision time and the decision result corresponding to each first tactical decision. Among them, the total decision time is: the sum of the time durations respectively corresponding to determining each first tactical decision, and the decision result is: whether the first tactical decision is correct. It also includes: Construct a tactical decision training effect evaluation index system; based on the analytic hierarchy process, determine and according to the weights of each evaluation index in the tactical decision training effect evaluation index system, generate the preset training effect evaluation model. Among them, the tactical decision training effect evaluation index system includes multiple evaluation indexes. The evaluation indexes are: the role type, the training difficulty, the offense-defense type, the total decision time, and the decision result corresponding to each first tactical decision. The corresponding weights are: role type weight, training difficulty weight, offense-defense type weight, total decision time weight, and decision result weight of each tactical decision.

2. The method for evaluating the training effect of tactical decision-making based on human-computer interaction according to claim 1, wherein After generating the initial evaluation result of the trainee, it also includes: Based on the initial evaluation result, the initial training plan of the trainee is corrected to generate a target training plan, so that the trainee can train according to the target training plan.

3. The method for evaluating the training effect of tactical decision-making based on human-computer interaction according to claim 1 or 2, characterized in that, The initial evaluation result of the trainee is: the tactical decision training score obtained according to the tactical decision data, the initial training plan and the preset training effect evaluation model.

4. A tactical decision-making training effect evaluation system based on human-computer interaction, characterized in that, Including: A matching module, an acquisition module and an evaluation module; The matching module is used to: according to the initial training plan of the trainee, obtain a training video set corresponding to the initial training plan in the preset training video library, and the training video set includes training videos in multiple different training scenarios; The initial training plan includes: role type, training difficulty and offense-defense type; the role type specifically includes: goalkeeper, defender, forward; the training difficulty specifically includes: simple, ordinary, professional or difficult; the offense-defense type includes: offense and defense; the videos in the preset video library are all from the game clips of professional games; The acquisition module is used to: receive the target training video selected from the training video set, play the target training video to the trainee, and based on the human-computer interaction device, obtain the first tactical decision selected by the trainee in each tactical scenario of the target training video, and obtain the tactical decision data of the trainee according to all the first tactical decisions; the human-computer interaction device is: VR glasses or a human-computer interaction carpet; it also includes: using an electronic curtain wall to display the target training video; wherein, an electronic curtain wall is arranged around the trainee for projecting a real game three-dimensional scene; The evaluation module is used to: substitute the tactical decision data and the initial training plan of the trainee into the preset training effect evaluation model to generate the initial evaluation result of the trainee; The target training video includes: at least one tactical scenario, and each tactical scenario corresponds to multiple alternative tactical decisions; Specifically, the acquisition module is used to: When the target training video is played to any tactical scenario, control the target training video to pause, and display the multiple alternative tactical decisions corresponding to the any tactical scenario to the trainee through the human-computer interaction device; Obtain the first tactical decision selected by the trainee from the multiple alternative tactical decisions corresponding to the any tactical scenario, until obtaining the first tactical decision selected by the trainee according to each tactical scenario in the target training video; The tactical decision data includes: the total decision-making duration and the decision result corresponding to each first tactical decision, wherein the total decision-making duration is: the sum of the time durations respectively corresponding to determining each first tactical decision, and the decision result is: whether the first tactical decision is correct; It further includes: a construction module; the construction module is used for: constructing an evaluation index system for the training effect of tactical decision-making; based on the analytic hierarchy process, determining and generating the preset training effect evaluation model according to the weight of each evaluation index in the evaluation index system for the training effect of tactical decision-making; wherein, the evaluation index system for the training effect of tactical decision-making includes multiple evaluation indexes, and the evaluation indexes are: the role type, the training difficulty, the offense and defense type, the total decision-making duration, and the decision-making result corresponding to each first tactical decision, and the corresponding weights are: the role type weight, the training difficulty weight, the offense and defense type weight, the total decision-making duration weight, and the decision-making result weight of each tactical decision.

Images