Teaching agent system based on large scene model

Abstract

The invention relates to a teaching agent system based on a large scene model, and the system comprises a physical layer which comprises a SkillLink workstation for students to log in and carry out the operation training, and the SkillLink workstation records the operation training data and uploads a result file; the operation and maintenance support layer comprises a teaching task management system and a teaching agent, the teaching task management system is provided with a school terminal, a teacher terminal and a student terminal, the school terminal is correspondingly provided with a school account, and the school account can set a teacher account and a student account and configure operation authority by logging in the teaching task management system through the school terminal; the teaching agent performs technical evaluation on the result file uploaded by the SkillLink workstation and associates and sends an evaluation result to a corresponding teacher account and a student account; and the digital layer comprises a background database for storing the result file and the training data and a data statistical system connected with the background database.

Description

Technical Field

[0001] This invention relates to the field of digital teaching technology, specifically a teaching intelligent agent system based on a large-scale picture model. Background Technology

[0002] As a core discipline in majors such as optical engineering, electronic information, and intelligent manufacturing, optoelectronic technology relies heavily on hands-on training. Traditional optoelectronic training teaching models have many technical pain points that are difficult to overcome and can no longer meet the practical training needs of modern vocational and higher education.

[0003] First, traditional optoelectronic training relies heavily on physical optoelectronic equipment and offline manual guidance. Equipment deployment is costly, maintenance is difficult, and the number of students a single device can serve simultaneously is limited. Limited training space and equipment resources hinder large-scale, personalized training. Second, there is a lack of process control. Teachers cannot track students' operation of optoelectronic equipment, optical path construction, parameter debugging, and other complete training processes in real time. They can only make rough judgments based on the final training results, leading to subjective evaluations, inconsistent standards, and an inability to accurately identify students' weaknesses. Third, training data and results management is chaotic. Student training data, operation videos, and training reports are stored in a scattered manner, making it difficult to form a systematic learning archive. Schools and teachers cannot efficiently analyze teaching effectiveness or optimize teaching plans. Finally, existing teaching platforms lack targeted AI-powered intelligent evaluation capabilities. They cannot combine professional standards and operational specifications of optoelectronic training to quantify and objectively score students' practical results, resulting in delayed teaching feedback and hindering the implementation of personalized teaching.

[0004] While there are some digital teaching platforms on the market, most have not been customized for the professional characteristics of optoelectronic training and teaching. They lack deep adaptation to optoelectronic practical workstations and have not integrated artificial intelligence image model to achieve core functions such as image operation recognition, intelligent evaluation of results, and full-domain data statistics. They cannot solve core problems such as practical control, accurate evaluation, and digital management in optoelectronic training and teaching. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a teaching intelligent agent system based on a large-scale picture model. Through a layered architecture design, combined with AI cloud-based assessment and full-domain data statistics, it achieves standardized optoelectronic training operations, intelligent assessment, and digital management. This solves the problems of low practical efficiency, inaccurate assessment, delayed teaching feedback, and low resource utilization in traditional optoelectronic teaching. At the same time, it adapts to the teaching needs of schools, teachers, and students, constructing a closed-loop optoelectronic training and teaching system throughout the entire process.

[0006] A teaching agent system based on a large-scale picture model includes: Physical layer: includes SkillLink workstations, which students can log in to and perform operation training. SkillLink workstations record operation training data and upload result files; Operation and maintenance support layer: This includes a teaching task management system and a teaching intelligence agent. The teaching task management system has a school end, a teacher end, and a student end. The school end is set up with a corresponding school account. The school account can log in to the teaching task management system through the school end to set up teacher accounts and student accounts and configure operation permissions. The teacher account can log in to the teaching task management system through the teacher end to generate teaching tasks and distribute them to the corresponding student accounts. The student account can access the teaching task management system through the SkillLink workstation and perform operation training according to the assigned teaching tasks. The teaching intelligence agent performs technical evaluation on the result files uploaded by the SkillLink workstation and associates and sends the evaluation results to the corresponding teacher account and student account. Digital Layer: This includes a backend database that stores output files and training data, as well as a data statistics system that connects to the backend database. The backend database provides reference data for technical evaluation of the teaching agent, and the data statistics system can aggregate the output files uploaded by each student account and generate corresponding learning profiles and log files.

[0007] Furthermore, the SkillLink workstation is equipped with an image acquisition module for capturing images and training data of students' operation training process.

[0008] Furthermore, the backend database also stores operation demonstration videos. Teachers can associate the corresponding operation demonstration videos with their accounts when generating teaching tasks, and students can watch the operation demonstration videos through the SkillLink workstation before conducting operation training.

[0009] Furthermore, the teaching task management system includes a basic task section and an advanced task section. The basic task section contains basic teaching tasks from level 1 to 70, while the advanced task section contains advanced teaching tasks from level 71 to 100. Students can access the corresponding task section after their accounts are verified.

[0010] Furthermore, the student end features: Personal Authentication Section: Log in to authenticate your SkillLink workstation to automatically receive teaching assignments; Learning and Training Section: Access the teaching task management system to obtain the teaching task content that needs to be performed; Results submission section: Generate results files from the training data recorded on the SkillLink workstation and upload them to the teaching AI. Feedback receiving section: Receives evaluation results distributed by the teaching intelligence agent; Archives Management Section: Connects to the backend database and data statistics system to obtain corresponding learning archives and log files.

[0011] Furthermore, the teacher's end includes: Teaching and Training Management Section: Access the teaching task management system to generate and publish teaching tasks to students, and view the real-time progress of associated students; Data viewing and evaluation module: Connects to the backend database and data statistics system, obtains the learning files and log files of the associated students, generates overview charts, receives evaluation results issued by the teaching agent, and develops personalized teaching plans based on the data; Support and review section: View and analyze student operation training data and results files to assist in classroom review and adjustment of teaching plans.

[0012] Furthermore, the school has the following features: System Deployment and Authorization Section: Authenticate SkillLink workstations, configure and manage access permissions for teacher and student accounts, and set up associations between student and teacher accounts; Data monitoring and statistics module: Connects to the backend database and data statistics system to view data for all teacher and student accounts, and to collect statistics on student learning activity and device usage records; Compliance and Records Management: Export teaching data as evidence for institutional accreditation and government reporting; record equipment usage logs; manage and view student learning records for grade assessment and competition eligibility.

[0013] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention builds a dedicated optoelectronic training digital teaching platform based on an AI-powered large-scale model, adopting a three-layer collaborative architecture of physical layer, operation and maintenance support layer, and digital layer to achieve digital and intelligent closed-loop management of the entire optoelectronic training process. Relying on the AI-powered large-scale model, a cloud-based intelligent evaluation system is constructed. Combined with professional standards and quantitative indicators for optoelectronic training, the system automatically and multidimensionally evaluates students' practical processes and output documents, generating accurate evaluation results and improvement suggestions in real time. It tracks students' weaknesses in practical operations throughout the process, achieving real-time feedback and unified evaluation standards, effectively improving the accuracy of teaching evaluation. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a schematic diagram of the system structure of the present invention.

[0016] Figure 2 This is a schematic diagram of the system structure for the student side of this invention.

[0017] Figure 3 This is a schematic diagram of the system structure of the teacher's side in this invention.

[0018] Figure 4 This is a schematic diagram of the system structure at the school end of this invention. Detailed Implementation

[0019] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided.

[0020] Please see Figures 1-4 A teaching intelligent agent system based on a large-scale image model is applied to optoelectronic training scenarios. Its core comprises three main layers: physical layer 1, operation and maintenance support layer 2, and digital layer 3. These layers collaborate and exchange data to jointly complete the entire process of equipment operation, task distribution, intelligent evaluation, data storage, and statistical analysis in optoelectronic training. Specifically: The core of Physical Layer 1 is the SkillLink Workstation 4, used for optoelectronic training. It serves as the terminal device for students to conduct optoelectronic practical training, specifically designed for training scenarios such as optoelectronic equipment operation, optical path debugging, optoelectronic parameter detection, and the creation of optoelectronic training results. It is compatible with various optoelectronic training equipment and operational procedures. Students log in to the SkillLink Workstation 4 with a dedicated account to complete the entire optoelectronic practical training process. The workstation has real-time data acquisition and uploading capabilities, recording core data from the student's optoelectronic operation training, including operation steps, parameter debugging values, operation duration, and optical path setup status. It automatically organizes the training data into standardized result files and uploads them synchronously to the cloud, providing raw data support for subsequent AI evaluation.

[0021] Furthermore, the SkillLink workstation 4 has a built-in image acquisition module that can specifically capture images of students' optoelectronic operation training process, including visual data such as optoelectronic equipment debugging actions, optical path construction details, and instrument operation specifications. At the same time, it can simultaneously acquire corresponding quantitative training data, realizing "video + data" dual recording of the practical operation process, completely restoring the entire student training process, which is convenient for subsequent review, evaluation and teaching evaluation.

[0022] Operation and maintenance support layer 2 is the core control and evaluation module of the platform, including two core components: teaching task management system 5 and teaching intelligent agent 6. It realizes full-process control of teaching tasks and intelligent evaluation of training results. The teaching task management system 5 has three ports: school end 7, teacher end 8, and student end 9, which are adapted to the operation permissions and functional requirements of different roles.

[0023] The teaching task management system 5 adopts a hierarchical account control model: the school terminal 7 corresponds to a dedicated school management account. After logging into the system through the school terminal 7, the administrator can perform operations such as batch creation of teacher accounts and student accounts, permission configuration, and account binding. At the same time, the administrator can configure the access permissions and training resource access permissions of the SkillLink workstation 4 to achieve unified deployment and management of the platform and training equipment. After logging into the system through the teacher terminal 8, the teacher can customize and generate basic optoelectronic training tasks, advanced optoelectronic training tasks, and special assessment tasks based on the optoelectronic teaching syllabus, and accurately distribute them to the corresponding classes or individual student accounts. The teacher can also view the student's training progress and operation status in real time. The student account logs in through the student terminal 9 via the SkillLink workstation 4, obtains the assigned optoelectronic teaching tasks with one click, and conducts standardized practical training according to the task requirements.

[0024] The teaching intelligence agent 6 is built on a large-scale AI landscape model and is deeply adapted to the professional evaluation standards of optoelectronic training. It receives training results files, operation process videos and training data uploaded by SkillLink workstation 4. According to optoelectronic operation specifications, result qualification standards and operation standardization indicators, it conducts fully automatic and quantitative technical evaluation, generates an evaluation report containing scores, deduction points and improvement suggestions, and synchronously sends the evaluation results to the corresponding teacher accounts and student accounts to achieve real-time synchronization and two-way feedback of evaluation results.

[0025] The digital layer 3 is responsible for the storage, retrieval, and statistical analysis of data across the entire platform, including the backend database 10 and the data statistics system 11. The two components are interconnected to achieve closed-loop data management.

[0026] The backend database 10 is a large-capacity distributed storage module, specifically designed to store all data related to optoelectronic training, including student-uploaded training results files, operational training data, and process video materials. It also pre-stores standardized optoelectronic operation demonstration videos, training specification documents, and detailed assessment standards, providing unified technical evaluation reference data and standards for the teaching intelligent agent 6, ensuring objective, professional, and consistent evaluation results. When generating optoelectronic teaching tasks, teacher accounts can directly associate and match corresponding operation demonstration videos. Before conducting practical training, students can watch the demonstration videos in advance through the SkillLink workstation 4 to master optoelectronic operation specifications and key training points, improving training efficiency.

[0027] The data statistics system 11 is connected to the backend database 10 in real time. It can automatically summarize the training results, training data and evaluation results uploaded by each student account. According to the dimensions of individual students, classes and schools, it generates exclusive learning files and standardized log files. The learning files fully record the student's optoelectronic training situation throughout the entire cycle, and the log files record detailed data such as equipment use, operation procedures and evaluation records, providing data support for teaching analysis, performance evaluation and competition selection.

[0028] The Teaching Task Management System 5 is specifically designed with basic and advanced task modules to meet the tiered training needs of optoelectronic teaching: the basic task module contains 1-70 levels of basic optoelectronic teaching tasks, covering introductory training content such as optoelectronic equipment recognition, basic optical path construction, and simple parameter detection, suitable for beginners; the advanced task module contains 71-100 levels of advanced optoelectronic teaching tasks, covering advanced content such as complex optical path debugging, precise measurement of optoelectronic parameters, and comprehensive optoelectronic training projects. Student accounts must pass the corresponding ability certification assessment before they can unlock access to the corresponding level of task module, realizing tiered and progressive optoelectronic teaching.

[0029] Student Terminal 9 serves as the core portal for student practical training, featuring five dedicated functional modules to meet the needs of the entire optoelectronic training process: Personal Authentication Section 12: Complete account and password login and SkillLink workstation 4 hardware authentication. The system will automatically match the corresponding teaching tasks and training permissions to avoid account mixing and device mismatch. Learning and Training Section 13: One-click access to the teaching task management system 5, quickly obtain optoelectronic teaching task content, demonstration videos, and practical training specifications, and carry out practical training combining online and offline methods; Submission Section 14: Automatically generate standardized result files from the operation training data and process images recorded by SkillLink workstation 4, and upload them to the teaching AI 6 with one click, without the need for manual organization; Feedback Receiving Section 15: Receive evaluation results and improvement suggestions from the teaching AI 6 in real time, quickly identify weaknesses in your own operation, and optimize training accordingly; File Management Section 16: Directly connects to the backend database 10 and data statistics system 11, allowing users to view their personal optoelectronic training learning files, historical evaluation records, and training logs at any time, and independently review their learning outcomes.

[0030] Teacher App 8 is specifically designed for teaching management, featuring three core functional modules to achieve full-process control over teaching: Teaching and Training Management Module 17: Quickly generate, edit, and publish various optoelectronic teaching tasks, accurately distribute them to target students, view the training progress and operation status of associated students in real time, and provide remote reminders and guidance to students who are lagging behind. Data Viewing and Evaluation Section 18: Connects the backend database 10 and the data statistics system 11 to batch obtain the learning files, log files and evaluation results of the associated students, automatically generate a class training effectiveness overview chart, and combine AI evaluation data to develop personalized optoelectronic teaching plans to achieve individualized teaching. Support and Review Section 19: Access student optoelectronic operation process videos, training data and result files, deeply analyze student operation problems, assist classroom review and practical training review, flexibly adjust teaching plans and practical training focus, and improve teaching quality.

[0031] School Terminal 7, as the highest management portal of the platform, is responsible for overall control and data coordination, and consists of three core modules: System Deployment and Authorization Section 20: Complete batch authentication and access management of SkillLink workstation 4, uniformly configure access permissions and training resource permissions for teacher accounts and student accounts, establish the association and binding between student accounts and teacher accounts, and achieve a clear division of teaching responsibilities; Data monitoring and statistics module 21: Fully access data from the backend database 10 and data statistics system 11, view the practical training data of all teachers and students in the school, and collect statistics on core indicators such as student learning activity, equipment usage frequency, practical training completion rate, and equipment failure records to understand the overall progress of optoelectronic teaching. Compliance and Records Management Section 22: One-click export of standardized teaching data and training records, which can be directly used as valid evidence for institutional professional certification, teaching reports from education departments, and skills competition qualification certification. The entire process records equipment usage logs and teaching logs, standardizing teaching management. At the same time, it can rely on student learning records to complete grade evaluation and skill level certification, realizing the standardization of teaching management.

[0032] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A teaching intelligent agent system based on a large-scale picture model, characterized in that, include: Physical layer: This includes a SkillLink workstation, which allows students to log in and perform operational training. The SkillLink workstation records operational training data and uploads result files. Operation and maintenance support layer: This includes a teaching task management system and a teaching intelligence agent. The teaching task management system has a school end, a teacher end, and a student end. The school end is set up with a corresponding school account. The school account can log in to the teaching task management system through the school end to set up teacher accounts and student accounts and configure operation permissions. The teacher account can log in to the teaching task management system through the teacher end to generate teaching tasks and distribute them to the corresponding student accounts. The student account can access the teaching task management system through the SkillLink workstation and perform operation training according to the assigned teaching tasks. The teaching intelligence agent performs technical evaluation on the result files uploaded by the SkillLink workstation and associates and sends the evaluation results to the corresponding teacher account and student account. Digital Layer: This includes a backend database that stores output files and training data, as well as a data statistics system that connects to the backend database. The backend database provides reference data for technical evaluation of the teaching agent, and the data statistics system can aggregate the output files uploaded by each student account and generate corresponding learning profiles and log files.

2. The teaching intelligent agent system based on a large-scale picture model according to claim 1, characterized in that, The SkillLink workstation is equipped with an image acquisition module, which is used to capture images and training data of students' operation training process.

3. The teaching intelligent agent system based on a large-scale picture model according to claim 1, characterized in that, The backend database also stores operation demonstration videos. Teachers can associate the corresponding operation demonstration videos when generating teaching tasks, and students can watch the operation demonstration videos through the SkillLink workstation before conducting operation training.

4. The teaching intelligent agent system based on a large-scale picture model according to claim 1, characterized in that, The teaching task management system has a basic task section and an advanced task section. The basic task section contains basic teaching tasks for levels 1 to 70, and the advanced task section contains advanced teaching tasks for levels 71 to 100. Students can access the corresponding task section after their accounts are verified.

5. The teaching intelligent agent system based on a large-scale picture model according to claim 1, characterized in that, The student terminal includes: Personal Authentication Section: Log in to authenticate your SkillLink workstation to automatically receive teaching assignments; Learning and Training Section: Access the teaching task management system to obtain the teaching task content that needs to be performed; Results submission section: Generate results files from the training data recorded on the SkillLink workstation and upload them to the teaching AI. Feedback receiving section: Receives evaluation results distributed by the teaching intelligence agent; Archives Management Section: Connects to the backend database and data statistics system to obtain corresponding learning archives and log files.

6. The teaching intelligent agent system based on a large-scale picture model according to claim 1, characterized in that, The teacher's end has the following features: Teaching and Training Management Section: Access the teaching task management system to generate and publish teaching tasks to students, and view the real-time progress of associated students; Data viewing and evaluation module: Connects to the backend database and data statistics system, obtains the learning files and log files of the associated students, generates overview charts, receives evaluation results issued by the teaching agent, and develops personalized teaching plans based on the data; Support and review section: View and analyze student operation training data and results files to assist in classroom review and adjustment of teaching plans.

7. The teaching intelligent agent system based on a large-scale picture model according to claim 1, characterized in that, The school has the following features: System Deployment and Authorization Section: Authenticate SkillLink workstations, configure and manage access permissions for teacher and student accounts, and set up associations between student and teacher accounts; Data monitoring and statistics module: Connects to the backend database and data statistics system to view data for all teacher and student accounts, and to collect statistics on student learning activity and device usage records; Compliance and Records Management: Export teaching data as evidence for institutional accreditation and government reporting; record equipment usage logs; manage and view student learning records for grade assessment and competition eligibility.

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