CN109685692A - A kind of noninductive acquisition and analysis system of various dimensions student learning behavior - Google Patents
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Abstract
The invention discloses a kind of noninductive acquisition systems of various dimensions student learning behavior, including server, the server internal is equipped with central processing unit, the central processing unit connecting pin be equipped with classroom listen to the teacher effect data acquisition module, with hall practice data acquisition module and work data acquisition module；The present invention also provides a kind of noninductive analysis system of various dimensions student learning behavior, the various dimensions Learning behavior analyzing according to classroom listen to the teacher effect data acquisition module, with hall practice data acquisition module and work data acquisition module acquisition three dimension datas by formula calculate analyzed.The present invention utilizes the technologies such as camera, Internet of Things, artificial intelligence and big data, respectively from office coaching, with the learning behavior data of three dimension acquisition students of hall practice and homework, and the tissue and analysis method of data are described, it finally can be realized the students ' behavior data collection and analysis of comprehensive various dimensions.
Description
Technical field
The present invention relates to student's learning behavior collection analysis technical field, in particular to a kind of various dimensions student learning behavior
Noninductive acquisition and analysis system.
Background technique
Patent CN102663347A proposes that a kind of student's learning behavior acquires and analysis system and its method.It is only related in method
And the mobile data of student, such as run, jump, walk, shake action behavior and behavior time of origin, tie course table analysis student
Learning state.The information category that the patent is related to is single, only accounts for movement and temporal information in students'learning.
Patent CN104992479A and CN106023013A propose a kind of students ' behavior analysis system and method, be related to using
RFID, face Work attendance device record student realize the position data acquisition of student in the disengaging time in specific place in the school etc..
These data help to manage, and belong to one kind of learning behavior data, but are associated with less with the achievement of student, are suitable only for student
Daily management.
Patent CN106023012A propose it is a kind of can in acquisition time section student's physiological parameter equipment, physiology is bent
Line and achievement curve fitting propose behavior recommendation.But how to extract effective physiological data and analyze the correlation with achievement
It is a big difficulty, validity is not yet learnt.
Patent CN108022057A proposes a kind of algorithm based on more minimum support correlation rules, can determine study row
For in data with the associated learning behavior data of achievement rise and fall.Although this is a kind of common associated data analysis method,
But do not illustrate how data collect in patent, how to store and quantify, those skilled in the art are difficult to realize the reality in patent
Case is applied, and this association rule algorithm applicability is poor, or even not as good as common principal component analytical method.
Finally, 207406695 U of special train CN proposes a kind of device for students ' behavior analysis and acquisition system, include
Liquid crystal display panel, button, various kinds of sensors, wireless communication apparatus etc., it is seen that adopting for many information may be implemented in present technology
Collection.But existing patent focuses on student's location information, movement, in the acquisition of residence time mostly, and therefrom analyzes
Some data relevant to student's body development.The pass for having a small amount of patent that above- mentioned information is utilized to analyze it with student performance by force
Connection, effect are necessarily undesirable.It is generally known that learning behavior is a kind of high-purity mental activity, relate generally to that classroom pays attention to the class recognizes
True degree, to the degree of understanding of awarded knowledge and the flexible Application ability of knowledge point.The assessment of these information obviously can not pass through
Traditional, single internet of things equipment acquisition, and more methods and apparatus should be utilized, to the number with learning data highlights correlations
According to being acquired, to realize real learning behavior data analysis.
Therefore, the noninductive acquisition and analysis system for inventing a kind of various dimensions student learning behavior have very much to solve the above problems
It is necessary.
Summary of the invention
The purpose of the present invention is to provide a kind of noninductive acquisition of various dimensions student learning behavior and analysis systems, pass through benefit
With technologies such as camera, Internet of Things, artificial intelligence and big datas, respectively from office coaching, with hall practice and homework three
Dimension acquires the learning behavior data of student, and describes the tissue and analysis method of data；Wherein camera, face and posture
Grasp situation in the knowledge point that identification, speech recognition technology are used to record during student attends class；Equipment of answering is for recording classroom
With the answer of hall problem；Camera photo taking type operation identification technology and online electronic exam pool are used to record the handling situations of student,
It can be realized the students ' behavior data collection and analysis of comprehensive various dimensions, finally to solve mentioned above in the background art ask
Topic.
To achieve the above object, the invention provides the following technical scheme: a kind of the noninductive of various dimensions student learning behavior is adopted
Collecting system, including server, the server internal are equipped with central processing unit, and the central processing unit connecting pin is listened equipped with classroom
Class effect data acquisition module practices data acquisition module and work data acquisition module with hall；
Classroom effect data acquisition module of listening to the teacher includes face identification system and normality recording and broadcasting system, the recognition of face system
Output end of uniting is equipped with data processing unit, and the normality recording and broadcasting system output end is equipped with voice recognition unit, the speech recognition
Unit output end is equipped with scanning element and neural network unit, data processing unit, scanning element and the output of neural network unit
Database of holding and listen to the teacher connection；
The voice recognition unit is used to convert the voice of normality recording and broadcasting system recorded broadcast to word sequence, and uses scanning element
Classify with neural network unit to word sequence, obtained knowing for lecture contents in the period with x minutes for time window
Know point；
The data processing unit is used to the movement of each student is analyzed, using just using face recognition technology identification student id
Often movement number is divided by all acting numbers, the normal behaviour accounting in available student's time window, and then in cooperating and giving lessons
Hold knowledge point and carry out behavior evaluation of listening to the teacher, the scoring event of each student is stored as unit of student respectively to database of listening to the teacher
It is interior；
Described to include classroom instruction equipment and answer equipment with hall practice data acquisition module, the equipment output end of answering is equipped with
Unit is read and made comments, equipped with electronic exam pool, the unit output end of reading and making comments is equipped with hall practice database for the unit connecting pin of reading and making comments；
The answer reading and making comments unit and submitting for receiving equipment of answering, receiving after answer can be with locating students id, and according to electricity
Crosshead library determines knowledge point, is corrected errors according to student's answer and determines the scoring event of the knowledge point, practiced on the class of each student
Point situation is stored as unit of student respectively in hall practice database；
The work data acquisition module includes homework identification module, the homework identification module connection electronics topic
Library, the homework identification module output end are equipped with homework database；
The homework identification module is used to fulfil assignment in student and after mobile phone photograph uploads operation, utilizes artificial intelligence
Technology identification homework is corrected errors, and matches relevant knowledge point by electronic exam pool, after judging that answer is corrected errors, determines that this is known
Know the scoring event of point, the operation scoring event of each student is stored as unit of student respectively to homework database.
Preferably, the face identification system connecting pin is equipped with camera, and the camera is installed on inside classroom, is used for
Shooting identification student and the posture movement for identifying operation, and continuing to identify student on this basis of taking pictures, such as come back, are low
Head sleeps, stands up and other little tricks.
Preferably, the equipment of answering is specially the Electronic school badges or RFID answer card of button.
Preferably, the database of listening to the teacher, practicing with hall database and homework database output end, to be equipped with score total
Database.
On the other hand, the present invention also provides a kind of noninductive analysis system of various dimensions student learning behavior, the multidimensional
Degree Learning behavior analyzing according to classroom listen to the teacher effect data acquisition module, with hall practice data acquisition module and work data acquisition
Three dimension datas of module acquisition are calculated as a fixed value by formula, and one of student std is for a knowledge point
The score of kp are as follows:
Wherein L is that classroom is listened to the teacher effect score, and Q is to practice score on class, and H is homework score, above-mentioned score whole value
Between 0-1, weighting parameters, therefore,It is recommended that
Value 0.3,0.3,0.4；
It listens to the teacher the calculation method of effect score L in classroom are as follows:
Wherein p is listen to the teacher conscientious degree of the student in this knowledge point, is obtained according to regular event time/everything time,
Value range [0,1]；
Practice effect score on class are as follows:
Wherein x is that correctly the answer number of problem of student updates x=x+1, when student's mistake is answered when student correctly answers
X=x*0.7 is updated, wherein 1 and 0.7 is proposed parameter, Tuning function image aspects are used, should macroscopic view broad understanding；
Practice in operation practice effect score and class identical:
Wherein x is student std by correctly answering a question belonging to camera system or the collected knowledge point kp of electronic exam pool
The number of topic updates x=x+1 when student correctly answers, and x=x*0.7 is updated when student's mistake is answered, wherein 1 and 0.7 is
Proposed parameter, Tuning function image aspects use, should macroscopic view broad understanding；
Finally, each knowledge point kp of student std can Dynamic Maintenance in daily teaching.
Technical effect and advantage of the invention:
The present invention using the technologies such as camera, Internet of Things, artificial intelligence and big data, respectively from office coaching, with hall practice and
The learning behavior data of three dimension acquisition students of homework, and describe the tissue and analysis method of data；Wherein image
Grasp situation in the knowledge point that head, face and gesture recognition, speech recognition technology are used to record during student attends class；It answers equipment
For recording classroom with the answer of hall problem；Camera photo taking type operation identification technology and online electronic exam pool are for recording student
Handling situations, finally can be realized the students ' behavior data collection and analysis of comprehensive various dimensions.
Detailed description of the invention
Fig. 1 is whole topological diagram of the invention.
Fig. 2 is overall flow figure of the invention.
Fig. 3 is of the invention listen to the teacher effect and regular event proportion function figure.
Fig. 4 is class-exercise and operation and topic correct number functional arrangement of the invention.
In figure: effect data acquisition module, 4 are listened to the teacher with hall practice data acquisition in 1 server, 2 central processing units, 3 classrooms
Module, 5 work data acquisition modules.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
Embodiment 1:
A kind of noninductive acquisition system of various dimensions student learning behavior according to shown in Fig. 1-4, including server 1, the service
Inside device 1 be equipped with central processing unit 2,2 connecting pin of central processing unit be equipped with classroom listen to the teacher effect data acquisition module 3, with
Hall practice data acquisition module 4 and work data acquisition module 5；
The classroom listen to the teacher effect data acquisition module 3 include face identification system and normality recording and broadcasting system, the recognition of face
System output is equipped with data processing unit, and the normality recording and broadcasting system output end is equipped with voice recognition unit, and the voice is known
Other unit output end is equipped with scanning element and neural network unit, and data processing unit, scanning element and neural network unit are defeated
Outlet is connect with database of listening to the teacher；
The voice recognition unit is used to convert the voice of normality recording and broadcasting system recorded broadcast to word sequence, and uses scanning element
Classify with neural network unit to word sequence, obtained knowing for lecture contents in the period with x minutes for time window
Know point；
The data processing unit is used to the movement of each student is analyzed, using just using face recognition technology identification student id
Often movement number is divided by all acting numbers, the normal behaviour accounting in available student's time window, and then in cooperating and giving lessons
Hold knowledge point and carry out behavior evaluation of listening to the teacher, the scoring event of each student is stored as unit of student respectively to database of listening to the teacher
It is interior；
Described to include classroom instruction equipment and equipment of answering with hall practice data acquisition module 4, the equipment output end of answering is set
Unit is read and made comments, equipped with electronic exam pool, the unit output end of reading and making comments is equipped with hall practice data for the unit connecting pin of reading and making comments
Library；
The answer reading and making comments unit and submitting for receiving equipment of answering, receiving after answer can be with locating students id, and according to electricity
Crosshead library determines knowledge point, is corrected errors according to student's answer and determines the scoring event of the knowledge point, practiced on the class of each student
Point situation is stored as unit of student respectively in hall practice database；
The work data acquisition module 5 includes homework identification module, the homework identification module connection electronics topic
Library, the homework identification module output end are equipped with homework database；
The homework identification module is used to fulfil assignment in student and after mobile phone photograph uploads operation, utilizes artificial intelligence
Technology identification homework is corrected errors, and matches relevant knowledge point by electronic exam pool, after judging that answer is corrected errors, determines that this is known
Know the scoring event of point, the operation scoring event of each student is stored as unit of student respectively to homework database；
A kind of noninductive analysis system of various dimensions student learning behavior, the various dimensions Learning behavior analyzing are listened to the teacher effect according to classroom
Fruit data acquisition module 3 leads to three dimension datas that hall practice data acquisition module 4 and work data acquisition module 5 acquire
It crosses formula and is calculated as a fixed value, score of one of student std for a knowledge point kp are as follows:
Wherein L is that classroom is listened to the teacher effect score, and Q is to practice score on class, and H is homework score, above-mentioned score whole value
Between 0-1, weighting parameters, therefore,It is recommended that
Value 0.3,0.3,0.4；
It listens to the teacher the calculation method of effect score L in classroom are as follows:
Wherein p is listen to the teacher conscientious degree of the student in this knowledge point, is obtained according to regular event time/everything time,
Value range [0,1]；
Practice effect score on class are as follows:
Wherein x is that correctly the answer number of problem of student updates x=x+1, when student's mistake is answered when student correctly answers
X=x*0.7 is updated, wherein 1 and 0.7 is proposed parameter, Tuning function image aspects are used, should macroscopic view broad understanding；
Practice in operation practice effect score and class identical:
Wherein x is student std by correctly answering a question belonging to camera system or the collected knowledge point kp of electronic exam pool
The number of topic updates x=x+1 when student correctly answers, and x=x*0.7 is updated when student's mistake is answered, wherein 1 and 0.7 is
Proposed parameter, Tuning function image aspects use, should macroscopic view broad understanding；
Finally, each knowledge point kp of student std can Dynamic Maintenance in daily teaching.
By practicing from office coaching, with hall respectively using technologies such as camera, Internet of Things, artificial intelligence and big datas
The learning behavior data of student are acquired with three dimensions of homework, and describe the tissue and analysis method of data；Wherein take the photograph
As situation is grasped in the knowledge point that head, face and gesture recognition, speech recognition technology are used to record during student attends class；It answers and sets
Record classroom is ready for use on the answer of hall problem；Camera photo taking type operation identification technology and online electronic exam pool are learned for recording
Raw handling situations finally can be realized the students ' behavior data collection and analysis of comprehensive various dimensions.
Embodiment 2:
The face identification system connecting pin is equipped with camera, and the camera is installed on inside classroom, for shooting cognometrics
The raw and posture movement for identifying operation, and continuing to identify student on this basis of taking pictures, such as comes back, bows, sleeps, stands up
With other little tricks；
The equipment of answering is specially the Electronic school badges or RFID answer card of button；
The database of listening to the teacher practices database and homework database output end equipped with total points according to library with hall.
Working principle of the present invention:
Referring to Figure of description 1-4, effect data acquisition module 3 is listened to the teacher when acquiring data in classroom, the content of classroom oral account,
It is converted into word sequence by voice recognition unit, is classified using scanning element and neural network unit to word sequence,
The knowledge point in the period is obtained as unit of x minutes, teacher can also pass through knowing in 1 manual setting current time of server
Know point, by the normality recording and broadcasting system being arranged in classroom, periodically scans student in classroom, identified using face recognition technology
Individual students, and continue to identify the posture movement of student on this basis, it such as comes back, bow, sleeping, standing up, other little tricks
Deng, after a class, movement statistics is carried out respectively to the student that range is told about in each knowledge point, using regular event number divided by
All movement numbers, scoring event of the available student to the knowledge point in learning process, the at this time score of each student
Situation is stored as unit of student respectively to listening to the teacher in database；
When class acquires data with hall practice data acquisition module 4, on class, teacher proposes problem using classroom instruction equipment, it is desirable that
Student answers at scene, and result of answering is fed back by carry-on the equipment such as Electronic school badges with button, RFID answer card of student, is
System can be with locating students id after receiving answer, and determines knowledge point according to electronic exam pool, is corrected errors according to student's answer and determines that this is known
Know the scoring event of point, the scoring event of each student is stored as unit of student respectively in hall practice database；
When work data acquisition module 5 acquires data, after student fulfils assignment, operation can be uploaded by mobile phone photograph, utilized
Homework identification module artificial intelligence identification homework is corrected errors, and matches relevant knowledge point by electronic exam pool, is learned
Life is answered by electronic exam pool using computer equipment, then can be directly realized by and read and make comments, and is obtained knowledge point and is grasped situation；
Finally listen to the teacher database, with hall practice database and homework databases storage three dimension datas summarize to
Divide total Database, and calculated by various dimensions Learning behavior analyzing system according to calculation formula, finally be can be realized comprehensive
The students ' behavior data collection and analysis of various dimensions.
Finally, it should be noted that the foregoing is only a preferred embodiment of the present invention, it is not intended to restrict the invention,
Although the present invention is described in detail referring to the foregoing embodiments, for those skilled in the art, still may be used
To modify the technical solutions described in the foregoing embodiments or equivalent replacement of some of the technical features,
All within the spirits and principles of the present invention, any modification, equivalent replacement, improvement and so on should be included in of the invention
Within protection scope.
Claims (5)
1. a kind of noninductive acquisition system of various dimensions student learning behavior, including server (1), it is characterised in that: the service
Central processing unit (2) are equipped with inside device (1), central processing unit (2) connecting pin is equipped with classroom and listens to the teacher effect data acquisition mould
Block (3) practices data acquisition module (4) and work data acquisition module (5) with hall；
Classroom effect data acquisition module (3) of listening to the teacher includes face identification system and normality recording and broadcasting system, and the face is known
Other system output is equipped with data processing unit, and the normality recording and broadcasting system output end is equipped with voice recognition unit, the voice
Recognition unit output end is equipped with scanning element and neural network unit, data processing unit, scanning element and neural network unit
Output end is connect with database of listening to the teacher；
The voice recognition unit is used to convert the voice of normality recording and broadcasting system recorded broadcast to word sequence, and uses scanning element
Classify with neural network unit to word sequence, obtained knowing for lecture contents in the period with x minutes for time window
Know point；
The data processing unit is used to the movement of each student is analyzed, using just using face recognition technology identification student id
Often movement number is divided by all acting numbers, the normal behaviour accounting in available student's time window, and then in cooperating and giving lessons
Hold knowledge point and carry out behavior evaluation of listening to the teacher, the scoring event of each student is stored as unit of student respectively to database of listening to the teacher
It is interior；
It is described to include classroom instruction equipment with hall practice data acquisition module (4) and answer equipment, the equipment output end of answering
Equipped with unit is read and made comments, equipped with electronic exam pool, the unit output end of reading and making comments is equipped with hall practice number for the unit connecting pin of reading and making comments
According to library；
The answer reading and making comments unit and submitting for receiving equipment of answering, receiving after answer can be with locating students id, and according to electricity
Crosshead library determines knowledge point, is corrected errors according to student's answer and determines the scoring event of the knowledge point, practiced on the class of each student
Point situation is stored as unit of student respectively in hall practice database；
The work data acquisition module (5) includes homework identification module, and the homework identification module connects electronics
Exam pool, the homework identification module output end are equipped with homework database；
The homework identification module is used to fulfil assignment in student and after mobile phone photograph uploads operation, utilizes artificial intelligence
Technology identification homework is corrected errors, and matches relevant knowledge point by electronic exam pool, after judging that answer is corrected errors, is determined related
The scoring event of knowledge point, the operation scoring event of each student are stored as unit of student respectively to homework database
It is interior.
2. a kind of noninductive acquisition system of various dimensions student learning behavior according to claim 1, it is characterised in that: described
Face identification system connecting pin is equipped with camera, and the camera is installed on inside classroom, for shooting identification student and bat
According to identification operation, and on this basis continue identify student posture movement, such as come back, bow, sleeping, stand up with it is other small
Movement.
3. a kind of noninductive acquisition system of various dimensions student learning behavior according to claim 1, it is characterised in that: described
Equipment of answering is specially the Electronic school badges or RFID answer card of button.
4. a kind of noninductive acquisition system of various dimensions student learning behavior according to claim 1, it is characterised in that: described
Listen to the teacher database, practice database and homework database output end with hall and be equipped with total points according to library.
5. a kind of noninductive analysis system of various dimensions student learning behavior according to any one of claims 1-4, special
Sign is: the various dimensions Learning behavior analyzing according to classroom listen to the teacher effect data acquisition module (3), with hall practice data acquisition
Module (4) and three dimension datas of work data acquisition module (5) acquisition are calculated as a fixed value by formula, wherein one
Score of a student std for a knowledge point kp are as follows:
Wherein L is that classroom is listened to the teacher effect score, and Q is to practice score on class, and H is homework score, above-mentioned score whole value
Between 0-1, weighting parameters, therefore,It is recommended that taking
Value 0.3,0.3,0.4；
It listens to the teacher the calculation method of effect score L in classroom are as follows:
Wherein p is listen to the teacher conscientious degree of the student in this knowledge point, is obtained according to regular event time/everything time,
Value range [0,1], wherein 2 and -5 be proposed parameter, Tuning function image aspects are used, should macroscopic view broad understanding；
Practice effect score on class are as follows:
Wherein x is that correctly the answer number of problem of student updates x=x+1, when student's mistake is answered when student correctly answers
X=x*0.7 is updated, wherein increment 1 and ratio 0.7 are proposed parameters, and Tuning function image aspects use, should macroscopical broad sense reason
Solution；
Practice in operation practice effect score and class identical:
Wherein x is student std by correctly answering a question belonging to camera system or the collected knowledge point kp of electronic exam pool
The number of topic updates x=x+1 when student correctly answers, and x=x*0.7 is updated when student's mistake is answered, wherein increment 1 and ratio
Example 0.7 is proposed parameter, and Tuning function image aspects use, should macroscopic view broad understanding；
Finally, each knowledge point kp of student std can Dynamic Maintenance in daily teaching.
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| CN110443226A (en) * | 2019-08-16 | 2019-11-12 | 重庆大学 | A kind of student's method for evaluating state and system based on gesture recognition |
| CN110490074A (en) * | 2019-07-17 | 2019-11-22 | 广州学邦信息技术有限公司 | Method, system and device are corrected in a kind of classroom based on image recognition in real time |
| CN110992741A (en) * | 2019-11-15 | 2020-04-10 | 深圳算子科技有限公司 | Learning auxiliary method and system based on classroom emotion and behavior analysis |
| CN111091484A (en) * | 2020-03-19 | 2020-05-01 | 浙江正元智慧科技股份有限公司 | Student learning behavior analysis system based on big data |
| CN113409635A (en) * | 2021-06-17 | 2021-09-17 | 上海松鼠课堂人工智能科技有限公司 | Interactive teaching method and system based on virtual reality scene |
| CN114005173A (en) * | 2020-07-13 | 2022-02-01 | 阿里巴巴集团控股有限公司 | Data processing method and device |
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| CN115631074A (en) * | 2022-12-06 | 2023-01-20 | 南京熊大巨幕智能科技有限公司 | Network science and education method, system and equipment based on informatization |
| CN116167898A (en) * | 2023-02-16 | 2023-05-26 | 广州中慧智能科技有限公司 | Network course management method, device, terminal and storage medium based on image data analysis |
| CN117423131A (en) * | 2023-10-18 | 2024-01-19 | 广东融粤宝信息科技有限公司 | Remote education system based on cloud computing |
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| CN110490074A (en) * | 2019-07-17 | 2019-11-22 | 广州学邦信息技术有限公司 | Method, system and device are corrected in a kind of classroom based on image recognition in real time |
| CN110443226A (en) * | 2019-08-16 | 2019-11-12 | 重庆大学 | A kind of student's method for evaluating state and system based on gesture recognition |
| CN110443226B (en) * | 2019-08-16 | 2022-01-25 | 重庆大学 | Student state evaluation method and system based on posture recognition |
| CN110992741A (en) * | 2019-11-15 | 2020-04-10 | 深圳算子科技有限公司 | Learning auxiliary method and system based on classroom emotion and behavior analysis |
| CN111091484A (en) * | 2020-03-19 | 2020-05-01 | 浙江正元智慧科技股份有限公司 | Student learning behavior analysis system based on big data |
| CN114005173A (en) * | 2020-07-13 | 2022-02-01 | 阿里巴巴集团控股有限公司 | Data processing method and device |
| CN113409635A (en) * | 2021-06-17 | 2021-09-17 | 上海松鼠课堂人工智能科技有限公司 | Interactive teaching method and system based on virtual reality scene |
| CN114926889A (en) * | 2022-07-19 | 2022-08-19 | 安徽淘云科技股份有限公司 | Job submission method and device, electronic equipment and storage medium |
| CN115631074A (en) * | 2022-12-06 | 2023-01-20 | 南京熊大巨幕智能科技有限公司 | Network science and education method, system and equipment based on informatization |
| CN116167898A (en) * | 2023-02-16 | 2023-05-26 | 广州中慧智能科技有限公司 | Network course management method, device, terminal and storage medium based on image data analysis |
| CN117423131A (en) * | 2023-10-18 | 2024-01-19 | 广东融粤宝信息科技有限公司 | Remote education system based on cloud computing |
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