Dynamic scene five-step teaching method and device, computer equipment and storage medium

Abstract

The invention discloses a dynamic scene five-step teaching method and device, computer equipment and a storage medium, and the method comprises the steps: receiving a design case generation demand, and based on the design case generation demand, employing a low-code mode to generate a case framework; key knowledge points involved in the case framework are determined through an artificial intelligence technology; collecting data related to the key knowledge points for extraction and analysis, and generating a dynamic case in combination with parameter configuration; and synchronizing the dynamic cases to a teaching platform of the smart classroom, and carrying out teaching by adopting intelligent equipment. Personalized dynamic generation of the case is realized, and the teaching efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent teaching technology, and in particular to a dynamic scene five-step teaching method, device, computer equipment and storage medium. Background Art

[0002] Professional knowledge training is particularly important in modern society, especially in the training of financial talents, which involves a lot of content. The traditional teaching method is mainly based on book knowledge, and teachers prepare lessons in advance. However, due to the different foundations, understanding abilities and application needs of different students, the traditional teaching method has low compatibility and low teaching efficiency. Summary of the invention

[0003] The embodiment of the present invention provides a dynamic scene five-step teaching method, device, computer equipment and storage medium to improve teaching efficiency.

[0004] In order to solve the above technical problems, the present application embodiment provides a dynamic scene five-step teaching method, including:

[0005] Receive design case generation requirements, and generate a case framework based on the design case generation requirements in a low-code manner;

[0006] Through artificial intelligence technology, determine the key knowledge points involved in the case framework;

[0007] Collect data related to the key knowledge points for extraction and analysis, and generate dynamic cases in combination with parameter configuration;

[0008] The dynamic cases are synchronized to the teaching platform of the smart classroom, and teaching is carried out using smart devices.

[0009] Optionally, the generating requirement based on the design case adopts a low-code approach, and the generating case framework includes:

[0010] Obtaining entity attribute information in the case generation requirement;

[0011] Based on the entity attribute information, a new entity structure is generated, and according to the new entity structure, a database migration file is constructed and persisted in the database;

[0012] The case framework is generated by adopting an entity-relationship model based on the entity structure persisted to the database, teaching objectives and industry needs.

[0013] Optionally, the collecting data related to the key knowledge points for refining and analyzing includes:

[0014] Collecting data related to the key knowledge points as basic data;

[0015] Performing data preprocessing on the basic data to obtain preprocessed data;

[0016] The pre-processed data is identified and analyzed by a long short-term memory neural network to obtain an analysis result.

[0017] Optionally, the generating a dynamic case by combining parameter configuration includes:

[0018] Combine parameter configuration and use the low-code platform to integrate management systems and rules into teaching tasks and generate the task import part;

[0019] Convert key knowledge points from the analysis results into teaching content;

[0020] Decompose and analyze the teaching content and generate analysis reports;

[0021] Use big data to assess the risks of villages in the analysis report and formulate corresponding control measures;

[0022] The teaching content and control measures are combined to dynamically adjust the tasks to obtain the dynamic cases.

[0023] Optionally, the smart device includes a plurality of smart large screens, and synchronizing the dynamic case to a teaching platform of a smart classroom, and using the smart device for teaching includes:

[0024] The courseware content, case analysis and student works in the dynamic case are projected onto different screens for display in real time. Each screen automatically switches and displays data in linkage according to teaching needs.

[0025] In order to solve the above technical problems, the embodiment of the present application also provides a dynamic scene five-step teaching device, including:

[0026] A framework generation module, used for receiving a design case generation requirement, and generating a case framework based on the design case generation requirement in a low-code manner;

[0027] A knowledge point determination module, used to determine the key knowledge points involved in the case framework through artificial intelligence technology;

[0028] A case generation module is used to collect data related to the key knowledge points for extraction and analysis, and generate dynamic cases in combination with parameter configuration;

[0029] The synchronous teaching module is used to synchronize the dynamic cases to the teaching platform of the smart classroom and use smart devices for teaching.

[0030] Optionally, the framework generation module includes:

[0031] An entity acquisition unit, used to acquire entity attribute information in the case generation requirement;

[0032] A persistence unit, used to generate a new entity structure based on the entity attribute information, and to construct a database migration file according to the new entity structure, and persist it in the database;

[0033] The framework generation unit is used to generate the case framework by adopting an entity relationship model based on the entity structure persisted to the database, teaching objectives and industry requirements.

[0034] Optionally, the case generation module includes:

[0035] A collection unit, used to collect data related to the key knowledge points as basic data;

[0036] A preprocessing unit, used for performing data preprocessing on the basic data to obtain preprocessed data;

[0037] The analysis unit is used to identify and analyze the pre-processed data through a long short-term memory neural network to obtain an analysis result.

[0038] Optionally, the case generation module further includes:

[0039] The task import unit is used to combine parameter configuration and use the low-code platform to integrate management systems and rules into teaching tasks to generate the task import part;

[0040] Content generation unit, used to convert key knowledge points in the analysis results into teaching content;

[0041] Content analysis unit, used to analyze and judge teaching content and generate analysis reports;

[0042] The risk control unit is used to evaluate the risks of villages in the analysis report through big data and formulate corresponding control measures;

[0043] The dynamic adjustment unit is used to combine the teaching content and the management and control measures to dynamically adjust the tasks to obtain the dynamic cases.

[0044] In order to solve the above technical problems, an embodiment of the present application also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above dynamic scene five-step teaching method when executing the computer program.

[0045] In order to solve the above technical problems, an embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the above-mentioned dynamic scene five-step teaching method are implemented.

[0046] The five-step dynamic scenario teaching method, device, computer equipment and storage medium provided by the embodiment of the present invention generate a case framework by receiving a design case generation requirement and generating the case framework based on the design case generation requirement in a low-code manner; determine the key knowledge points involved in the case framework through artificial intelligence technology; collect data related to the key knowledge points for extraction and analysis, and generate dynamic cases in combination with parameter configuration; synchronize the dynamic cases to the teaching platform of the smart classroom, and use smart devices for teaching. The personalized dynamic generation of cases is realized, which is conducive to improving teaching efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0048] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0049] Figure 2 is a flowchart of an embodiment of the dynamic scene five-step teaching method of the present application;

[0050] Figure 3 is a structural schematic diagram of an embodiment of a dynamic scene five-step teaching device according to the present application;

[0051] Figure 4 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0052] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of the present application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0053] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0054] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0055] See also Figure 1 ,like Figure 1 As shown, the system architecture 100 may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0056] Users can use terminal devices 101 , 102 , 103 to interact with server 105 via network 104 to receive or send messages, etc.

[0057] Terminal devices 101, 102, 103 can be various electronic devices with display screens and supporting web browsing, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III), MP4 (Moving Picture Experts Group Audio Layer IV) players, laptop computers, desktop computers, etc.

[0058] The server 105 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal devices 101 , 102 , and 103 .

[0059] It should be noted that the dynamic scene five-step teaching method provided in the embodiment of the present application is executed by a server, and accordingly, the dynamic scene five-step teaching device is arranged in the server.

[0060] It should be understood that Figure 1The number of terminal devices, networks and servers in the embodiment is only for illustration. According to the implementation requirements, there may be any number of terminal devices, networks and servers. The terminal devices 101, 102, 103 in the embodiment of the present application may specifically correspond to application systems in actual production.

[0061] See also Figure 2 , Figure 2 A five-step teaching method for dynamic scenes provided by an embodiment of the present invention is shown. Figure 1 The server in is used as an example to illustrate the details as follows:

[0062] S201: Receive design case generation requirements, and generate a case framework based on the design case generation requirements using a low-code approach.

[0063] In a specific implementation, based on the design case generation requirements, a low-code approach is adopted to generate a case framework including:

[0064] Obtain entity attribute information in case generation requirements;

[0065] Generate a new entity structure based on entity attribute information, build a database migration file based on the new entity structure, and persist it in the database;

[0066] The entity-relationship model is used to generate a case framework based on the entity structure persisted to the database, teaching objectives, and industry needs.

[0067] S202: Determine the key knowledge points involved in the case framework through artificial intelligence technology.

[0068] S203: Collect data related to key knowledge points for extraction and analysis, and generate dynamic cases in combination with parameter configuration.

[0069] In a specific implementation, collecting data related to key knowledge points for refining and analyzing includes:

[0070] Collect data related to key knowledge points as basic data;

[0071] Performing data preprocessing on basic data to obtain preprocessed data;

[0072] The preprocessed data is identified and analyzed through the long short-term memory neural network to obtain the analysis results.

[0073] In a specific implementation, in combination with parameter configuration, generating a dynamic case includes:

[0074] Combine parameter configuration and use the low-code platform to integrate management systems and rules into teaching tasks and generate the task import part;

[0075] Convert key knowledge points from the analysis results into teaching content;

[0076] Decompose and analyze the teaching content and generate analysis reports;

[0077] Use big data to assess the risks of villages in the analysis report and formulate corresponding control measures;

[0078] Combine teaching content and management measures, dynamically adjust tasks, and obtain dynamic cases.

[0079] S204: Synchronize the dynamic cases to the teaching platform of the smart classroom and use smart devices for teaching.

[0080] In a specific implementation, the smart device includes several smart large screens, and the dynamic cases are synchronized to the teaching platform of the smart classroom. The teaching using the smart device includes:

[0081] The courseware content, case analysis and student works in dynamic cases are projected onto different screens for real-time display. Each screen automatically switches and displays data in linkage according to teaching needs.

[0082] In this embodiment, by receiving the design case generation requirements, and based on the design case generation requirements, a case framework is generated in a low-code manner; the key knowledge points involved in the case framework are determined through artificial intelligence technology; data related to the key knowledge points are collected for extraction and analysis, and dynamic cases are generated in combination with parameter configuration; the dynamic cases are synchronized to the teaching platform of the smart classroom, and teaching is carried out using smart devices. The personalized dynamic generation of cases is achieved, which is conducive to improving teaching efficiency.

[0083] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0084] Figure 3 The schematic diagram of the dynamic scene five-step teaching device corresponding to the dynamic scene five-step teaching method in the above embodiment is shown. Figure 3 As shown, the dynamic scene five-step teaching device includes a framework generation module 31, a knowledge point determination module 32, a case generation module 33 and a synchronous teaching module 34. The functional modules are described in detail as follows:

[0085] The framework generation module 31 is used to receive the design case generation requirement, and based on the design case generation requirement, generate a case framework in a low-code manner;

[0086] A knowledge point determination module 32 is used to determine key knowledge points involved in the case framework through artificial intelligence technology;

[0087] The case generation module 33 is used to collect data related to key knowledge points for extraction and analysis, and generate dynamic cases in combination with parameter configuration;

[0088] The synchronous teaching module 34 is used to synchronize dynamic cases to the teaching platform of the smart classroom and use smart devices for teaching.

[0089] Optionally, the framework generation module 31 includes:

[0090] An entity acquisition unit, used to acquire entity attribute information in case generation requirements;

[0091] The persistence unit is used to generate a new entity structure based on entity attribute information, and to build a database migration file based on the new entity structure and persist it in the database;

[0092] The framework generation unit is used to generate a case framework based on the entity structure persisted to the database, teaching objectives and industry requirements by adopting the entity relationship model.

[0093] Optionally, the case generation module 33 includes:

[0094] The collection unit is used to collect data related to key knowledge points as basic data;

[0095] A preprocessing unit, used for performing data preprocessing on basic data to obtain preprocessed data;

[0096] The analysis unit is used to identify and analyze the pre-processed data through a long short-term memory neural network to obtain an analysis result.

[0097] Optionally, the case generation module 33 further includes:

[0098] The task import unit is used to combine parameter configuration and use the low-code platform to integrate management systems and rules into teaching tasks to generate the task import part;

[0099] Content generation unit, used to convert key knowledge points in the analysis results into teaching content;

[0100] Content analysis unit, used to analyze and judge teaching content and generate analysis reports;

[0101] The risk control unit is used to evaluate the risks of villages in the analysis report through big data and formulate corresponding control measures;

[0102] The dynamic adjustment unit is used to combine teaching content and management measures, dynamically adjust tasks, and obtain dynamic cases.

[0103] The specific definition of the dynamic scene five-step teaching device can be found in the above definition of the dynamic scene five-step teaching method, which will not be repeated here. Each module in the above-mentioned dynamic scene five-step teaching device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0104] To solve the above technical problems, the present application also provides a computer device. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0105] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 4 with components connected to the memory 41, the processor 42, and the network interface 43, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable gate arrays (Field-Programmable Gate Array, FPGA), digital processors (Digital Signal Processor, DSP), embedded devices, etc.

[0106] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.

[0107] The memory 41 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or D interface display memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 41 can be an internal storage unit of the computer device 4, such as a hard disk or memory of the computer device 4. In other embodiments, the memory 41 can also be an external storage device of the computer device 4, such as a plug-in hard disk equipped on the computer device 4, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. Of course, the memory 41 can also include both the internal storage unit of the computer device 4 and its external storage device. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 4, such as the program code of the dynamic scene five-step teaching method, etc. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or are to be output.

[0108] The processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to run the program code stored in the memory 41 or process data, such as running the program code of the dynamic scene five-step teaching method.

[0109] The network interface 43 may include a wireless network interface or a wired network interface. The network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0110] The present application also provides another implementation, namely, providing a computer-readable storage medium, wherein the computer-readable storage medium stores an interface display program, and the interface display program can be executed by at least one processor to enable the at least one processor to perform the steps of the dynamic scene five-step teaching method as described above.

[0111] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0112] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to replace some of the technical features therein with equivalents. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. A five-step teaching method for dynamic scenes, characterized in that: include: Receive design case generation requirements, and generate a case framework based on the design case generation requirements in a low-code manner; Through artificial intelligence technology, determine the key knowledge points involved in the case framework; Collect data related to the key knowledge points for extraction and analysis, and generate dynamic cases in combination with parameter configuration; The dynamic cases are synchronized to the teaching platform of the smart classroom, and teaching is carried out using smart devices.

2. The dynamic scene five-step teaching method as claimed in claim 1, characterized in that: The requirements are generated based on the design case, and a low-code approach is used to generate a case framework, including: Obtaining entity attribute information in the case generation requirement; Based on the entity attribute information, a new entity structure is generated, and according to the new entity structure, a database migration file is constructed and persisted in the database; The case framework is generated by adopting an entity-relationship model based on the entity structure persisted to the database, teaching objectives, and industry needs.

3. The dynamic scene five-step teaching method as claimed in claim 1, characterized in that: The collecting and refining analysis of data related to the key knowledge points includes: Collecting data related to the key knowledge points as basic data; Performing data preprocessing on the basic data to obtain preprocessed data; The pre-processed data is identified and analyzed by a long short-term memory neural network to obtain an analysis result.

4. The dynamic scene five-step teaching method as claimed in claim 3, characterized in that: The generating of dynamic cases by combining parameter configuration includes: Combine parameter configuration and use the low-code platform to integrate management systems and rules into teaching tasks and generate the task import part; Convert key knowledge points from the analysis results into teaching content; Decompose and analyze the teaching content and generate analysis reports; Use big data to assess the risks of villages in the analysis report and formulate corresponding control measures; The teaching content and control measures are combined to dynamically adjust the tasks to obtain the dynamic cases.

5. The dynamic scene five-step teaching method as claimed in claim 1, characterized in that: The smart device includes a plurality of smart large screens, and the dynamic case is synchronized to the teaching platform of the smart classroom. The teaching using the smart device includes: The courseware content, case analysis and student works in the dynamic case are projected onto different screens for display in real time. Each screen automatically switches and displays data in linkage according to teaching needs.

6. A dynamic scene five-step teaching device, characterized in that: include: A framework generation module, used for receiving a design case generation requirement, and generating a case framework based on the design case generation requirement in a low-code manner; A knowledge point determination module, used to determine the key knowledge points involved in the case framework through artificial intelligence technology; A case generation module is used to collect data related to the key knowledge points for extraction and analysis, and generate dynamic cases in combination with parameter configuration; The synchronous teaching module is used to synchronize the dynamic cases to the teaching platform of the smart classroom and use smart devices for teaching.

7. The dynamic scene five-step teaching device according to claim 6, characterized in that: The framework generation module includes: An entity acquisition unit, used to acquire entity attribute information in the case generation requirement; A persistence unit, used to generate a new entity structure based on the entity attribute information, and to construct a database migration file according to the new entity structure, and persist it in the database; The framework generation unit is used to generate the case framework by adopting an entity relationship model based on the entity structure persisted to the database, teaching objectives and industry requirements.

8. The dynamic scene five-step teaching device according to claim 6, characterized in that: The case generation module includes: A collection unit, used to collect data related to the key knowledge points as basic data; A preprocessing unit, used for performing data preprocessing on the basic data to obtain preprocessed data; The analysis unit is used to identify and analyze the pre-processed data through a long short-term memory neural network to obtain an analysis result.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the dynamic scene five-step teaching method as described in any one of claims 1 to 5 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the dynamic scene five-step teaching method as described in any one of claims 1 to 5 is implemented.

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