Data processing method and device for personalized education learning

Abstract

The invention discloses a data processing method and device for personalized education learning, which comprises the steps of entering an artificial intelligence and curriculum teaching analysis application platform through a preset account and starting personalized education learning tutoring operation of corresponding contents, and is characterized in that the method comprises the following steps: selecting in a learning content selection interface according to own requirements; inputting keyword information, and generating teaching script information of teaching tutoring; and displaying dialogue information of personalized education learning according to a preset standard database. The device comprises a learning content response module, a keyword response module, a script response module, an intelligent learning guide response module and a dialogue response module. Compared with the prior art, the method has the advantages that the knowledge display content is adjusted according to the requirements of the students, personalized education learning guidance corresponding to the requirements of the students is generated to meet the actual requirements of the students, and the method is simple, convenient, high in practicability and good in application prospect.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of artificial intelligence teaching guidance, and in particular to a data processing method for personalized education learning and a data processing device thereof. BACKGROUND

[0002] Personalized teaching guidance is an important tool for assisting teaching materials and improving learning effect in the teaching process. A large language model is a natural language processing model based on deep learning. After pre-training based on massive text data, the large language model can perform text generation, question answering, translation and other tasks. At present, the large language model has been applied in teaching guidance. However, the existing process of personalized teaching guidance based on the large language model only displays knowledge to students in one direction based on the set display rules, and cannot adjust the knowledge display content according to the needs of students, so that the teaching guidance cannot meet the needs of students.

[0003] In summary, the existing process of teaching guidance based on the large language model only displays knowledge to students in one direction based on the set display rules, and cannot adjust the knowledge display content according to the needs of students, so that the teaching guidance cannot meet the actual needs of students. SUMMARY

[0004] The present application aims to provide a data processing method for personalized education learning and a device thereof to overcome the shortcomings of the prior art. The method displays dialog information for personalized education learning based on a preset standard database, so that students can generate display content corresponding to their needs during the learning process to meet their actual needs. The method displays a learning content selection interface according to the student's needs in response to a personalized education learning start instruction, displays a keyword input interface in response to a selection completion instruction of the learning content selection interface, generates teaching script information of a teaching guidance course outline in response to keyword information input by the student in the keyword input interface, displays an intelligent learning interface for teaching guidance in response to a generation completion instruction of the teaching script information, and displays dialog information for personalized education learning based on the preset standard database in response to an intelligent learning generation instruction of the intelligent learning interface for teaching guidance. Thus, students can generate display content corresponding to their needs during the learning process to meet their actual needs.

[0005] The present application is achieved by a data processing method for personalized education learning, which includes entering an artificial intelligence and course teaching analysis application platform through a preset account, starting personalized education learning guidance operation of corresponding content when "artificial intelligence learning guidance" is selected, and the method includes the following steps: Step 1: displaying a learning content selection interface in response to a personalized education learning start instruction; Step 2: in response to the selection completion instruction of the learning content selection interface, display the keyword input interface; Step 3: input the keyword information in the keyword input interface, generate the teaching script information of the teaching guidance course outline; Step 4: in response to the generation completion instruction of the teaching script information, display the intelligent learning guide interface of the teaching guidance; Step 5: in response to the intelligent learning generation instruction of the intelligent learning guide interface, display the dialogue information of the personalized education learning according to the preset standard database.

[0006] The step 1 specifically includes: 1) in response to the learning basic information selection instruction in the personalized education learning start instruction, perform the selection operation of the learning basic information in the displayed learning basic information selection interface, the learning basic information including: subject information, learning age and learning type; 2) in response to the learning theme selection instruction in the personalized education learning start instruction, perform the selection operation of the learning theme in the displayed learning theme selection interface; 3) in response to the learning goal selection instruction in the personalized education learning start instruction, perform the selection operation of the learning goal in the displayed learning goal selection interface.

[0007] The response to the learning basic information selection instruction in the personalized education learning start instruction, the selection operation of the learning basic information in the displayed learning basic information selection interface, specifically includes: 1) in response to the subject selection instruction of the learning basic information selection instruction, display at least one subject selection item; 2) in response to the age selection instruction of the learning basic information selection instruction, display at least one age selection item; 3) in response to the course type selection instruction of the learning basic information selection instruction, display at least one course type selection item.

[0008] The response to the learning theme selection instruction in the personalized education learning start instruction, the selection operation of the learning theme in the displayed learning theme selection interface, specifically includes: in response to the learning theme selection instruction in the personalized education learning start instruction, display a plurality of learning theme options obtained by artificial intelligence expansion according to the learning basic information selection result in the displayed learning theme selection interface; or in response to the learning theme selection instruction in the personalized education learning start instruction, fill in the learning theme information in the displayed learning theme selection interface.

[0009] The response to the learning goal selection instruction in the personalized education learning start instruction, the selection of the learning goal in the displayed learning goal selection interface, specifically includes: 1) a learning section selection instruction in response to a learning target selection instruction, displaying at least one learning section selection item; 2) a task group selection instruction in response to a learning target selection instruction, displaying at least one task group selection item; 3) a sub-task group selection instruction in response to a learning target selection instruction, displaying at least one sub-task group selection item according to a learning basic information selection result and a learning theme selection result.

[0010] The step 5 specifically includes: 1) a first content information in response to a learning content selection result according to a preset standard database, displayed in a personalized education learning dialogue information display interface corresponding to a keyword in response to an intelligent learning generation instruction of an intelligent learning interface; 2) a second content information in response to a first text question information input by a student in a personalized education learning dialogue information display interface, displayed in the displayed personalized education learning dialogue information display interface according to a preset standard database.

[0011] Further, the step 5 includes: 1) a first content information in response to a learning content selection result according to a preset standard database, displayed in a personalized education learning dialogue information display interface corresponding to a keyword in response to an intelligent learning generation instruction of an intelligent learning interface; 2) a second text question information corresponding to a voice information in a personalized education learning dialogue information display interface in response to the voice information input by a student in the personalized education learning dialogue information display interface; 3) a third content information in response to the second text question information in a personalized education learning dialogue information display interface, displayed in the personalized education learning dialogue information display interface according to a preset standard database.

[0012] A personalized education learning data processing method constructs a personalized education learning data processing device, characterized by a learning content response module, a keyword response module, a script response module, an intelligent learning response module, and a dialogue response module. The keyword response module is used for a selection completion instruction of a learning content selection interface to display a keyword input interface; the script response module is used for generating teaching script information of a teaching guidance course outline in response to keyword information input by the keyword input interface; the intelligent learning response module is used for displaying an intelligent learning interface of teaching guidance in response to a generation completion instruction of the teaching script information; and the dialogue response module is used for displaying dialogue information of personalized education learning according to a preset standard database in response to an intelligent learning generation instruction of the intelligent learning interface.

[0013] Compared with the prior art, the present application has the advantages that by displaying a learning content selection interface in response to a personalized education learning start instruction, the student can select according to his own needs in the learning content selection interface, by displaying a keyword input interface in response to a selection completion instruction of the learning content selection interface, then generating teaching script information of a teaching guidance course outline in response to keyword information input by the keyword input interface, so that the generated script information corresponds to the selection result of the learning content and the keyword, then displaying an intelligent learning guide interface of the teaching guidance in response to a generation completion instruction of the teaching script information, and displaying dialogue information of the personalized education learning according to a preset standard database in response to an intelligent learning guide generation instruction of the intelligent learning guide interface, the student can also ask questions according to his actual needs during the learning process, and the display interface can adjust the subsequent guidance and training content according to the questions combined with the preset standard database, so as to generate display content corresponding to the needs of the student to meet the actual needs of the student. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 Data processing method flowchart for the embodiment 1 personalized education learning; Figure 2 Interface schematic diagram for selecting learning basic information of the embodiment 1; Figure 3 Interface schematic diagram for selecting learning theme of the embodiment 1; Figure 4 Interface schematic diagram for selecting learning goal of the embodiment 1; Figure 5 Schematic diagram of the keyword input interface of the embodiment 1; Figure 6 Schematic diagram of the teaching script information display interface of the embodiment 1; Figure 7 Schematic diagram of the intelligent learning guide interface of the embodiment 1; Figure 8 Schematic diagram of the intelligent question and answer interface of the embodiment 1; Figure 9 Schematic diagram of the intelligent question and answer voice interface of the embodiment 1; Figure 10 Schematic diagram of the personalized education learning data processing device structure of the embodiment 2. DETAILED DESCRIPTION

[0015] In order to make the purposes, technical solutions and advantages of the present application clearer, further detailed description will be made to the present application in combination with the accompanying drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and not intended to limit the present application. When the following description refers to the accompanying drawings, the same numbers in different drawings represent the same or similar elements unless otherwise specified. The implementations described in the following exemplary examples do not represent all implementations consistent with the present examples. They are only examples of devices and methods consistent with some aspects of the present examples.

[0016] It can be understood that the terms "first", "second" and the like used in the present application can be used herein to describe various concepts, but unless specifically stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another concept. For example, without departing from the scope of the present examples, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as the first information. Depending on the context, the word "if" as used herein can be interpreted as "when" or "when" or "in response to determining".

[0017] The terms "at least one", "multiple", "each", "any" and the like used in the present application include one, two or more than two, multiple includes two or more than two, each refers to each of the corresponding multiple, and any refers to any one of the multiple.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as understood by a person skilled in the art to which the present application belongs. The terms used herein are only for the purpose of describing the embodiments of the present application and are not intended to limit the present application.

[0019] Before the embodiments of the present application are described in detail, first, some nouns and terms involved in the embodiments of the present application are described, and the nouns and terms involved in the embodiments of the present application are applicable to the following explanations: Artificial intelligence (AI) is a technology science in the field of computer science that studies how to simulate, extend and expand human intelligence. The core goal of artificial intelligence is to enable machines to have intelligent behaviors such as learning, reasoning, perception and language understanding through algorithms, data and computing power, and to realize autonomous or semi-autonomous decision-making in specific fields.

[0020] RAG (Retrieval-Augmented Generation) is a technology framework that combines external knowledge retrieval and generation model, aiming to improve the question answering and generation capabilities of AI models. RAG retrieves relevant information from external knowledge bases (such as documents, web pages, knowledge graphs) and inputs it into the generation model (such as GPT) to generate more accurate and context-rich responses. The essence of RAG is "retrieval augmented generation", which compensates for the knowledge limitations, illusion problems and data security problems of large models (LLM) through InContext Learning.

[0021] Personalized teaching guidance is a reference book that assists teaching materials, composed of knowledge explanations and exercises, aiming to help students consolidate knowledge, deepen understanding, and assist teachers in teaching. The user groups of teaching guidance include students, teachers, and researchers, etc.

[0022] New curriculum standards refer to the new round of teaching specifications and standards formulated by national or local education departments for basic education curriculum, the core of which is to promote educational reform and improve students' comprehensive quality.

[0023] In related technologies, large language models have been applied in teaching guidance. However, the existing teaching guidance based on large language models only displays knowledge to students in a one-way manner based on the set display rules, and cannot adjust the knowledge display content according to the students' needs, making the teaching guidance unable to meet the actual needs of students.

[0024] Therefore, the embodiments of the present application provide a personalized education learning data processing method and device, an electronic device and a storage medium, which can generate display content corresponding to the needs of students to meet the actual needs of students.

[0025] The personalized education learning data processing method provided in the embodiments of the present application relates to the field of artificial intelligence. The personalized education learning data processing method provided in the embodiments of the present application can be applied in a terminal, can be applied in a server, and can also be software running in a terminal or a server. In some embodiments, the terminal can be a smart phone, a tablet computer, a notebook computer, a desktop computer, a smart speaker, a smart watch, a vehicle-mounted terminal, etc., but is not limited thereto; the server end can be configured as an independent physical server, can be configured as a server cluster or a distributed system composed of multiple physical servers, can also be configured as a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDNs, and basic cloud computing services such as big data and artificial intelligence platforms, and the server can also be a node server in a blockchain network; the software can be an application that implements the above method, etc., but is not limited to the above forms.

[0026] The embodiments of the present application will be described below in detail with reference to the accompanying drawings. Embodiment 1

[0027] Referring to Figure 1 An optional flowchart of the personalized education learning data processing method provided by the embodiment is provided, and the method can include but is not limited to steps S110 to S150. Step S110, in response to a personalized education learning start instruction, a learning content selection interface is displayed. Step S120, in response to a selection completion instruction of the learning content selection interface, a keyword input interface is displayed. Step S130, in response to keyword information input by the keyword input interface, teaching script information of a teaching guidance course outline is generated. Step S140, in response to a generation completion instruction of the teaching script information, an intelligent learning interface of teaching guidance is displayed. Step S150, in response to an intelligent learning generation instruction of the intelligent learning interface, dialogue information display of personalized education learning is performed according to a preset standard database.

[0028] It can be understood that the method of the embodiment can be applied to an artificial intelligence and course teaching analysis application platform. When a student enters the platform through a preset account, the personalized education learning guidance operation of the corresponding content can be started by selecting "artificial intelligence learning (AI Tutor)". Specifically, when the personalized education learning guidance is performed, the back end generates the display content of the interface by searching through RAG based on the content of the preset standard database. The content of the preset standard database can be obtained by constructing the content based on the new curriculum standards in advance.

[0029] It can be understood that when the student selects the learning content of the personalized education, it includes but is not limited to learning basic information selection, learning theme selection and learning goal selection. Therefore, in the process of displaying the learning content selection interface in response to the personalized education learning start instruction, the embodiment includes but is not limited to the following steps: 1) In response to the learning basic information selection instruction in the personalized education learning start instruction, a learning basic information selection interface is displayed to perform a learning basic information selection operation, wherein the learning basic information includes subject information, learning age and learning course type. 2) In response to the learning theme selection instruction in the personalized education learning start instruction, a learning theme selection interface is displayed to perform a learning theme selection operation. 3) In response to the learning goal selection instruction in the personalized education learning start instruction, a learning goal selection interface is displayed to perform a learning goal selection.

[0030] Specifically, when the student selects the learning basic information, the method of the embodiment includes but is not limited to the following steps: 1) displaying at least one subject selection item in response to a subject selection instruction of the learning basic information selection instruction; 2) displaying at least one age selection item in response to an age selection instruction of the learning basic information selection instruction; 3) displaying at least one course type selection item in response to a course type selection instruction of the learning basic information selection instruction.

[0031] Referring to Figure 2 When the student clicks the selection box of the "subject" column in the interface, the display interface can send a subject selection instruction to the back end, so that the back end can call the content of the subject selection item corresponding to the selection box based on the instruction and display it in the interface, so that the student can select the subject according to his own needs. The content of the subject selection item includes but is not limited to Chinese, mathematics, English, biology, chemistry, etc. When the student clicks the selection box of the "age" column in the interface, the display interface can send an age selection instruction to the back end, so that the back end can call the content of the age selection item corresponding to the selection box based on the instruction and display it in the interface, so that the student can select the age according to his own needs. The content of the age selection item includes but is not limited to first grade, second grade, third grade, fourth grade, …, third grade of junior high school, etc. When the student clicks the selection box of the "course type" column in the interface, the display interface can send a course type selection instruction to the back end, so that the back end can call the content of the course type selection item corresponding to the selection box based on the instruction and display it in the interface, so that the student can select the course type according to his own needs. The content of the course type selection item includes but is not limited to new course, review course, experiment course, and review course.

[0032] Specifically, after the selection of the learning basic information is completed, when the student clicks the touch control "next step" in the interface, the back end can display the display content of the next interface to facilitate the student to make corresponding selection in the next interface. It can be understood that, after the selection of the learning basic information is completed, the selection and display of the learning theme are performed. The selection and display process of the learning theme includes but is not limited to the following steps: 1) displaying a learning theme selection interface in response to a learning theme selection instruction in the personalized education learning start instruction, so as to display a plurality of learning theme selection items obtained by artificial intelligence expansion in the learning theme selection interface according to the learning basic information selection result; 2) or, in response to a learning theme selection instruction in the personalized education learning start instruction, a learning theme selection interface is displayed to fill in the learning theme information in the learning theme selection interface.

[0033] It can be understood that the learning theme selection interface can be displayed after the backend receives the learning theme selection instruction.

[0034] Referring to Figure 3 The learning theme selection interface can display a plurality of learning theme selection items extended by the artificial intelligence according to the learning basic information selection result in the learning theme selection box. For example, after the learning basic information selects "Chinese, new teaching of fourth grade of primary school", the artificial intelligence can extend "Jingwei filling sea, myth and legend, fighting spirit, perseverance, cultural heritage, national spirit" and other learning theme selection items based on the learning basic information. During the selection process of the interface, the student can delete or retain the learning theme selection items extended by the artificial intelligence. At the same time, when the student thinks that there is no option in the learning theme selection items extended by the artificial intelligence that meets the current needs, the student can also fill in the learning theme information in the filling box corresponding to the learning theme in the learning theme selection interface. Based on this, it can be known that during the learning theme information filling process of the embodiment, the student can select or fill in according to the actual needs, so that the subsequent steps can generate content that meets the actual situation of the student.

[0035] Specifically, after the selection of the learning theme is completed, when the student clicks the touch control "next step" in the interface, the backend can display the display content of the next interface, so that the student can make corresponding selection in the next interface. It can be understood that after the selection of the learning theme is completed, the selection of the learning goal is displayed. The selection and display process of the learning goal includes but is not limited to the following steps: 1) In response to the learning goal selection instruction, display at least one learning stage selection item; 2) In response to the task group selection instruction of the learning goal selection instruction, display at least one task group selection item; 3) In response to the sub-task group selection instruction of the learning goal selection instruction, display at least one sub-task group selection item according to the learning basic information selection result and the learning theme selection result.

[0036] It can be understood that the learning goal selection interface can be displayed after the backend receives the learning goal selection instruction.

[0037] Referring to Figure 4 Since the learning basic information selects "Chinese", the Chinese will be locked in the learning goal selection interface. From Figure 4The interface shown can know that the student selects the learning goal, including but not limited to selecting the learning stage, selecting the task group, and selecting the sub-task group. The selection of these three learning goals can only select the learning stage, or only select the learning stage and the task group, or select all three learning goals. When only the learning stage is selected, the task group and the sub-task group corresponding content are blank items, indicating that all tasks or sub-tasks corresponding to the learning stage can be displayed during the retrieval process. In Figure 4 the embodiment, the learning stage is selected as "the second learning stage (3-4 years old)", the task group is selected as "the basic type learning task group", and the sub-task group is selected as "language and character accumulation and carding". Then, the corresponding content requirements can be displayed in the learning goal selection item in the content requirements. From the above content, it can be known that the student can select the learning goal according to the actual situation, so that the subsequent generated content corresponds to the actual demand.

[0038] It can be understood that after the learning goal is selected in the embodiment, the keyword input interface is displayed, so that the student can select the keyword meeting the actual demand in the interface.

[0039] Referring to Figure 5 , after the learning basic information, the learning theme and the learning goal are set, the keyword input interface displays four fixed keyword input boxes. The four fixed stages include introduction, new teaching, consolidation and summary, and each stage can input keywords. Specifically, the input process of the keyword can be input by the student himself, or the pre-set keyword selection item can be displayed for the student to select and determine. In the embodiment, when the pre-set keyword selection item is displayed, the content of the selection item is associated with the previously selected learning basic information, learning theme and learning goal, so as to meet the actual demand of the student. In addition, the keywords of the keyword input interface of the embodiment can also be blank items, that is, the student does not select or fill in any keyword, so that the subsequent steps can be selected and displayed in a more extensive content.

[0040] It can be understood that the embodiment can generate the teaching script information of the teaching guidance outline based on the keyword selection result of the keyword input interface.

[0041] Referring to Figure 6 , since the selected learning theme in the learning theme includes "Jingwei filling the sea", the embodiment displays the teaching guidance information about Jingwei filling the sea in the teaching script information corresponding to each keyword, so as to make the teaching guidance content more meet the actual demand of the student.

[0042] It can be understood that after obtaining the teaching script information, the embodiment can perform intelligent question and answer operation in the teaching script information of each stage, that is, intelligent learning guidance.

[0043] Referring to Figure 7 In the intelligent learning interface, the intelligent question and answer operation can be performed under the teaching script information of each stage. When the "generate" control behind the teaching script information in the intelligent learning interface is clicked, the back end can call Figure 8 The intelligent question and answer interface shown in the figure displays the dialogue information of personalized education and learning.

[0044] Referring to Figure 8 In the intelligent question and answer interface, the AI teacher will first generate question content to guide the tutoring object to think and interact with the question.

[0045] Specifically, in some embodiments, the process of displaying the dialogue information of personalized education and learning includes but is not limited to the following steps: 1) In response to the intelligent learning generation instruction of the intelligent learning interface, display the dialogue information display interface of personalized education and learning corresponding to the key words corresponding to the intelligent learning generation instruction, and display the first content information corresponding to the learning content selection result in the dialogue information display interface of personalized education and learning according to the preset standard database; 2) In response to the first text question information input by the student in the dialogue information display interface of personalized education and learning, display the second content information corresponding to the first text question information in the dialogue information display interface of personalized education and learning according to the preset standard database.

[0046] In other embodiments, the process of displaying the dialogue information of personalized education and learning includes but is not limited to the following steps: 1) In response to the intelligent learning generation instruction of the intelligent learning interface, display the dialogue information display interface of personalized education and learning corresponding to the key words corresponding to the intelligent learning generation instruction, and display the first content information corresponding to the learning content selection result in the dialogue information display interface of personalized education and learning according to the preset standard database; 2) In response to the voice information input by the student in the dialogue information display interface of personalized education and learning, display the second text question information corresponding to the voice information in the dialogue information display interface of personalized education and learning; 3) In response to the second text question information in the dialogue information display interface of personalized education and learning, display the third content information corresponding to the second text question information in the dialogue information display interface of personalized education and learning according to the preset standard database.

[0047] It can be understood that the student can ask questions in the intelligent question and answer interface based on the questions generated by the AI teacher after thinking. In the process of asking questions, the corresponding question information can be input through text or voice.

[0048] Referring to Figure 9 When the question information is input through voice, the backend of the embodiment converts it into text question information and then generates corresponding interactive information for display, so that the content displayed on the intelligent question and answer interface corresponds to the needs of the student's questions, thereby meeting the actual tutoring needs of the student.

[0049] From the above, the embodiment of the application can provide personalized teaching tutoring for students, that is, it can provide personalized one-on-one training content for students. At the same time, when the student is taking a personalized course, he or she can choose the corresponding age, content and course type according to his or her actual needs, and can also continue to interact with the AI teacher, that is, can input questions through the "click to initiate statement or question" control. Figure 8 The AI teacher (equivalent to the backend) can adjust the subsequent question and answer link according to the input question, generate display content corresponding to the needs of the student, and meet the actual needs of the student. Embodiment 2

[0050] Referring to Figure 10 The embodiment provides a data processing device for personalized education and learning, which comprises: a learning content response module 1010 configured to display a learning content selection interface in response to a personalized education and learning start instruction; a keyword response module 1020 configured to display a keyword input interface in response to a selection completion instruction of the learning content selection interface; a script response module 1030 configured to generate teaching script information of a teaching tutoring course outline in response to keyword information input by the keyword input interface; an intelligent guide learning response module 1040 configured to display an intelligent guide learning interface of teaching tutoring in response to a generation completion instruction of the teaching script information; and a dialogue response module 1050 configured to display dialogue information of personalized education and learning according to a preset standard database in response to an intelligent guide learning generation instruction of the intelligent guide learning interface.

[0051] It can be understood that the content in the above method embodiment is applicable to the device embodiment, the device embodiment specifically realizes the same functions as the above method embodiment, and achieves the same beneficial effects as the above method embodiment. Embodiment 3

[0052] The embodiment also provides an electronic device, which comprises a memory and a processor, wherein the memory stores a computer program; the processor implements the above method when executing the computer program; and the electronic device can be any intelligent terminal including a tablet computer, a vehicle-mounted computer, etc.

[0053] It can be understood that the contents in the above method embodiments are all applicable to the present device embodiments, the present device embodiments specifically implement the functions same as those of the above method embodiments, and achieve the same beneficial effects as those of the above method embodiments. Embodiment 4

[0054] The present embodiment also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the above method.

[0055] It can be understood that the contents in the above method embodiments are all applicable to the present storage medium embodiments, the present storage medium embodiments specifically implement the functions same as those of the above method embodiments, and achieve the same beneficial effects as those of the above method embodiments.

[0056] The present embodiment is not intended to limit the technical solutions provided by the present embodiment, and those skilled in the art can know that, with the evolution of technology and the appearance of new application scenarios, the technical solutions provided by the present embodiment are also applicable to similar technical problems.

[0057] Those skilled in the art can understand that the technical solutions shown in the figures do not constitute a limitation of the present embodiment, and can include more or fewer steps than the figures shown, or combine certain steps, or different steps.

[0058] The device embodiments described above are only schematic, and the units described as separate components can or can not be physically separate, that is, they can be located in one place, or distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the present embodiment.

[0059] Those skilled in the art can understand that all or some steps in the above disclosed method, the function modules / units in the system and the device can be implemented as software, firmware, hardware and their appropriate combinations.

[0060] It should be understood that, in the application, "at least one" means one or more, "multiple" means two or more. "And / or" is used to describe the relationship between the associated objects, which means that there can be three relationships, for example, "A and / or B" can represent three cases: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after it. "At least one of the following" or similar expressions means any combination of these items, including any combination of single or multiple items. For example, at least one of a, b or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0061] In several embodiments provided in the application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only illustrative, for example, the division of the above units is only a logical function division, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0062] The units described above as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed on multiple network units. According to actual needs, part or all of the units can be selected to achieve the purpose of the embodiment scheme.

[0063] In addition, each function unit in each of the above embodiments can be integrated in one processing unit, or each unit can exist physically independently, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software function unit. When the integrated unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application, essentially or in other words, the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes multiple instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in the various embodiments of the present application. The foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various program storage media.

[0064] The preferred examples of the present application are described above with reference to the accompanying drawings, and are not intended to limit the scope of the embodiments of the present application. Any modifications, equivalent replacements and improvements made by those skilled in the art without departing from the scope and essence of the embodiments of the present application shall be within the scope of protection of the claims of the present application.

Claims

1. A data processing method for personalized education learning, comprising entering an artificial intelligence and course teaching analysis application platform through a preset account, and starting a personalized education learning guidance operation of corresponding content, characterized in that, The method comprises the following steps: Step 1: start the personalized education learning instruction, display the learning content selection interface; Step 2: complete the selection instruction of the learning content selection interface, display the keyword input interface; Step 3: input keyword information in the keyword input interface, generate teaching script information of the teaching guidance course outline; Step 4: complete the generation instruction of the teaching script information, display the intelligent learning interface of the teaching guidance; Step 5: complete the intelligent learning generation instruction in the intelligent learning interface, and display the dialogue information of the personalized education learning according to the preset standard database.

2. The data processing method for personalized education learning according to claim 1, characterized in that, The step 1 specifically comprises: 1) in response to the learning basic information selection instruction in the personalized education learning start instruction, the selection operation of the learning basic information is performed in the displayed learning basic information selection interface, and the learning basic information comprises subject information, learning age and learning type; 2) in response to the learning theme selection instruction in the personalized education learning start instruction, the selection operation of the learning theme is performed in the displayed learning theme selection interface; 3) in response to the learning goal selection instruction in the personalized education learning start instruction, the selection operation of the learning goal is performed in the displayed learning goal selection interface.

3. The data processing method for personalized education learning according to claim 2, characterized in that, In response to the learning basic information selection instruction in the personalized education learning start instruction, the selection operation of the learning basic information in the displayed learning basic information selection interface specifically comprises: 1) in response to the subject selection instruction of the learning basic information selection instruction, at least one subject selection item is displayed; 2) in response to the age selection instruction of the learning basic information selection instruction, at least one age selection item is displayed; 3) in response to the course type selection instruction of the learning basic information selection instruction, at least one course type selection item is displayed.

4. The data processing method for personalized education learning according to claim 2, characterized in that, In response to the learning theme selection instruction in the personalized education learning start instruction, the selection operation of the learning theme in the displayed learning theme selection interface specifically comprises: in response to the learning theme selection instruction in the personalized education learning start instruction, in the displayed learning theme selection interface, a plurality of learning theme options obtained by artificial intelligence expansion are displayed according to the learning basic information selection result; or in response to the learning theme selection instruction in the personalized education learning start instruction, the learning theme information is filled in the displayed learning theme selection interface.

5. The data processing method for personalized education learning according to claim 2, characterized in that, In response to the learning goal selection instruction in the personalized education learning start instruction, the learning goal selection in the displayed learning goal selection interface specifically comprises: 1) in response to the learning goal selection instruction, at least one learning stage selection item is displayed; 2) in response to the task group selection instruction of the learning goal selection instruction, at least one task group selection item is displayed; 3) in response to the subtask group selection instruction of the learning goal selection instruction, at least one subtask group selection item is displayed according to the learning basic information selection result and the learning theme selection result.

6. The data processing method for personalized education learning according to claim 1, characterized in that, The step 5 specifically comprises: 1) in response to the intelligent learning generation instruction of the intelligent learning interface, displaying the first content information corresponding to the learning content selection result in the displayed personalized education learning dialogue information display interface corresponding to the keywords of the intelligent learning generation instruction according to the preset standard database; 2) in response to the first text question information input by the student in the personalized education learning dialogue information display interface, displaying the second content information corresponding to the first text question information in the displayed personalized education learning dialogue information display interface according to the preset standard database.

7. The data processing method of personalized education learning according to claim 1 or claim 6, characterized in that, The step 5 further comprises: 1) in response to the intelligent learning generation instruction of the intelligent learning interface, displaying the first content information corresponding to the learning content selection result in the displayed personalized education learning dialogue information display interface corresponding to the keywords of the intelligent learning generation instruction according to the preset standard database; 2) in response to the voice information input by the student in the personalized education learning dialogue information display interface, displaying the second text question information corresponding to the voice information in the personalized education learning dialogue information display interface; 3) in response to the second text question information in the personalized education learning dialogue information display interface, displaying the third content information corresponding to the second text question information in the personalized education learning dialogue information display interface according to the preset standard database.

8. A personalized education and learning data processing device constructed using a personalized education and learning data processing method, characterized in that, The personalized education learning data processing device constructed by the learning content response module, the keyword response module, the script response module, the intelligent learning response module and the dialogue response module, the keyword response module is used for the selection completion instruction of the learning content selection interface, and the keyword input interface is displayed; the script response module is used for responding to the keyword information input by the keyword input interface, and the teaching script information of the teaching guidance course outline is generated; the intelligent learning response module is used for responding to the generation completion instruction of the teaching script information, and the intelligent learning interface of the teaching guidance is displayed; the dialogue response module is used for responding to the intelligent learning generation instruction of the intelligent learning interface, and the dialogue information display of the personalized education learning is carried out according to the preset standard database.

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