CN112085632A - AI intelligent education system based on big data and working method thereof - Google Patents
AI intelligent education system based on big data and working method thereof Download PDFInfo
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Abstract
The invention relates to an AI intelligent education system based on big data and a working method thereof, comprising the following steps: the teaching management system comprises a teaching management system and a cloud data center; the teaching management system includes: the system comprises a course supervision module, a dynamic extraction module and a data management module; the course supervision module is used for acquiring a teaching plan; the dynamic extraction module is used for extracting the teaching behaviors of the teacher; the data management module is used for uploading a teaching progress to the course supervision module, and the course supervision module corresponds the teaching behavior extracted by the dynamic extraction module with the teaching progress uploaded by the data management module and updates a corresponding teaching plan; the teaching management system shares the teaching plan with the cloud data center, and if other teaching management centers need remote teaching, the teaching management system provides teaching behaviors corresponding to the teaching plan to the other teaching management centers through the cloud data center.
Description
Technical Field
The invention relates to the field of education, in particular to an AI intelligent education system based on big data and a working method thereof.
Background
At present, new technologies such as cloud computing, big data, internet of things and mobile computing are emerging continuously, the informatization pace of each industry is accelerated continuously, the overall informatization degree of the society is deepened continuously, and the revolutionary influence of the information technology on education is obvious day by day. With the advancement of strategies, higher requirements are put forward for the construction of colleges and universities and the subject construction thereof, the colleges and universities need to culture tip-drawing innovation talents, the personalized culture is greatly advanced, and the comprehensive quality, the international visual field, the scientific spirit, the entrepreneurship consciousness and the creativity of students are comprehensively improved. Correspondingly, schools need to develop innovation of traditional teaching modes, mode construction needs environment support, and innovative teaching environment construction becomes an important ring.
Nowadays, the integration of information technology and education and teaching and the implementation of intelligent teaching by means of intelligent classrooms have become the macro requirements of national and social development. The intelligent classroom is not only a key medium for realizing education modernization, cultivating innovative talents and creating a learning-type society in the national middle and long-term education planning, but also a core composition content of an education informatization system architecture.
The intelligent school construction of the school has made great efforts, brings great convenience to teachers and students, and meanwhile, the school also realizes that the investment on the classroom construction level is not enough, and the current classroom can not meet the demand in the present day that the informatization high-speed development and talent cultivation mode urgently need to be changed. High-quality teacher resources are scarce, good teaching contents are difficult to share, and when the teacher cannot teach himself, complete teaching cannot be provided in a teaching area.
Disclosure of Invention
The purpose of the invention is as follows:
in order to solve the problems mentioned in the background art, the invention provides an AI intelligent education system based on big data and a working method thereof.
The technical scheme is as follows:
an AI intelligent education system based on big data, comprising: the teaching management system comprises a teaching management system and a cloud data center;
the cloud data center is connected with a plurality of different teaching management systems and is used for sharing teaching data provided by the different teaching management systems;
the teaching management system comprises: the system comprises a course supervision module, a dynamic extraction module and a data management module;
the course supervision module is used for acquiring a teaching plan, acquiring the teaching plan uploaded by a user and supervising the course progress according to the teaching plan;
the dynamic extraction module is used for extracting teaching behaviors of teachers, is arranged in different teaching areas and extracts and stores the teaching behaviors in the teaching areas;
the data management module is used for uploading a teaching progress to the course supervision module, and the course supervision module corresponds the teaching behavior extracted by the dynamic extraction module with the teaching progress uploaded by the data management module and updates a corresponding teaching plan;
the teaching management system shares the teaching plan with the cloud data center, and if other teaching management centers need remote teaching, the teaching management system provides teaching behaviors corresponding to the teaching plan to the other teaching management centers through the cloud data center.
As a preferred mode of the present invention, the teaching management system further includes a playing module, and the playing module is configured to play a set teaching behavior; the teaching behavior comprises images and voice.
As a preferred mode of the present invention, the dynamic extraction module corresponds the teacher to the teaching behavior, and establishes a teacher behavior database.
As a preferable mode of the present invention, the teaching management system further includes a course simulation module, and the course simulation module is configured to simulate teaching by a teacher according to teaching contents and teaching behaviors of the teacher.
As a preferable mode of the present invention, the course simulation module shares teacher teaching simulation through the cloud data center.
A working method of an AI intelligent education system based on big data comprises the following steps:
the course supervision module acquires a teaching plan uploaded by a user and updates the teaching plan in real time;
the dynamic extraction module extracts and stores teaching behaviors of teachers in different teaching areas;
the data management module uploads the teaching progress to the course supervision module;
the course supervision module corresponds the teaching behavior extracted by the dynamic extraction module with the teaching progress uploaded by the data management module and updates the corresponding teaching plan;
in addition, if the teaching management center submits a teaching plan viewing request to the cloud data center, the cloud data center opens teaching plans of other teaching management centers to the teaching management center;
the teaching management center submits remote teaching requests to other teaching management centers through the cloud data center, and then the other teaching management centers provide teaching behaviors corresponding to teaching plans according to the remote teaching requests.
The method comprises the following steps:
the teaching management center acquires teaching behaviors provided by other teaching management centers and outputs the teaching behaviors to the playing module;
the playing module plays the teaching behaviors in the appointed teaching area.
The method comprises the following steps:
the dynamic extraction module establishes a teacher behavior database;
the dynamic extraction module corresponds the independent teachers to the teaching behaviors of the teachers and continuously updates a teacher behavior database.
The method comprises the following steps:
the course simulation module analyzes the teaching behaviors of the teacher behavior database;
and the course simulation module is used for simulating the teaching behavior of the teaching content submitted by the teacher according to the teaching content submitted by the teacher and the teaching behavior of the teacher in the teacher behavior database.
The method comprises the following steps:
the course simulation module shares a teacher behavior database through the cloud data center;
and the teaching management center submits teaching contents to the cloud data center and formulates a teacher, and the cloud data center performs teaching behavior simulation on the submitted teaching contents according to the teaching behaviors of the teacher in the teacher behavior database.
The invention realizes the following beneficial effects:
the invention can share high-quality teaching behaviors, not only can record images in the teaching process, but also can simulate the behaviors of teachers through AI, provides on-site teaching in an unmanned state, effectively utilizes high-quality teacher resources, and can customize the teaching behaviors by submitting teaching contents, thereby effectively expanding the education of schools.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
Fig. 1 is a system connection diagram of an AI intelligent education system based on big data according to the present invention;
fig. 2 is a cloud data center simulation diagram of an AI intelligent education system based on big data according to the present invention;
fig. 3 is a system connection diagram of a second big data-based AI intelligent education system provided by the present invention;
fig. 4 is a system connection diagram of a third big data-based AI intelligent education system provided by the present invention;
FIG. 5 is a flowchart illustrating a working method of the big data based AI intelligent education system according to the present invention;
FIG. 6 is a flow chart of a remote course of a working method of the big data based AI intelligent education system according to the present invention;
FIG. 7 is a playing flow chart of a working method of the big data based AI intelligent education system provided by the present invention;
FIG. 8 is a flow chart of teacher behavior database update of a working method of the big data based AI intelligent education system according to the present invention;
FIG. 9 is a flow chart of course simulation of a working method of the big data based AI intelligent education system according to the present invention;
fig. 10 is a flow chart of simulated course sharing of a working method of the big data based AI intelligent education system according to the present invention.
1. The teaching management system comprises a teaching management system 11, a course supervision module 12, a dynamic extraction module 13, a data management module 14, a playing module 15, a course simulation module 2 and a cloud data center.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments; in the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure; one skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, etc.; in other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale; the same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted; the structures shown in the drawings are illustrative only and do not necessarily include all of the elements; for example, some components may be split and some components may be combined to show one device.
The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The method disclosed by the embodiment corresponds to the system disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the system part for description.
Example one
An AI intelligent education system based on big data, comprising: teaching management system 1, high in the clouds data center 2.
The cloud data center 2 is connected with a plurality of different teaching management systems 1, and the cloud data center 2 is used for sharing teaching data provided by the different teaching management systems 1.
Different schools use different teaching management systems 1, and the teaching management systems 1 exchange and share data through the cloud data center 2.
The teaching management system 1 includes: course supervision module 11, dynamic extraction module 12, and data management module 13.
The course supervision module 11 is used for acquiring a teaching plan, and the course supervision module 11 acquires the teaching plan uploaded by the user and supervises the course progress according to the teaching plan.
The course supervision module 11 acquires and follows up the teaching plan, and the teaching plan supervised by the course supervision module 11 can be used as the content shared with other teaching management systems 1. The follow-up teaching plan can refer to the teaching progress of other schools.
The dynamic extraction module 12 is used for extracting teaching behaviors of teachers, and the dynamic extraction module 12 is arranged in different teaching areas and extracts and stores the teaching behaviors in the teaching areas.
The dynamic extraction module 12 records the teaching process of the teacher, and extracts the dynamics of the teacher in the image. Different teaching areas have different teachers to teach.
The data management module 13 is used for uploading a teaching progress to the course supervision module 11, and the course supervision module 11 corresponds the teaching behavior extracted by the dynamic extraction module 12 to the teaching progress uploaded by the data management module 13, and updates a corresponding teaching plan.
The teaching plan also includes specific courses and corresponding teaching teachers. After the teacher gives lessons, the teaching plan is updated, and the updating is corresponding to the teaching behavior.
The teaching management system 1 shares the teaching plan with the cloud data center 2, and if other teaching management centers need remote teaching, the teaching management system 1 provides teaching behaviors corresponding to the teaching plan to the other teaching management centers through the cloud data center 2.
Through sharing, the teaching behavior corresponding to the teaching plan can be extracted.
Specifically, the course supervision module 11 obtains a teaching plan uploaded by the user, and updates the teaching plan in real time.
The dynamic extraction module 12 extracts and stores teaching behaviors of teachers in different teaching areas.
The data management module 13 uploads the teaching progress to the course supervision module 11.
The course supervision module 11 corresponds the teaching behavior extracted by the dynamic extraction module 12 to the teaching progress uploaded by the data management module 13, and updates the corresponding teaching plan.
In addition, if the teaching management center submits a teaching plan viewing request to the cloud data center 2, the cloud data center 2 opens teaching plans of other teaching management centers to the teaching management center.
The teaching management center submits remote teaching requests to other teaching management centers through the cloud data center 2, and then the other teaching management centers provide teaching behaviors corresponding to teaching plans according to the remote teaching requests.
As a preferred mode of the present invention, the teaching management system 1 further includes a playing module 14, and the playing module 14 is configured to play the set teaching behavior. The teaching behavior comprises images and voice.
The teaching management center acquires teaching behaviors provided by other teaching management centers and outputs the teaching behaviors to the playing module 14.
The playing module 14 plays the teaching behavior in the designated teaching area.
The playing module 14 is arranged in the teaching area, plays the designated teaching behavior, and facilitates sharing courses for different schools.
As a preferred mode of the present invention, the dynamic extraction module 12 corresponds the teacher to the teaching behavior, and establishes a teacher behavior database.
The dynamic extraction module 12 builds a teacher's behavior database.
The dynamic extraction module 12 corresponds the independent teacher with the teaching behavior of the teacher and continuously updates the teacher behavior database.
The teacher behavior database is a behavior database taking the teacher as a search condition, and aims at the simulation behavior of the teacher.
As a preferred mode of the present invention, the teaching management system 1 further includes a course simulation module 15, where the course simulation module 15 is configured to simulate teacher teaching according to teaching contents and teaching behaviors of the teacher.
The course simulation module 15 analyzes the teaching behavior of the teacher behavior database.
The course simulation module 15 performs teaching behavior simulation on the teaching contents submitted by the teacher according to the teaching contents submitted by the teacher and the teaching behaviors of the teacher in the teacher behavior database.
After the teacher submits the teaching content, the course simulation module 15 simulates a teaching behavior of the teacher teaching the teaching content according to the selected teacher.
As a preferred mode of the present invention, the course simulation module 15 shares teacher teaching simulation through the cloud data center 2.
The course simulation module 15 shares the teacher behavior database through the cloud data center 2.
The teaching management center submits teaching contents to the cloud data center 2 and formulates a teacher, and the cloud data center 2 performs teaching behavior simulation on the submitted teaching contents according to the teaching behaviors of the teacher in the teacher behavior database.
Example two
A working method of an AI intelligent education system based on big data comprises the following steps:
the course supervision module 11 obtains the teaching plan uploaded by the user, and updates the teaching plan in real time.
The dynamic extraction module 12 extracts and stores teaching behaviors of teachers in different teaching areas.
The data management module 13 uploads the teaching progress to the course supervision module 11.
The course supervision module 11 corresponds the teaching behavior extracted by the dynamic extraction module 12 to the teaching progress uploaded by the data management module 13, and updates the corresponding teaching plan.
In addition, if the teaching management center submits a teaching plan viewing request to the cloud data center 2, the cloud data center 2 opens teaching plans of other teaching management centers to the teaching management center.
The teaching management center submits remote teaching requests to other teaching management centers through the cloud data center 2, and then the other teaching management centers provide teaching behaviors corresponding to teaching plans according to the remote teaching requests.
The method comprises the following steps:
the teaching management center acquires teaching behaviors provided by other teaching management centers and outputs the teaching behaviors to the playing module 14.
The playing module 14 plays the teaching behavior in the designated teaching area.
The method comprises the following steps:
the dynamic extraction module 12 builds a teacher's behavior database.
The dynamic extraction module 12 corresponds the independent teacher with the teaching behavior of the teacher and continuously updates the teacher behavior database.
The method comprises the following steps:
the course simulation module 15 analyzes the teaching behavior of the teacher behavior database.
The course simulation module 15 performs teaching behavior simulation on the teaching contents submitted by the teacher according to the teaching contents submitted by the teacher and the teaching behaviors of the teacher in the teacher behavior database.
The method comprises the following steps:
the course simulation module 15 shares the teacher behavior database through the cloud data center 2.
The teaching management center submits teaching contents to the cloud data center 2 and formulates a teacher, and the cloud data center 2 performs teaching behavior simulation on the submitted teaching contents according to the teaching behaviors of the teacher in the teacher behavior database.
The above embodiments are merely illustrative of the technical ideas and features of the present invention, and are intended to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the scope of the present invention. All equivalent changes or modifications made according to the spirit of the present invention should be covered within the protection scope of the present invention.
Claims (10)
1. An AI intelligent education system based on big data, comprising: the teaching management system comprises a teaching management system (1) and a cloud data center (2);
the cloud data center (2) is connected with a plurality of different teaching management systems (1), and the cloud data center (2) is used for sharing teaching data provided by the different teaching management systems (1);
the teaching management system (1) includes: the system comprises a course supervision module (11), a dynamic extraction module (12) and a data management module (13);
the course supervision module (11) is used for acquiring a teaching plan, and the course supervision module (11) acquires the teaching plan uploaded by a user and supervises the course progress according to the teaching plan;
the dynamic extraction module (12) is used for extracting teaching behaviors of teachers, and the dynamic extraction module (12) is arranged in different teaching areas and extracts and stores the teaching behaviors in the teaching areas;
the data management module (13) is used for uploading a teaching progress to the course supervision module (11), and the course supervision module (11) corresponds the teaching behavior extracted by the dynamic extraction module (12) with the teaching progress uploaded by the data management module (13) and updates a corresponding teaching plan;
the teaching management system (1) shares the teaching plan with the cloud data center (2), and if other teaching management centers need remote teaching, the teaching management system (1) provides teaching behaviors corresponding to the teaching plan to the other teaching management centers through the cloud data center (2).
2. The AI intelligent education system based on big data according to claim 1, characterized in that the teaching management system (1) further includes a playing module (14), the playing module (14) is used for playing the set teaching behavior; the teaching behavior comprises images and voice.
3. The AI intelligent education system based on big data according to claim 1, wherein the dynamic extraction module (12) corresponds a teacher with a teaching action and creates a teacher action database.
4. The big-data-based AI intelligent education system according to claim 3 characterized in that the teaching management system (1) further includes a course simulation module (15), the course simulation module (15) is used to simulate teacher teaching according to the teaching content and the teaching behavior of the teacher.
5. The big-data-based AI intelligent education system of claim 4 characterized in that the course simulation module (15) shares teacher teaching simulation through the cloud data center (2).
6. The operating method of the big-data based AI intelligent education system according to any one of claims 1 to 5, comprising the steps of:
the course supervision module (11) acquires a teaching plan uploaded by a user and updates the teaching plan in real time;
the dynamic extraction module (12) extracts and stores teaching behaviors of teachers in different teaching areas;
the data management module (13) uploads a teaching progress to the course supervision module (11);
the course supervision module (11) corresponds the teaching behavior extracted by the dynamic extraction module (12) to the teaching progress uploaded by the data management module (13), and updates the corresponding teaching plan;
in addition, if the teaching management center submits a teaching plan viewing request to the cloud data center (2), the cloud data center (2) opens teaching plans of other teaching management centers to the teaching management center;
the teaching management center submits remote teaching requests to other teaching management centers through the cloud data center (2), and then the other teaching management centers provide teaching behaviors corresponding to teaching plans according to the remote teaching requests.
7. The operating method of a big-data-based AI intelligent education system according to claim 6, characterized by comprising the steps of:
the teaching management center acquires teaching behaviors provided by other teaching management centers and outputs the teaching behaviors to the playing module (14);
the playing module (14) plays the teaching behaviors in the appointed teaching area.
8. The operating method of a big-data-based AI intelligent education system according to claim 6, characterized by comprising the steps of:
the dynamic extraction module (12) establishes a teacher behavior database;
the dynamic extraction module (12) corresponds the independent teachers to the teaching behaviors of the teachers and continuously updates a teacher behavior database.
9. The operating method of a big-data-based AI intelligent education system according to claim 8, characterized by comprising the steps of:
the course simulation module (15) analyzes the teaching behaviors of the teacher behavior database;
and the course simulation module (15) is used for simulating the teaching behavior of the teaching content submitted by the teacher according to the teaching content submitted by the teacher and the teaching behavior of the teacher in the teacher behavior database.
10. The operating method of a big-data-based AI intelligent education system according to claim 6, characterized by comprising the steps of:
the course simulation module (15) shares a teacher behavior database through the cloud data center (2);
the teaching management center submits teaching contents to the cloud data center (2) and formulates a teacher, and the cloud data center (2) performs teaching behavior simulation on the submitted teaching contents according to the teaching behaviors of the teacher in the teacher behavior database.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113344754A (en) * | 2021-07-06 | 2021-09-03 | 上海商汤科技开发有限公司 | Teaching plan generation method and device, computer equipment and storage medium |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113344754A (en) * | 2021-07-06 | 2021-09-03 | 上海商汤科技开发有限公司 | Teaching plan generation method and device, computer equipment and storage medium |
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