An intelligent adaptive analysis system for civil aviation practice teaching based on knowledge graph

Abstract

The present invention discloses an intelligent adaptive analysis system for civil aviation practice teaching based on a knowledge graph, specifically relating to the technical field of knowledge graph, including a knowledge graph construction module, a learner model module, an intelligent recommendation module, a teaching effect evaluation module, an adaptive learning module, and a human-computer interaction module. The civil aviation practice knowledge graph is constructed by the knowledge graph construction module collecting the first key information text of civil aviation practice. The learner model is constructed by the learner model module obtaining the second key information value of civil aviation practice. The third key information value of civil aviation practice is obtained by the intelligent recommendation module. The fourth key information value of civil aviation practice is obtained by the teaching effect evaluation module; the adaptive learning module is used to establish an adaptive learning model and dynamically adjust the civil aviation practice teaching content; the human-computer interaction module is used to provide a visual interface and display the content of civil aviation practice in real time, improving the timeliness and comprehensiveness of civil aviation practice teaching.

Description

Technical Field

[0001] The present invention relates to the technical field of knowledge graphs, and more specifically, the present invention relates to an intelligent adaptive analysis system for civil aviation practice teaching based on a knowledge graph. Background Art

[0002] With the rapid development of the civil aviation industry, the demand for professional talents is increasing day by day, and at the same time, higher requirements are also put forward for the knowledge structure and skill level of talents. Traditional civil aviation practice teaching often focuses on the instillation of theoretical knowledge and the operation of simple skills, and it is difficult to meet the current industry's demand for compound and innovative talents. As a new type of knowledge representation and management technology, the knowledge graph can efficiently organize and mine massive knowledge information, providing strong support for intelligent education. With the rapid development of technologies such as artificial intelligence and big data, an intelligent adaptive analysis system based on the knowledge graph has been realized and can be continuously optimized and improved.

[0003] The traditional intelligent adaptive analysis system for civil aviation practice teaching includes a data collection module, a data analysis module, an intelligent recommendation module, a teaching effect evaluation module, and an adaptive learning module. The data collection module is responsible for collecting various data in the process of civil aviation practice teaching; the data analysis module is used to process and analyze the collected data; the intelligent recommendation module is used to provide personalized learning resources and suggestions for students according to the analysis results; the teaching effect evaluation module evaluates the effect of practice teaching; the adaptive learning module is used to dynamically adjust the teaching content and difficulty according to the learning progress and ability of students. It effectively improves the teaching efficiency and quality, enhances the effect of practice teaching, promotes teaching innovation and reform, as well as adaptability and scalability.

[0004] However, when it is actually used, there are still some disadvantages. For example, the collected data is not comprehensive enough. The parameters for evaluating the effect of civil aviation practice teaching collected by the traditional intelligent adaptive analysis system for civil aviation practice teaching are not comprehensive enough, and cannot accurately reflect the real teaching effect of civil aviation practice, resulting in inaccurate subsequent adjustments; it cannot intuitively display the results of civil aviation practice teaching and cannot effectively and timely transmit the results of civil aviation practice teaching of the intelligent adaptive analysis system for civil aviation practice teaching. Summary of the Invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides an intelligent adaptive analysis system for civil aviation practice teaching based on a knowledge graph, through the following solutions to solve the problems raised in the above background art.

[0006] To achieve the above object, the present invention provides the following technical solutions: An intelligent adaptive analysis system for civil aviation practice teaching based on a knowledge graph, including a system operation database, a system central processor, and a user information terminal, further including: a knowledge graph construction module, a learner model module, an intelligent recommendation module, a teaching effect evaluation module, an adaptive learning module, and a human-computer interaction module;

[0007] The system operation database includes all data information of the intelligent adaptive analysis system for civil aviation practice teaching, and real-time collects the data information output by each module; the system central processor is used to centrally control the information text instructions output by each module; the user information terminal is an information output device for receiving the intelligent adaptive analysis system for civil aviation practice teaching;

[0008] The knowledge graph construction module is used to collect the first key information text of civil aviation practice, and perform data processing and analysis on it to obtain the first key information value of civil aviation practice, and construct a knowledge graph of civil aviation practice;

[0009] The first key information value of civil aviation practice is obtained by performing data integration and processing on the first key information text of civil aviation practice;

[0010] The learner model module collects the second key information text of civil aviation practice, obtains the second key information value of civil aviation practice, and constructs a learner model;

[0011] The second key information value of civil aviation practice is obtained by performing data integration and processing on the second key information text of civil aviation practice;

[0012] The intelligent recommendation module is used to obtain the third key information value of civil aviation practice according to the first key information value of civil aviation practice and the second key information value of civil aviation practice;

[0013] The third key information value of civil aviation practice includes the learning stage time, task quantity, and learning feedback frequency of the learner;

[0014] The teaching effect evaluation module is used to evaluate the teaching effect of civil aviation practice, including a parameter collection unit, a data analysis unit, a comprehensive analysis unit, and a judgment unit, and obtains the fourth key information value of civil aviation practice;

[0015] The fourth key information value of civil aviation practice specifically refers to the evaluation grade of the teaching effect of civil aviation practice;

[0016] The adaptive learning module is used to establish an adaptive learning model, combine the fourth key information value of civil aviation practice with the third key information value of civil aviation practice, and dynamically adjust the teaching content of civil aviation practice;

[0017] The human-computer interaction module is used to provide a visual interface, display the teaching content, teaching progress and teaching results of civil aviation practice in real time, and transmit them to the user information terminal.

[0018] Preferably, the first key information text of civil aviation practice is civil aviation practice teaching information, specifically including teaching resources and practice projects, wherein the teaching resources specifically include videos, micro-courses, lesson plans, study plans and courseware, and the practice projects specifically include the name, content, time and location information of the civil aviation practice projects in which the learners participate.

[0019] Preferably, obtaining the first key information value of civil aviation practice requires integrating the first key information text of civil aviation practice to form a unified data set; performing data cleaning and conversion on the data set and performing data formatting and structuring to obtain the first key information value of civil aviation practice; constructing a civil aviation practice knowledge graph requires selecting a knowledge representation method and data modeling technology based on the obtained first key information value of civil aviation practice, and performing knowledge extraction and fusion; using knowledge calculation and reasoning methods to perform further analysis to obtain a civil aviation practice knowledge graph.

[0020] Preferably, the second key information text of civil aviation practice is learner information, specifically including learner basic information, learner knowledge level, learner cognitive ability and learning interest preference; building a learner model requires collecting enough learner information.

[0021] Preferably, the intelligent recommendation module performs adaptive analysis based on the obtained civil aviation practice knowledge graph and learner model to recommend appropriate learning stage time, number of tasks and learning feedback frequency, i.e., the third key information value of civil aviation practice, to learners.

[0022] Preferably, the parameter collection unit is used to collect student performance parameters, project achievement parameters and teaching process parameters. The student performance parameters specifically include accuracy, knowledge coverage, learning progress percentage and task completion, which are marked as η and η, respectively. 1 , η 2 , η 3 and η 4 ; The project achievement parameters include task completion rate, achievement submission rate, achievement completeness and number of innovation points, which are marked as η 5 , η 6 , η 7 and n 1 ; The teaching process parameters include the application frequency of knowledge graph, the number of online learning resource visits, and the utilization rate of teaching resources, which are marked as f and n respectively. 2 and η 8 .

[0023] Preferably, the data analysis unit is used to establish a data analysis model, import student performance parameters, project result parameters, and teaching process parameters into the data analysis model, and calculate a student performance evaluation value, a project result evaluation value, and a teaching process evaluation value. The student performance evaluation value is specifically expressed as:

[0024] ,

[0025] y 1 represents the student performance evaluation value of the intelligent adaptive analysis system for civil aviation practice teaching. Information of n learners is collected as samples, which are respectively labeled as 1, 2,..., i,..., n, η 1i represents the correct rate of the i-th learner, η 2i represents the knowledge coverage rate of the i-th learner, η 3i represents the learning progress percentage of the i-th learner, η 4i represents the task completion degree of the i-th learner, a 1 、a 2 、a 3 and a 4 respectively represent the influence coefficients of the correct rate, knowledge coverage rate, learning progress percentage, and task completion degree on the student performance evaluation value; The project result evaluation value is specifically expressed as:

[0026] ,

[0027] y 2 represents the project result evaluation value of the intelligent adaptive analysis system for civil aviation practice teaching. Information of k projects is collected as samples, which are respectively labeled as 1, 2,..., j,..., k, η 5j represents the task completion ratio of the j-th project, η 6j represents the result submission rate of the j-th project, η 7j represents the result integrity of the j-th project, n 1j represents the number of innovation points of the j-th project, b 1 、b 2 、b 3 and b 4 respectively represent the influence coefficients of the task completion ratio, result submission rate, result integrity, and number of innovation points on the project result evaluation value; The teaching process evaluation value is specifically expressed as:

[0028] ,

[0029] y 3 represents the teaching process evaluation value of the intelligent adaptive analysis system for civil aviation practice teaching, f represents the application frequency of the knowledge graph of the intelligent adaptive analysis system for civil aviation practice teaching, n 2Denotes the access volume of online learning resources of the intelligent adaptive analysis system for civil aviation practice teaching, η 8 Denotes the utilization rate of teaching resources of the intelligent adaptive analysis system for civil aviation practice teaching, c 1 、c 2 And c 3 Respectively denote the influence coefficients of the application frequency of the knowledge graph, the access volume of online learning resources, and the utilization rate of teaching resources on the teaching process evaluation value.

[0030] Preferably, the comprehensive analysis unit is used to establish a comprehensive analysis model, import the student performance evaluation value, the project result evaluation value, and the teaching process evaluation value into the comprehensive analysis model to calculate the civil aviation practice teaching effect evaluation value, specifically expressed as:

[0031] ,

[0032] φ denotes the civil aviation practice teaching effect evaluation value of the intelligent adaptive analysis system for civil aviation practice teaching, y 1 Denotes the student performance evaluation value of the intelligent adaptive analysis system for civil aviation practice teaching, y 2 Denotes the project result evaluation value of the intelligent adaptive analysis system for civil aviation practice teaching, y 3 Denotes the teaching process evaluation value of the intelligent adaptive analysis system for civil aviation practice teaching, y 1标 Denotes the student performance evaluation standard value of the intelligent adaptive analysis system for civil aviation practice teaching, y 2标 Denotes the project result evaluation standard value of the intelligent adaptive analysis system for civil aviation practice teaching, y 3标 Denotes the teaching process evaluation standard value of the intelligent adaptive analysis system for civil aviation practice teaching.

[0033] Preferably, the early warning unit is used to construct the civil aviation practice teaching effect evaluation standard value, including three levels, namely φ 1 、φ 2 And φ 3 Compare the obtained civil aviation practice teaching effect evaluation value with the civil aviation practice teaching effect evaluation standard value to judge the civil aviation practice teaching effect of the intelligent adaptive analysis system for civil aviation practice teaching, that is, the fourth key information value of civil aviation practice.

[0034] Preferably, the adaptive learning model is based on the obtained fourth key information value of civil aviation practice, associates it with the third key information value of civil aviation practice, and dynamically adjusts the learning stage time, task quantity, and learning feedback frequency of the learner according to the feedback effect of practical learning.

[0035] The technical effects and advantages of the present invention:

[0036] The present invention collects student performance parameters, project result parameters, and teaching process parameters through the parameter collection unit of the teaching effect evaluation module. By sampling multiple groups of learner data and project data as samples, parameters for evaluating the civil aviation practice teaching effect are comprehensively collected, accurately and effectively reflecting the true teaching effect of civil aviation practice, providing strong data support for subsequent dynamically adjusting the learning stage time, task quantity, and learning feedback frequency of learners;

[0037] The present invention performs data processing and analysis through the data analysis unit of the teaching effect evaluation module to obtain student performance evaluation values, project result evaluation values, and teaching process evaluation values. Through the comprehensive analysis unit and judgment unit, the civil aviation practice teaching effect evaluation value is obtained, and a civil aviation practice teaching effect evaluation standard value is constructed to judge the civil aviation practice teaching effect of the civil aviation practice teaching intelligent adaptive analysis system. The teaching content, teaching progress, and teaching results of civil aviation practice are accurately displayed through the man-machine interaction module, improving the efficiency and timeliness of the civil aviation practice teaching intelligent adaptive analysis system. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic structural diagram of the system of the present invention.

[0039] Figure 2 It is a schematic structural diagram of the electronic device of the present invention.

[0040] Figure 3 It is a flowchart of the steps for judging the civil aviation practice teaching effect of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0041] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0042] As shown in the Figure 1 accompanying drawings, a civil aviation practice teaching intelligent adaptive analysis system based on a knowledge graph includes a system operation database, a system central processor, and a user information terminal, and further includes a knowledge graph construction module, a learner model module, an intelligent recommendation module, a teaching effect evaluation module, an adaptive learning module, and a man-machine interaction module.

[0043] The output end of the knowledge graph construction module is connected to the input end of the learner model module through telecommunications. The output end of the learner model module is connected to the input end of the intelligent recommendation module through telecommunications. The output end of the intelligent recommendation module is connected to the input end of the teaching effect evaluation module through telecommunications. The output end of the teaching effect evaluation module is connected to the input end of the adaptive learning module through telecommunications. The output end of the adaptive learning module is connected to the input end of the human-computer interaction module through telecommunications. The output end of the system central processor is connected to the input ends of each module through telecommunications. The output ends of each module are connected to the input end of the system operation database through telecommunications.

[0044] The system operation database includes all the data information of the civil aviation practice teaching intelligent adaptive analysis system and collects the data information output by each module in real time. The system central processor is used to centrally control the information text instructions output by each module. The user information terminal is an information output device for receiving the civil aviation practice teaching intelligent adaptive analysis system.

[0045] Knowledge graph construction module: Collect the first key information text of civil aviation practice, process and analyze the data to obtain the first key information value of civil aviation practice, and construct the civil aviation practice knowledge graph.

[0046] Furthermore, the first key information text of civil aviation practice is civil aviation practice teaching information, which specifically includes teaching resources and practice projects. Among them, the teaching resources specifically include videos, micro-lessons, teaching plans, learning plans, and courseware. The practice projects specifically include the name, content, time, and location information of the civil aviation practice projects participated by learners.

[0047] Even further, obtaining the first key information value of civil aviation practice requires integrating the first key information text of civil aviation practice to form a unified data set; cleaning and transforming the data set, formatting and structuring the data to obtain the first key information value of civil aviation practice; constructing the civil aviation practice knowledge graph requires selecting a knowledge representation method and data modeling technology based on the obtained first key information value of civil aviation practice, and performing knowledge extraction and fusion; using knowledge calculation and reasoning methods for further analysis to obtain the civil aviation practice knowledge graph.

[0048] It should be specifically noted in this embodiment that the teaching resources should cover all aspects of the civil aviation field to meet the different needs of learners; the practice projects record information such as the name, content, time, and location of the civil aviation practice projects participated by learners, so that the system can analyze the practical experience and skill level of learners.

[0049] It should be specifically noted in this embodiment that in constructing the civil aviation practice knowledge graph, knowledge representation methods and data modeling techniques can be selected to collect data from the logical layer, storage layer, and computing layer to construct the knowledge graph; knowledge extraction includes entity extraction, which identifies named entities in the text, such as person names, place names, and organization names; attribute extraction, which extracts the attribute information of entities, such as the model of an aircraft and the departure time of a flight; and relationship extraction, which identifies the association relationships between entities, such as the takeoff and landing relationships between flights and airports, and the participation relationships between students and practical projects.

[0050] Learner model module: Collect the second key information text of civil aviation practice to obtain the second key information value of civil aviation practice, and construct a learner model.

[0051] Furthermore, the second key information text of civil aviation practice is learner information, which specifically includes the basic information of learners, the knowledge level of learners, the cognitive ability of learners, and the interest preferences of learning; constructing a learner model requires collecting sufficient learner information.

[0052] It should be specifically noted in this embodiment that the learner model should include basic information management, learning style analysis, knowledge level assessment, cognitive ability analysis, and interest preference analysis. Basic information management is used to store and manage the basic information of learners, such as name, age, major, etc.; learning style analysis is used to analyze and evaluate the learning style of learners using tools such as scales or questionnaires, so as to provide a basis for subsequent learning path recommendations and resource recommendations; knowledge level assessment evaluates the knowledge level of learners through tests or exercises, etc., to understand their mastery of civil aviation field knowledge; cognitive ability analysis analyzes the cognitive ability of learners, including observation, abstraction, induction, memory, analysis, calculation, and imagination abilities, etc., so as to recommend appropriate learning strategies for them; interest preference analysis analyzes the interest preferences of learners through their habits, preferences, and tendencies shown in the learning process, so as to recommend interesting learning content and learning resources for them.

[0053] Intelligent recommendation module: Obtain the third key information value of civil aviation practice based on the first key information value of civil aviation practice and the second key information value of civil aviation practice.

[0054] Furthermore, the intelligent recommendation module conducts adaptive analysis based on the obtained civil aviation practice knowledge graph and learner model, and recommends appropriate learning stage time, task quantity, and learning feedback frequency for learners, that is, the third key information value of civil aviation practice.

[0055] What needs to be specifically explained in this embodiment is that the learning stage is divided into a theoretical basis learning stage, a professional skills learning stage, and an innovative practice stage. The theoretical basis learning stage mainly cultivates students' professional basic knowledge and studies the core courses of civil aviation regulations, civil aviation transportation, civil aviation safety management, civil aviation communications, and civil aviation meteorology; the professional skills learning stage includes professional course experiments and professional internships, which deepen the understanding of theoretical knowledge through experiments and preliminarily master relevant practical operation skills; the innovative practice stage includes comprehensive practice and innovative practice, which comprehensively applies the knowledge and skills learned to solve practical problems and improve comprehensive and innovative abilities. The number of tasks refers to the total number of practical links provided to students in the practical teaching system according to the teaching plan, syllabus, and teaching requirements; the learning feedback frequency refers to the number and time interval of students submitting learning feedback to teachers or learning platforms, so that teachers can grasp students' learning situation in a timely manner.

[0056] Teaching effect evaluation module: evaluates the teaching effect of civil aviation practice, including parameter collection unit, data analysis unit, comprehensive analysis unit and judgment unit, and obtains the fourth key information value of civil aviation practice.

[0057] Furthermore, the parameter collection unit is used to collect student performance parameters, project achievement parameters and teaching process parameters. The student performance parameters specifically include accuracy, knowledge coverage, learning progress percentage and task completion, which are marked as η 1 , η 2 , η 3 and η 4 ; The project achievement parameters include task completion rate, achievement submission rate, achievement completeness and number of innovation points, which are marked as η 5 , η 6 , η 7 and n 1 ; The teaching process parameters include the application frequency of knowledge graph, the number of online learning resource visits, and the utilization rate of teaching resources, which are marked as f and n respectively. 2 and η 8 .

[0058] Furthermore, the data analysis unit is used to establish a data analysis model, import student performance parameters, project achievement parameters and teaching process parameters into the data analysis model, and calculate the student performance evaluation value, project achievement evaluation value and teaching process evaluation value. The student performance evaluation value is specifically expressed as:

[0059] ,

[0060] y 1 represents the student performance evaluation value of the intelligent adaptive analysis system for civil aviation practical teaching. The information of n learners is collected as samples and marked as 1, 2, …, i, …, n, η respectively.1i represents the correct rate of the \(i\)-th learner, \(\eta\) 2i represents the knowledge coverage rate of the \(i\)-th learner, \(\eta\) 3i represents the learning progress percentage of the \(i\)-th learner, \(\eta\) 4i represents the task completion degree of the \(i\)-th learner, \(a\) 1 、\(a\) 2 、\(a\) 3 and \(a\) 4 respectively represent the influence coefficients of the correct rate, knowledge coverage rate, learning progress percentage, and task completion degree on the student performance evaluation value; the project result evaluation value is specifically expressed as:

[0061] ,

[0062] y 2 represents the project result evaluation value of the Civil Aviation Practice Teaching Intelligent Adaptive Analysis System. \(k\) project information is collected as samples, which are respectively labeled as 1, 2, …, \(j\), …, \(k\), \(\eta\) 5j represents the task completion ratio of the \(j\)-th project, \(\eta\) 6j represents the result submission rate of the \(j\)-th project, \(\eta\) 7j represents the result integrity of the \(j\)-th project, \(n\) 1j represents the number of innovation points of the \(j\)-th project, \(b\) 1 、\(b\) 2 、\(b\) 3 and \(b\) 4 respectively represent the influence coefficients of the task completion ratio, result submission rate, result integrity, and number of innovation points on the project result evaluation value; the teaching process evaluation value is specifically expressed as:

[0063] ,

[0064] y 3 represents the teaching process evaluation value of the Civil Aviation Practice Teaching Intelligent Adaptive Analysis System. \(f\) represents the application frequency of the knowledge graph of the Civil Aviation Practice Teaching Intelligent Adaptive Analysis System, \(n\) 2 represents the access volume of online learning resources of the Civil Aviation Practice Teaching Intelligent Adaptive Analysis System, \(\eta\) 8 represents the utilization rate of teaching resources of the Civil Aviation Practice Teaching Intelligent Adaptive Analysis System, \(c\) 1 、\(c\) 2 and \(c\) 3 respectively represent the influence coefficients of the application frequency of the knowledge graph, the access volume of online learning resources, and the utilization rate of teaching resources on the teaching process evaluation value.

[0065] Furthermore, the comprehensive analysis unit is used to establish a comprehensive analysis model, import the student performance evaluation value, project outcome evaluation value, and teaching process evaluation value into the comprehensive analysis model to calculate the civil aviation practice teaching effect evaluation value, which is specifically expressed as:

[0066] ,

[0067] φ represents the civil aviation practice teaching effect evaluation value of the civil aviation practice intelligent adaptive analysis system, y 1 represents the student performance evaluation value of the civil aviation practice intelligent adaptive analysis system, y 2 represents the project outcome evaluation value of the civil aviation practice intelligent adaptive analysis system, y 3 represents the teaching process evaluation value of the civil aviation practice intelligent adaptive analysis system, y 1标 represents the student performance evaluation standard value of the civil aviation practice intelligent adaptive analysis system, y 2标 represents the project outcome evaluation standard value of the civil aviation practice intelligent adaptive analysis system, y 3标 represents the teaching process evaluation standard value of the civil aviation practice intelligent adaptive analysis system.

[0068] Furthermore, the warning unit is used to construct the civil aviation practice teaching effect evaluation standard value, including three levels, namely φ 1 , φ 2 and φ 3 , compare the obtained civil aviation practice teaching effect evaluation value with the civil aviation practice teaching effect evaluation standard value, and judge the civil aviation practice teaching effect of the civil aviation practice intelligent adaptive analysis system, that is, the fourth key information value of civil aviation practice.

[0069] It should be specifically noted in this embodiment that when φ > φ 3 , it means that the civil aviation practice teaching effect evaluation value of the civil aviation practice intelligent adaptive analysis system is greater than the civil aviation practice teaching effect evaluation standard value of the third level, indicating that the civil aviation practice teaching effect of the civil aviation practice intelligent adaptive analysis system belongs to the excellent level; when φ 2 ≤ φ ≤ φ 3 , it means that the civil aviation practice teaching effect evaluation value of the civil aviation practice intelligent adaptive analysis system is greater than the civil aviation practice teaching effect evaluation standard value of the second level and less than the civil aviation practice teaching effect evaluation standard value of the third level, indicating that the civil aviation practice teaching effect of the civil aviation practice intelligent adaptive analysis system belongs to the qualified level; when φ 1 ≤ φ < φ 2When it is, it means that the evaluation value of the civil aviation practice teaching effect of the intelligent adaptive analysis system for civil aviation practice teaching is greater than the evaluation standard value of the first-level civil aviation practice teaching effect and less than the evaluation standard value of the second-level civil aviation practice teaching effect, indicating that the civil aviation practice teaching effect of the intelligent adaptive analysis system for civil aviation practice teaching is unqualified; when φ < φ 1 When it is, it means that the evaluation value of the civil aviation practice teaching effect of the intelligent adaptive analysis system for civil aviation practice teaching is less than the evaluation standard value of the first-level civil aviation practice teaching effect, indicating that the civil aviation practice teaching effect of the intelligent adaptive analysis system for civil aviation practice teaching is seriously unqualified.

[0070] Adaptive learning module: Establish an adaptive learning model, combine the fourth key information value of civil aviation practice with the third key information value of civil aviation practice, and dynamically adjust the civil aviation practice teaching content.

[0071] Furthermore, based on the obtained fourth key information value of civil aviation practice, the adaptive learning model associates it with the third key information value of civil aviation practice, and dynamically adjusts the learning stage time, task quantity, and learning feedback frequency of learners according to the feedback effect of practical learning.

[0072] It should be specifically noted in this embodiment that according to the evaluation results of the civil aviation practice teaching effect, when the civil aviation practice teaching effect belongs to the excellent level, no adjustment is required; when the civil aviation practice teaching effect belongs to the qualified level, appropriately strengthen the time of the innovation practice stage in the learning stage time, and appropriately increase the task quantity; when the civil aviation practice teaching effect belongs to the unqualified level, strengthen the time of the professional skill learning stage and the innovation practice stage in the learning stage time, increase the task quantity, and improve the learning feedback frequency; when the civil aviation practice teaching effect belongs to the seriously unqualified level, strengthen the time of the theoretical basis learning stage, the professional skill learning stage, and the innovation practice stage in the learning stage time, adjust the task quantity according to the progress of task completion, and improve the learning feedback frequency.

[0073] Human-computer interaction module: Provide a visual interface, display the teaching content, teaching progress, and teaching achievements of civil aviation practice in real time, and transmit them to the user information terminal.

[0074] It should be specifically noted in this embodiment that the menu bar of the visual interface provides user navigation and setting options, including file operations, view control, and import and export of files. The toolbar includes common tool buttons to facilitate users to interact with the interface and display the teaching content, teaching progress, and teaching achievements of civil aviation practice in real time, including the first key information value of civil aviation practice, the second key information value of civil aviation practice, the third key information value of civil aviation practice, and the fourth key information value of civil aviation practice.

[0075] Secondly: In the accompanying drawings of the disclosed embodiments of the present invention, only the structures related to the disclosed embodiments are involved. For other structures, reference may be made to the general design. Without conflict, the same embodiment and different embodiments of the present invention may be combined with each other;

[0076] Finally: The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. An intelligent adaptive analysis system for civil aviation practical teaching based on knowledge graph, including a system operation database, a system central processor and a user information terminal, characterized in that: Also includes: Knowledge graph construction module, learner model module, intelligent recommendation module, teaching effect evaluation module, adaptive learning module and human-computer interaction module; The system operation database includes all data information of the civil aviation practical teaching intelligent adaptive analysis system, and collects data information output by each module in real time; The system central processor is used to control the information text instructions output by each module; the user information terminal is an information output device for receiving the civil aviation practical teaching intelligent adaptive analysis system; The knowledge graph construction module is used to collect the first key information text of civil aviation practice, and perform data processing and analysis on it to obtain the first key information value of civil aviation practice, and construct the civil aviation practice knowledge graph; The first key information value of civil aviation practice is obtained by performing data integration processing on the first key information text of civil aviation practice; The learner model module collects the second key information text of civil aviation practice, obtains the second key information value of civil aviation practice, and constructs a learner model; The second key information value of civil aviation practice is obtained by performing data integration processing on the second key information text of civil aviation practice; The intelligent recommendation module is used to obtain a third key information value of civil aviation practice according to the first key information value of civil aviation practice and the second key information value of civil aviation practice; The third key information value of civil aviation practice includes the learner's learning stage time, number of tasks and learning feedback frequency; The teaching effect evaluation module is used to evaluate the teaching effect of civil aviation practice, including a parameter collection unit, a data analysis unit, a comprehensive analysis unit and a judgment unit, and obtains the fourth key information value of civil aviation practice; The parameter collection unit is used to collect student performance parameters, project achievement parameters and teaching process parameters. The student performance parameters specifically include accuracy, knowledge coverage, learning progress percentage and task completion, which are marked as η1, η2, η3 and η4 respectively; the project achievement parameters specifically include task completion ratio, achievement submission rate, achievement completeness and number of innovation points, which are marked as η5, η6, η7 and n1 respectively; the teaching process parameters specifically include knowledge graph application frequency, online learning resource access volume and teaching resource utilization rate, which are marked as f, n2 and η8 respectively; The data analysis unit is used to establish a data analysis model, import student performance parameters, project achievement parameters and teaching process parameters into the data analysis model, calculate the student performance evaluation value, project achievement evaluation value and teaching process evaluation value, and the student performance evaluation value is specifically expressed as: , y1 represents the student performance evaluation value of the intelligent adaptive analysis system for civil aviation practical teaching. The information of n learners is collected as samples, which are marked as 1, 2, ..., i, ..., n, η respectively. 1i represents the accuracy rate of the i-th learner, η 2i represents the knowledge coverage of the i-th learner, η 3i represents the learning progress percentage of the i-th learner, η 4i represents the task completion of the i-th learner, a1, a2, a3 and a4 represent the influence coefficients of accuracy, knowledge coverage, learning progress percentage and task completion on the student performance evaluation value respectively; the project outcome evaluation value is specifically expressed as: ， y2 represents the project achievement evaluation value of the intelligent adaptive analysis system for civil aviation practical teaching. k project information is collected as samples and marked as 1, 2, ..., j, ..., k, η respectively. 5j represents the task completion rate of the jth project, η 6j represents the result submission rate of the jth project, η 7j Indicates the completeness of the results of the jth project, n 1j represents the number of innovation points of the jth project, b1, b2, b3 and b4 represent the influence coefficients of task completion rate, result submission rate, result completeness and number of innovation points on the project result evaluation value respectively; the teaching process evaluation value is specifically expressed as: , y3 represents the teaching process evaluation value of the civil aviation practical teaching intelligent adaptive analysis system, f represents the application frequency of the knowledge graph of the civil aviation practical teaching intelligent adaptive analysis system, n2 represents the number of online learning resource visits of the civil aviation practical teaching intelligent adaptive analysis system, η8 represents the teaching resource utilization rate of the civil aviation practical teaching intelligent adaptive analysis system, c1, c2 and c3 represent the influence coefficients of the knowledge graph application frequency, the number of online learning resource visits and the teaching resource utilization rate on the teaching process evaluation value respectively; The comprehensive analysis unit is used to establish a comprehensive analysis model, and import the student performance evaluation value, the project achievement evaluation value and the teaching process evaluation value into the comprehensive analysis model to calculate the civil aviation practical teaching effect evaluation value, which is specifically expressed as: ， φ represents the evaluation value of civil aviation practical teaching effect of intelligent adaptive analysis system for civil aviation practical teaching, y1 represents the evaluation value of student performance of intelligent adaptive analysis system for civil aviation practical teaching, y2 represents the evaluation value of project achievement of intelligent adaptive analysis system for civil aviation practical teaching, y3 represents the evaluation value of teaching process of intelligent adaptive analysis system for civil aviation practical teaching, y 1标 represents the student performance evaluation standard value of the civil aviation practical teaching intelligent adaptive analysis system, y 2标 represents the project achievement evaluation standard value of the civil aviation practical teaching intelligent adaptive analysis system, y 3标 It represents the teaching process evaluation standard value of the intelligent adaptive analysis system for civil aviation practical teaching; The fourth key information value of civil aviation practice specifically refers to the evaluation level of civil aviation practice teaching effect; The adaptive learning module is used to establish an adaptive learning model, combining the fourth key information value of civil aviation practice with the third key information value of civil aviation practice, and dynamically adjusting the teaching content of civil aviation practice; The human-computer interaction module is used to provide a visual interface, display the teaching content, teaching progress and teaching results of civil aviation practice in real time, and transmit them to the user information terminal.

2. According to claim 1, a knowledge graph-based intelligent adaptive analysis system for civil aviation practical teaching is characterized by: The first key information text of civil aviation practice is civil aviation practice teaching information, which specifically includes teaching resources and practice projects, among which teaching resources specifically include videos, micro-courses, lesson plans, study plans and courseware, and practice projects specifically include the name, content, time and location information of the civil aviation practice projects in which learners participate.

3. According to claim 1, a knowledge graph-based intelligent adaptive analysis system for civil aviation practical teaching is characterized by: The obtaining of the first key information value of civil aviation practice requires integrating the first key information text of civil aviation practice to form a unified data set; cleaning and converting the data set and formatting and structuring the data to obtain the first key information value of civil aviation practice; To construct the civil aviation practice knowledge graph, it is necessary to select the knowledge representation method and data modeling technology according to the first key information value of civil aviation practice, and perform knowledge extraction and fusion; further analysis is performed using knowledge calculation and reasoning methods to obtain the civil aviation practice knowledge graph.

4. According to claim 1, a knowledge graph-based intelligent adaptive analysis system for civil aviation practical teaching is characterized by: The second key information text of the civil aviation practice is the learner information, which specifically includes the learner's basic information, the learner's knowledge level, the learner's cognitive ability, and the learning interest preference; building a learner model requires collecting enough learner information.

5. According to claim 1, a knowledge graph-based intelligent adaptive analysis system for civil aviation practical teaching, characterized in that: The intelligent recommendation module performs adaptive analysis based on the obtained civil aviation practice knowledge graph and learner model to recommend appropriate learning stage time, task quantity and learning feedback frequency, i.e., the third key information value of civil aviation practice, to learners.

6. According to claim 1, a knowledge graph-based intelligent adaptive analysis system for civil aviation practical teaching is characterized by: The judgment unit is used to construct a civil aviation practical teaching effect evaluation standard value, including three levels, namely φ1, φ2 and φ3. The obtained civil aviation practical teaching effect evaluation value is compared with the civil aviation practical teaching effect evaluation standard value to judge the civil aviation practical teaching effect of the civil aviation practical teaching intelligent adaptive analysis system, that is, the fourth key information value of civil aviation practice.

7. According to claim 1, a knowledge graph-based intelligent adaptive analysis system for civil aviation practical teaching is characterized by: The adaptive learning model is based on the obtained fourth key information value of civil aviation practice, associates it with the third key information value of civil aviation practice, and dynamically adjusts the learner's learning stage time, task quantity and learning feedback frequency according to the feedback effect of practical learning.

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