CN113434229A - Education and teaching cloud desktop intelligent analysis management method and system and computer storage medium - Google Patents
Education and teaching cloud desktop intelligent analysis management method and system and computer storage medium Download PDFInfo
- Publication number
- CN113434229A CN113434229A CN202110690587.3A CN202110690587A CN113434229A CN 113434229 A CN113434229 A CN 113434229A CN 202110690587 A CN202110690587 A CN 202110690587A CN 113434229 A CN113434229 A CN 113434229A
- Authority
- CN
- China
- Prior art keywords
- teaching
- cloud desktop
- logged
- desktop teaching
- student
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/451—Execution arrangements for user interfaces
- G06F9/452—Remote windowing, e.g. X-Window System, desktop virtualisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/14—Digital output to display device ; Cooperation and interconnection of the display device with other functional units
- G06F3/1454—Digital output to display device ; Cooperation and interconnection of the display device with other functional units involving copying of the display data of a local workstation or window to a remote workstation or window so that an actual copy of the data is displayed simultaneously on two or more displays, e.g. teledisplay
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B5/00—Electrically-operated educational appliances
- G09B5/02—Electrically-operated educational appliances with visual presentation of the material to be studied, e.g. using film strip
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Software Systems (AREA)
- Human Computer Interaction (AREA)
- General Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Educational Administration (AREA)
- Educational Technology (AREA)
- Electrically Operated Instructional Devices (AREA)
Abstract
The invention discloses an intelligent analysis management method, a system and a computer storage medium for teaching cloud desktop, which are characterized in that before teaching in a cloud desktop classroom, teaching teachers and students respectively log in the cloud desktop, and identify teaching subjects corresponding to the teaching teachers according to the log-in mode of the teaching teachers, and further uniformly control all logged-in cloud desktop teaching extensions to automatically switch the cloud desktop teaching environment according to the identified teaching subjects by a cloud desktop teaching host, and simultaneously evaluate the control effect coefficient of the cloud desktop teaching host on each logged-in cloud desktop teaching extension in real time in the process that the cloud desktop teaching host controls all the logged-in cloud desktop teaching extensions, thereby realizing the automatic switching of the cloud desktop teaching environment and the tracking of the control effect of the cloud desktop teaching extensions, perfecting the management function of the cloud desktop teaching mode, and embodying the intelligent characteristics of management, the teaching experience of students can be improved, and the cloud desktop teaching quality is improved.
Description
Technical Field
The invention belongs to the technical field of teaching cloud desktop management, and particularly relates to an intelligent analysis management method and system for an education and teaching cloud desktop and a computer storage medium.
Background
Along with the development of information technology, the teaching requirements of colleges and universities are more diversified, and multimedia teaching is the main teaching means adopted by various colleges and universities. However, in the conventional multimedia teaching mode, different multimedia classrooms need to be configured according to different teaching subjects, so that the resource utilization rate of a single multimedia classroom is low, and in the process of configuring the multimedia classrooms, a large number of computer hosts and cables need to be installed, so that the space of the multimedia classrooms is occupied. Under the cloud computing condition, the cloud desktop construction scheme is widely accepted, many universities begin to apply the teaching mode based on the cloud desktop, and a cloud desktop classroom is constructed, so that the cloud desktop classroom can switch the cloud desktop teaching environment according to teaching subjects without a large number of computer hosts, the resource utilization rate of the multimedia classroom is improved, the teaching cost is effectively reduced, and the cloud desktop teaching mode becomes the most popular multimedia teaching mode at present. Similarly, regardless of the teaching mode, the teaching mode needs to be managed.
However, at present, the management function of the cloud desktop teaching mode is still incomplete, and the intelligent management level is low, which is embodied in the following two aspects:
1. switching the teaching environment: at present, teaching environment switching corresponding to a cloud desktop teaching mode requires a teaching teacher to manually control all cloud desktop teaching extensions to perform cloud desktop teaching environment switching through a cloud desktop teaching host according to a corresponding teaching subject, but due to the fact that subjective randomness of manual switching is high, the situation that switching is forgotten or switching errors possibly occur, and teaching experience of students is affected;
2. cloud desktop teaching extension control effect: because there is the difference in network transmission speed, cloud desktop screen definition, the control effect that leads to some cloud desktop teaching extension is good, and some cloud desktop teaching extension control effect is poor, and present teaching mr is in all cloud desktop teaching extension in-process of controlling through cloud desktop teaching host computer, does not trail the control effect for teaching mr can't know the control effect situation of all cloud desktop teaching extensions in real time accurately, has reduced cloud desktop teaching quality.
Disclosure of Invention
In view of the above problems, the invention provides an education and teaching cloud desktop intelligent analysis management method, system and computer storage medium, which effectively solve the problems mentioned in the background technology by automatically switching the cloud desktop teaching environment and evaluating the control effect coefficient of the cloud desktop teaching host on each cloud desktop teaching extension in real time in the process that the cloud desktop teaching host controls the cloud desktop teaching extensions.
The purpose of the invention can be realized by the following technical scheme:
the invention provides an educational teaching cloud desktop intelligent analysis management method, which comprises a cloud desktop teaching host, a cloud analysis platform and a plurality of cloud desktop teaching extensions, and the specific implementation process of the method comprises the following steps:
step 1, cloud desktop teaching login, wherein a teaching teacher selects a login mode from set login modes to log in a cloud desktop teaching host through a cloud desktop teaching login module before cloud desktop classroom teaching is performed, and each student selects a login mode from the set login modes to log in a corresponding cloud desktop teaching extension;
step 2, student class arrival rate analysis, namely controlling each cloud desktop teaching extension to capture a screen of a login result through a cloud analysis platform according to a student class arrival rate analysis module to form a login result image, and analyzing the class arrival rate of the student according to the login result image;
step 3, automatically switching the cloud desktop teaching environment, namely identifying a teaching subject corresponding to a teaching teacher by a cloud analysis platform according to the login mode of the teaching teacher through a cloud desktop teaching environment automatic switching module, and uniformly controlling all logged-in cloud desktop teaching extensions to automatically switch the cloud desktop teaching environment by a cloud desktop teaching host according to the identified teaching subject;
step 4, detecting control effect parameters of the cloud desktop teaching extensions, namely detecting the control effect parameters corresponding to all the logged cloud desktop teaching extensions in real time in the process of controlling all the logged cloud desktop teaching extensions by the cloud desktop teaching host through a control effect parameter detection module;
step 5, evaluating control effect parameters of the cloud desktop teaching extensions, namely evaluating control effect coefficients of the cloud desktop teaching host to the logged cloud desktop teaching extensions according to the control effect parameters corresponding to the logged cloud desktop teaching extensions through the management server, comparing the control effect coefficients with a preset minimum control effect coefficient, and screening out the serial numbers of the cloud desktop teaching extensions which are smaller than the preset minimum control effect coefficient;
step 6, collecting the face images of the students, namely arranging miniature cameras in the cloud desktop teaching branches through a student face image collecting module, controlling the miniature cameras in the logged-in cloud desktop teaching branches to start working by a cloud analysis platform in the process of cloud desktop classroom teaching, and collecting the face images of the students corresponding to the logged-in cloud desktop teaching branches in real time according to the set collecting time interval;
step 7, analyzing the comprehensive interest coefficient of student learning in the cloud desktop teaching, namely analyzing the collected face images of the students through a management server, and counting the comprehensive interest coefficient of the students corresponding to the cloud desktop teaching according to the analysis;
and 8, displaying by the cloud desktop teaching host: the class arrival rate of students, the serial numbers of the cloud desktop teaching extensions which are smaller than the preset minimum control effect coefficient, the comprehensive interest coefficients of the students corresponding to the cloud desktop teaching and the facial images of the students corresponding to the logged-in cloud desktop teaching extensions are displayed on the cloud desktop teaching host through the display module.
In an implementation manner of the first aspect of the present invention, the cloud desktop teaching host corresponds to a teaching teacher, each cloud desktop teaching extension corresponds to a student, and each cloud desktop teaching extension is numbered.
In an implementation manner of the first aspect of the present invention, the set login manner includes a face recognition login and a fingerprint recognition login.
In an implementation manner of the first aspect of the present invention, in the step 2, the class arrival rate of the student is analyzed according to the login result image, and the specific analysis process is as follows:
s1, comparing the login result image corresponding to each cloud desktop teaching extension with the set login result image corresponding to the un-login, if the comparison of the login result image corresponding to a certain cloud desktop teaching extension fails, indicating that the cloud desktop teaching extension is logged in and representing that students corresponding to the cloud desktop teaching extension have arrived at a class, and counting the number of the logged-in cloud desktop teaching extensions;
and S2, dividing the number of the logged-in cloud desktop teaching extensions by the total number of the cloud desktop teaching extensions to obtain the class arrival rate of the students.
In an implementation manner of the first aspect of the present invention, the step 2 further includes recognizing names of students who have not arrived in the class, and displaying the names on the cloud desktop teaching host, where the specific operation process includes the following steps:
w1, in the process of comparing the login result image corresponding to each cloud desktop teaching extension with the set login result image corresponding to the unregistered cloud desktop teaching extension, if the login result image corresponding to a certain cloud desktop teaching extension is successfully compared, the cloud desktop teaching extension is not logged in, which means that the student corresponding to the cloud desktop teaching extension does not arrive at the class, and at the moment, the number of the unregistered cloud desktop teaching extension is recorded;
w2, comparing the numbers of the unregistered cloud desktop teaching extensions with the names of students corresponding to the preset numbers of the cloud desktop teaching extensions, and acquiring the names of the students who have not arrived in the class.
In an implementation manner of the first aspect of the present invention, in step 3, the cloud desktop teaching host uniformly controls all logged-in cloud desktop teaching extensions to perform automatic switching of the cloud desktop teaching environment, and the specific switching steps are as follows:
h1, matching the identified teaching subjects with the cloud desktop teaching environments corresponding to various teaching subjects in the teaching database, and screening out the cloud desktop teaching environments corresponding to the teaching subjects, wherein the cloud desktop teaching environments comprise cloud desktop background images and cloud desktop teaching software;
and H2, counting the serial numbers of all the logged cloud desktop teaching extensions, wherein the serial numbers can be marked as 1,2, a.
In an implementation manner of the first aspect of the present invention, in step 5, the management server evaluates, according to the control effect parameter corresponding to each logged-in cloud desktop teaching extension, a control effect coefficient of the cloud desktop teaching host to each logged-in cloud desktop teaching extension, and a specific evaluation process of the evaluation server executes the following steps:
d1, forming a control effect parameter set Q of the logged cloud desktop teaching extensions by using the control effect parameters corresponding to the logged cloud desktop teaching extensionsr(qr1,qr2,...,qri,...,qrn)，qri represents a numerical value corresponding to a control effect parameter of the ith logged-in cloud desktop teaching extension, r represents the control effect parameter, and r is u1 and u2, which respectively represent network transmission speed and cloud desktop screen definition;
d2, comparing the control effect parameter set of the logged cloud desktop teaching extension with the minimum value of the standard synchronous network transmission speed corresponding to the cloud desktop teaching control in the teaching database and the minimum value of the standard cloud desktop screen definition, and further evaluating the control effect coefficient of the cloud desktop teaching host on each logged cloud desktop teaching extension according to the comparison result, wherein the evaluation calculation formula is
Expressed as the control effect coefficient of the cloud desktop teaching host computer to the ith logged-in cloud desktop teaching extension, qu1i、qu2i is respectively expressed as the network transmission speed, the cloud desktop screen definition and q corresponding to the ith logged-in cloud desktop teaching extensionu′1、qu′2The minimum value of the standard synchronous network transmission speed corresponding to the cloud desktop teaching control and the minimum value of the standard cloud desktop screen definition are respectively expressed.
In an implementation manner of the first aspect of the present invention, in step 7, the management server analyzes the collected facial images of the students, and accordingly calculates the comprehensive interest coefficient of the students corresponding to the cloud desktop teaching, where a specific statistical method is as follows:
f1, extracting facial expression characteristics of the collected facial images of the students, matching the extracted facial expression characteristics with facial expression characteristics corresponding to various expression types in a teaching database, and screening out the expression types of the students corresponding to the logged-in cloud desktop teaching extensions;
f2, comparing the expression types of students corresponding to the logged-in cloud desktop extension sets, judging whether the same expression types exist, if so, summarizing and classifying the students corresponding to the same expression types to obtain a student set corresponding to the same expression types, and numbering the same expression types at the moment, wherein the numbers of the student sets are respectively marked as 1,2, a.
F3, counting the number of students in the student set corresponding to each same expression type, and comparing the expression type corresponding to each same expression type with the student learning interest index corresponding to each expression type in the teaching database to obtain the student learning interest index corresponding to each same expression type;
f4, counting the student learning comprehensive interest coefficient corresponding to the cloud desktop teaching according to the number of students in the student set corresponding to each same expression type and the student learning interest index, wherein the calculation formula is
Eta is expressed as the student learning comprehensive interest coefficient, epsilon, corresponding to the cloud desktop teachingjExpressed as the student learning interest index, k, corresponding to the jth same expression typejThe expression that the jth same expression type corresponds to the number of students in the student set.
The invention provides an education and teaching cloud desktop intelligent analysis management system, which comprises a cloud desktop teaching login module, a student to class rate analysis module, a cloud desktop teaching environment automatic switching module, a control effect parameter detection module, a student facial image acquisition module, a teaching database, a management server and a display module, wherein cloud desktop teaching login module is connected with student to class rate analysis module, student to class rate analysis module is connected with cloud desktop teaching environment automatic switch-over module, cloud desktop teaching environment automatic switch-over module is connected with control effect parameter detection module and student's facial image acquisition module respectively, control effect parameter detection module and student's facial image acquisition module all are connected with management server, student to class rate analysis module, student's facial image acquisition module and management server all are connected with display module.
The third aspect of the invention provides a computer storage medium, wherein a computer program is burned in the computer storage medium, and when the computer program runs in a memory of a server, the intelligent analysis management method for the education and teaching cloud desktop is realized.
Based on any one of the aspects, the invention has the beneficial effects that:
1. according to the cloud desktop teaching environment automatic switching method, before cloud desktop classroom teaching, a teaching teacher and students respectively perform cloud desktop teaching login, the teaching subjects corresponding to the teaching teacher are identified according to the login mode of the teaching teacher, then the cloud desktop teaching host uniformly controls the cloud desktop teaching extensions to perform cloud desktop teaching environment automatic switching according to the identified teaching subjects, the control effect parameters corresponding to the cloud desktop teaching extensions are detected in real time in the process that the cloud desktop teaching host controls the cloud desktop teaching extensions, the control effect coefficient of the cloud desktop teaching host to the cloud desktop teaching extensions is evaluated accordingly, automatic switching of the cloud desktop teaching environment and tracking of the control effect of the cloud desktop teaching extensions are achieved, the management function of the cloud desktop teaching mode is perfected, the intelligent level of management is improved, and the situation that switching or switching errors caused by adopting an artificial switching mode to the cloud desktop teaching environment are greatly forgotten at present is greatly reduced The emergence of, on the other hand has effectively avoided at present not carrying out the emergence that the effect control situation was known to the teaching mr that the effect was trailed to cloud desktop teaching extension in real time accurately to the teaching teacher that the control effect was not caused to cloud desktop teaching extension in-process through cloud desktop teaching host computer control, is favorable to improving student's teaching experience and feels, and then has promoted cloud desktop teaching quality.
2. According to the cloud desktop teaching system and the cloud desktop teaching method, after the teaching teachers and students respectively perform cloud desktop teaching login, the numbers of all logged-in cloud desktop teaching extensions are obtained, and then all the logged-in cloud desktop teaching extensions are uniformly controlled by the cloud desktop teaching host, so that the situation that useless control is caused by controlling all the cloud desktop teaching extensions which are not logged in is avoided, the control flexibility is embodied, and meanwhile, the control efficiency is improved as only the logged-in cloud desktop teaching extensions are controlled.
3. According to the cloud desktop teaching system, after the teaching teacher and the students respectively carry out cloud desktop teaching login, the class arrival rate of the students is analyzed, convenience is provided for the teaching teacher to carry out student attendance management on the current cloud desktop teaching, the teaching work of the teacher is relieved, and the situation that the classroom duration is occupied due to the fact that the teaching teacher manually carries out student attendance is avoided.
4. According to the cloud desktop teaching method, the face images of students corresponding to the logged-in cloud desktop teaching extensions are collected in real time in the cloud desktop classroom teaching process, the collected face images of the students are analyzed, the comprehensive student learning interest coefficients corresponding to the cloud desktop teaching are counted according to the collected face images, the counted comprehensive student learning interest coefficients can comprehensively reflect the learning interest conditions of the students in the cloud desktop teaching, a teaching teacher can conveniently know the comprehensive student learning interest conditions in real time, and a reliable adjusting basis is improved for the teaching teacher to adjust the lecture mode of the cloud desktop teaching.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
FIG. 1 is a flow chart of the steps of a method of the present invention;
fig. 2 is a schematic diagram of the system module connection according to the present invention.
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. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a first aspect of the present invention provides an intelligent analysis and management method for a cloud desktop for education and teaching, the method is composed of a cloud desktop teaching host, a cloud analysis platform and a plurality of cloud desktop teaching extensions, wherein the cloud desktop teaching host corresponds to a teaching teacher, each cloud desktop teaching extension corresponds to a student, and each cloud desktop teaching extension is numbered, and the specific implementation process of the method includes the following steps:
step 1, cloud desktop teaching login, wherein a teaching teacher selects a login mode from set login modes to log in a cloud desktop teaching host through a cloud desktop teaching login module before cloud desktop classroom teaching is performed, and each student selects a login mode from the set login modes to log in a corresponding cloud desktop teaching extension;
the login mode set in the embodiment comprises face identification login and fingerprint identification login, and the face identification login and the fingerprint identification login are selected as the set login mode, because face identification and fingerprint identification have personal uniqueness, the personal uniqueness login can be realized, and the situation that a non-personal replaces login is avoided;
and 2, analyzing the class arrival rate of the students, namely controlling each cloud desktop teaching extension to capture the login results through a cloud analysis platform according to the class arrival rate analysis module to form login result images, and analyzing the class arrival rate of the students according to the login result images, wherein the specific analysis process is as follows:
s1, comparing the login result image corresponding to each cloud desktop teaching extension with the set login result image corresponding to the un-login, if the comparison of the login result image corresponding to a certain cloud desktop teaching extension fails, indicating that the cloud desktop teaching extension is logged in and representing that students corresponding to the cloud desktop teaching extension have arrived at a class, and counting the number of the logged-in cloud desktop teaching extensions;
s2, dividing the number of the logged-in cloud desktop teaching extensions by the total number of the cloud desktop teaching extensions to obtain the class arrival rate of the students;
in the embodiment, after the teaching teacher and the students respectively perform cloud desktop teaching login, the class arrival rate of the students is analyzed, so that convenience is provided for the teaching teacher to manage the current student attendance of the cloud desktop teaching, the teaching work of the teacher is reduced, and the situation that the class duration is occupied due to the fact that the teaching teacher manually performs student attendance is avoided;
the step 2 also comprises the steps of identifying names of students who have not arrived the class, and displaying the names on the cloud desktop teaching host, wherein the specific operation process comprises the following steps:
w1, in the process of comparing the login result image corresponding to each cloud desktop teaching extension with the set login result image corresponding to the unregistered cloud desktop teaching extension, if the login result image corresponding to a certain cloud desktop teaching extension is successfully compared, the cloud desktop teaching extension is not logged in, which means that the student corresponding to the cloud desktop teaching extension does not arrive at the class, and at the moment, the number of the unregistered cloud desktop teaching extension is recorded;
w2, comparing the number of the unregistered cloud desktop teaching extension with the name of the student corresponding to the preset number of each cloud desktop teaching extension, and acquiring the name of the student who does not arrive in the class;
in the embodiment, the names of the students who have not arrived in the class are displayed on the cloud desktop teaching host, so that the teaching teachers can conveniently and visually know the names, and a checking target is provided for checking the reasons of the students who have not arrived in the class in the following process;
step 3, automatically switching the cloud desktop teaching environment, namely identifying the teaching subjects corresponding to the teaching teacher by the cloud analysis platform according to the login mode of the teaching teacher through a cloud desktop teaching environment automatic switching module, wherein the specific identification process is that if the login mode selected by the teaching teacher is human face identification, the human face image of the teaching teacher is compared with the teaching subjects corresponding to the human face images of the teaching teacher to obtain the teaching subjects corresponding to the human face image of the teaching teacher, if the login mode selected by the teaching teacher is fingerprint identification, the fingerprint of the teaching teacher is compared with the teaching subjects corresponding to the fingerprints of the teaching teacher to obtain the teaching subjects corresponding to the fingerprint of the teaching teacher, and according to the identified teaching subjects, the cloud desktop teaching host uniformly controls all logged-in cloud desktop teaching extensions to automatically switch the cloud desktop teaching environment, the specific switching steps are as follows:
h1, matching the identified teaching subjects with the cloud desktop teaching environments corresponding to various teaching subjects in the teaching database, and screening out the cloud desktop teaching environments corresponding to the teaching subjects, wherein the cloud desktop teaching environments comprise cloud desktop background images and cloud desktop teaching software;
h2, counting the numbers of all the logged cloud desktop teaching extensions, wherein the numbers can be marked as 1,2, 1, i, 1, n, uniformly controlling the current cloud desktop background images corresponding to all the logged cloud desktop teaching extensions to be switched into the cloud desktop background images corresponding to the teaching subjects by the cloud desktop teaching host, and uniformly controlling the current cloud desktop teaching software corresponding to all the logged cloud desktop teaching extensions to be switched into the cloud desktop teaching software corresponding to the teaching subjects;
in the embodiment, after the teaching teachers and students respectively perform cloud desktop teaching login, the numbers of all logged-in cloud desktop teaching extensions are obtained, and then all logged-in cloud desktop teaching extensions are uniformly controlled by the cloud desktop teaching host, so that the condition that useless control is caused by controlling unregistered cloud desktop teaching extensions due to the fact that all cloud desktop teaching extensions are controlled is avoided, the control flexibility is embodied, and meanwhile, the control efficiency is improved due to the fact that only logged-in cloud desktop teaching extensions are controlled;
step 4, detecting control effect parameters of the cloud desktop teaching extensions, namely detecting the control effect parameters corresponding to all the logged cloud desktop teaching extensions in real time in the process of controlling all the logged cloud desktop teaching extensions by the cloud desktop teaching host through a control effect parameter detection module, wherein the control effect parameters comprise network transmission speed and cloud desktop screen definition;
and 5, evaluating control effect parameters of the cloud desktop teaching extensions, namely evaluating control effect coefficients of the cloud desktop teaching host to the logged cloud desktop teaching extensions through the management server according to the control effect parameters corresponding to the logged cloud desktop teaching extensions, wherein the specific evaluation process executes the following steps:
d1, forming a control effect parameter set Q of the logged cloud desktop teaching extensions by using the control effect parameters corresponding to the logged cloud desktop teaching extensionsr(qr1,qr2,...,qri,...,qrn)，qri represents a numerical value corresponding to a control effect parameter of the ith logged-in cloud desktop teaching extension, r represents the control effect parameter, and r is u1 and u2, which respectively represent network transmission speed and cloud desktop screen definition;
d2, comparing the control effect parameter set of the logged cloud desktop teaching extension with the minimum value of the standard synchronous network transmission speed corresponding to the cloud desktop teaching control in the teaching database and the minimum value of the standard cloud desktop screen definition, and further evaluating the control effect coefficient of the cloud desktop teaching host on each logged cloud desktop teaching extension according to the comparison result, wherein the evaluation calculation formula is
Expressed as the control effect coefficient of the cloud desktop teaching host computer to the ith logged-in cloud desktop teaching extension, qu1i、qu2i is respectively expressed as the network transmission speed, the cloud desktop screen definition and q corresponding to the ith logged-in cloud desktop teaching extensionu′1、qu′2Respectively representing the minimum value of the standard synchronous network transmission speed corresponding to the cloud desktop teaching control and the minimum value of the standard cloud desktop screen definition, wherein the larger the control effect coefficient is, the better the control effect is;
after the control effect coefficients of the cloud desktop teaching host computer to the logged cloud desktop teaching extensions are evaluated, the control effect coefficients are compared with a preset minimum control effect coefficient, and cloud desktop teaching extensions with the numbers smaller than the preset minimum control effect coefficient are screened out;
in the embodiment, the network transmission speed and the cloud desktop screen definition are selected as the control effect parameters because the network transmission speed and the cloud desktop screen definition have a large influence on the control effect, and when the network transmission speed corresponding to a certain cloud desktop teaching extension is low, a control delay condition occurs, so that the control effect is influenced; when the definition of a cloud desktop screen corresponding to a certain cloud desktop teaching extension is poor, the watching effect of students is influenced, and the control effect is further influenced;
in the embodiment, before the teaching of the cloud desktop classroom, a teaching teacher and students respectively log in the cloud desktop for teaching, identify teaching subjects corresponding to the teaching teacher according to the log-in mode of the teaching teacher, uniformly control all logged-in cloud desktop teaching extensions by the cloud desktop teaching host for automatic switching of the cloud desktop teaching environment according to the identified teaching subjects, simultaneously evaluate the control effect coefficient of the cloud desktop teaching host on each logged-in cloud desktop teaching extension in real time in the process of controlling all logged-in cloud desktop teaching extensions by the cloud desktop teaching host, realize automatic switching of the teaching environment corresponding to the cloud desktop teaching and tracking of the control effect of the cloud desktop teaching extensions, perfect the management function of the cloud desktop teaching mode, improve the intelligent level of management, on one hand, greatly reduce the occurrence of switching or switching error caused by manually switching the cloud desktop teaching environment at present, on the other hand, the problem that a teaching teacher cannot accurately know the control effect conditions of all cloud desktop teaching extensions in real time due to the fact that the control effect tracking is not carried out on the cloud desktop teaching extensions in the process of controlling the plurality of cloud desktop teaching extensions through the cloud desktop teaching host at present is effectively avoided, the teaching experience of students is favorably improved, and the cloud desktop teaching quality is further improved;
step 6, collecting the face images of the students, namely arranging miniature cameras in the cloud desktop teaching branches through a student face image collecting module, controlling the miniature cameras in the logged-in cloud desktop teaching branches to start working by a cloud analysis platform in the process of cloud desktop classroom teaching, and collecting the face images of the students corresponding to the logged-in cloud desktop teaching branches in real time according to the set collecting time interval;
step 7, analyzing the comprehensive interest coefficient of student learning in the cloud desktop teaching, namely analyzing the collected facial images of the students through a management server, and counting the comprehensive interest coefficient of the students corresponding to the cloud desktop teaching according to the analysis, wherein the specific statistical method comprises the following steps:
f1, extracting facial expression characteristics of the collected facial images of the students, matching the extracted facial expression characteristics with facial expression characteristics corresponding to various expression types in a teaching database, and screening out the expression types of the students corresponding to the logged-in cloud desktop teaching extensions;
f2, comparing the expression types of students corresponding to the logged-in cloud desktop extension sets, judging whether the same expression types exist, if so, summarizing and classifying the students corresponding to the same expression types to obtain a student set corresponding to the same expression types, and numbering the same expression types at the moment, wherein the numbers of the student sets are respectively marked as 1,2, a.
F3, counting the number of students in the student set corresponding to each same expression type, and comparing the expression type corresponding to each same expression type with the student learning interest index corresponding to each expression type in the teaching database to obtain the student learning interest index corresponding to each same expression type;
f4, counting the student learning comprehensive interest coefficient corresponding to the cloud desktop teaching according to the number of students in the student set corresponding to each same expression type and the student learning interest index, wherein the calculation formula is
Eta is expressed as the student learning comprehensive interest coefficient, epsilon, corresponding to the cloud desktop teachingjExpressed as the student learning interest index, k, corresponding to the jth same expression typejThe number of students in the student set corresponding to the jth same expression type is expressed, wherein the larger the comprehensive interest coefficient of the students in learning is, the more interested the students in the cloud desktop teaching is;
the method comprises the steps of acquiring face images of students corresponding to logged-in cloud desktop teaching extensions in real time in the process of cloud desktop classroom teaching, analyzing the acquired face images of the students, and accordingly counting comprehensive interest coefficients of the students corresponding to the cloud desktop teaching, wherein the counted comprehensive interest coefficients of the students can comprehensively reflect the learning interest conditions of the students in the cloud desktop teaching, so that teachers in teaching can conveniently know the learning interest conditions in real time, and reliable adjusting bases are improved for teachers in teaching to adjust the lecture modes of the cloud desktop teaching;
and 8, displaying by the cloud desktop teaching host: the class arrival rate of students, the serial numbers of the cloud desktop teaching extensions which are smaller than the preset minimum control effect coefficient, the learning comprehensive interest coefficients of the students corresponding to the cloud desktop teaching and the facial images of the students corresponding to the logged-in cloud desktop teaching extensions are displayed on the cloud desktop teaching host through the display module, and therefore teaching teachers can know the conditions of the logged-in cloud desktop teaching extensions in real time.
Referring to fig. 2, a second aspect of the present invention provides an educational and teaching cloud desktop intelligent analysis and management system, which includes a cloud desktop teaching login module, a student to class rate analysis module, a cloud desktop teaching environment automatic switching module, a control effect parameter detection module, a student facial image acquisition module, a teaching database, a management server and a display module, where the teaching database is used to store cloud desktop teaching environments corresponding to various teaching subjects, store a minimum value of a standard synchronous network transmission speed corresponding to cloud desktop teaching control and a minimum value of standard cloud desktop screen definition, store facial expression features corresponding to various expression types, and store student learning interest indexes corresponding to various expression types, where the various expression types include excitement, liking, surprise, injury, shame, anger, and the like.
Wherein cloud desktop teaching login module is connected with student to class rate analysis module, student to class rate analysis module is connected with cloud desktop teaching environment automatic switch-over module, cloud desktop teaching environment automatic switch-over module is connected with control effect parameter detection module and student's facial image acquisition module respectively, control effect parameter detection module and student's facial image acquisition module all are connected with management server, student to class rate analysis module, student's facial image acquisition module and management server all are connected with display module.
The third aspect of the invention provides a computer storage medium, wherein a computer program is burned in the computer storage medium, and when the computer program runs in a memory of a server, the intelligent analysis management method for the education and teaching cloud desktop is realized.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (10)
1. An educational teaching cloud desktop intelligent analysis management method is characterized by comprising a cloud desktop teaching host, a cloud analysis platform and a plurality of cloud desktop teaching extensions, and the specific implementation process of the method comprises the following steps:
step 1, cloud desktop teaching login, wherein a teaching teacher selects a login mode from set login modes to log in a cloud desktop teaching host through a cloud desktop teaching login module before cloud desktop classroom teaching is performed, and each student selects a login mode from the set login modes to log in a corresponding cloud desktop teaching extension;
step 2, student class arrival rate analysis, namely controlling each cloud desktop teaching extension to capture a screen of a login result through a cloud analysis platform according to a student class arrival rate analysis module to form a login result image, and analyzing the class arrival rate of the student according to the login result image;
step 3, automatically switching the cloud desktop teaching environment, namely identifying a teaching subject corresponding to a teaching teacher by a cloud analysis platform according to the login mode of the teaching teacher through a cloud desktop teaching environment automatic switching module, and uniformly controlling all logged-in cloud desktop teaching extensions to automatically switch the cloud desktop teaching environment by a cloud desktop teaching host according to the identified teaching subject;
step 4, detecting control effect parameters of the cloud desktop teaching extensions, namely detecting the control effect parameters corresponding to all the logged cloud desktop teaching extensions in real time in the process of controlling all the logged cloud desktop teaching extensions by the cloud desktop teaching host through a control effect parameter detection module;
step 5, evaluating control effect parameters of the cloud desktop teaching extensions, namely evaluating control effect coefficients of the cloud desktop teaching host to the logged cloud desktop teaching extensions according to the control effect parameters corresponding to the logged cloud desktop teaching extensions through the management server, comparing the control effect coefficients with a preset minimum control effect coefficient, and screening out the serial numbers of the cloud desktop teaching extensions which are smaller than the preset minimum control effect coefficient;
step 6, collecting the face images of the students, namely arranging miniature cameras in the cloud desktop teaching branches through a student face image collecting module, controlling the miniature cameras in the logged-in cloud desktop teaching branches to start working by a cloud analysis platform in the process of cloud desktop classroom teaching, and collecting the face images of the students corresponding to the logged-in cloud desktop teaching branches in real time according to the set collecting time interval;
step 7, analyzing the comprehensive interest coefficient of student learning in the cloud desktop teaching, namely analyzing the collected face images of the students through a management server, and counting the comprehensive interest coefficient of the students corresponding to the cloud desktop teaching according to the analysis;
and 8, displaying by the cloud desktop teaching host: the class arrival rate of students, the serial numbers of the cloud desktop teaching extensions which are smaller than the preset minimum control effect coefficient, the comprehensive interest coefficients of the students corresponding to the cloud desktop teaching and the facial images of the students corresponding to the logged-in cloud desktop teaching extensions are displayed on the cloud desktop teaching host through the display module.
2. The intelligent analysis and management method for the education and teaching cloud desktop, according to claim 1, is characterized in that: the cloud desktop teaching host corresponds to a teaching teacher, and each cloud desktop teaching extension corresponds to a student respectively, and numbers each cloud desktop teaching extension.
3. The intelligent analysis and management method for the education and teaching cloud desktop, according to claim 1, is characterized in that: the set login mode comprises face recognition login and fingerprint recognition login.
4. The intelligent analysis and management method for the education and teaching cloud desktop, according to claim 1, is characterized in that: in the step 2, the class arrival rate of the student is analyzed according to the login result image, and the specific analysis process is as follows:
s1, comparing the login result image corresponding to each cloud desktop teaching extension with the set login result image corresponding to the un-login, if the comparison of the login result image corresponding to a certain cloud desktop teaching extension fails, indicating that the cloud desktop teaching extension is logged in and representing that students corresponding to the cloud desktop teaching extension have arrived at a class, and counting the number of the logged-in cloud desktop teaching extensions;
and S2, dividing the number of the logged-in cloud desktop teaching extensions by the total number of the cloud desktop teaching extensions to obtain the class arrival rate of the students.
5. The intelligent analysis and management method for the education and teaching cloud desktop, according to claim 4, is characterized in that: the step 2 also comprises the steps of identifying names of students who have not arrived the class and displaying the names on the cloud desktop teaching host, wherein the specific operation process comprises the following steps:
w1, in the process of comparing the login result image corresponding to each cloud desktop teaching extension with the set login result image corresponding to the unregistered cloud desktop teaching extension, if the login result image corresponding to a certain cloud desktop teaching extension is successfully compared, the cloud desktop teaching extension is not logged in, which means that the student corresponding to the cloud desktop teaching extension does not arrive at the class, and at the moment, the number of the unregistered cloud desktop teaching extension is recorded;
w2, comparing the numbers of the unregistered cloud desktop teaching extensions with the names of students corresponding to the preset numbers of the cloud desktop teaching extensions, and acquiring the names of the students who have not arrived in the class.
6. The intelligent analysis and management method for the education and teaching cloud desktop, according to claim 1, is characterized in that: in the step 3, the cloud desktop teaching host uniformly controls all logged-in cloud desktop teaching extensions to automatically switch the cloud desktop teaching environment, and the specific switching steps are as follows:
h1, matching the identified teaching subjects with the cloud desktop teaching environments corresponding to various teaching subjects in the teaching database, and screening out the cloud desktop teaching environments corresponding to the teaching subjects, wherein the cloud desktop teaching environments comprise cloud desktop background images and cloud desktop teaching software;
and H2, counting the serial numbers of all the logged cloud desktop teaching extensions, wherein the serial numbers can be marked as 1,2, a.
7. The intelligent analysis and management method for the education and teaching cloud desktop, according to claim 1, is characterized in that: in the step 5, the management server evaluates the control effect coefficient of the cloud desktop teaching host to each logged-in cloud desktop teaching extension according to the control effect parameter corresponding to each logged-in cloud desktop teaching extension, and the specific evaluation process executes the following steps:
d1, forming a control effect parameter set Q of the logged cloud desktop teaching extensions by using the control effect parameters corresponding to the logged cloud desktop teaching extensionsr(qr1,qr2,...,qri,...,qrn)，qri represents a numerical value corresponding to a control effect parameter of the ith logged-in cloud desktop teaching extension, r represents the control effect parameter, and r is u1 and u2, which respectively represent network transmission speed and cloud desktop screen definition;
d2, comparing the control effect parameter set of the logged cloud desktop teaching extension with the minimum value of the standard synchronous network transmission speed corresponding to the cloud desktop teaching control in the teaching database and the minimum value of the standard cloud desktop screen definition, and evaluating the cloud desktop teaching host computer to each logged cloud desktop according to the comparison resultThe control effect coefficient of the teaching extension has an evaluation calculation formula of
Expressed as the control effect coefficient of the cloud desktop teaching host computer to the ith logged-in cloud desktop teaching extension, qu1i、qu2i is respectively expressed as the network transmission speed, the cloud desktop screen definition and q corresponding to the ith logged-in cloud desktop teaching extensionu′1、qu′2The minimum value of the standard synchronous network transmission speed corresponding to the cloud desktop teaching control and the minimum value of the standard cloud desktop screen definition are respectively expressed.
8. The intelligent analysis and management method for the education and teaching cloud desktop, according to claim 1, is characterized in that: in the step 7, the collected facial images of the students are analyzed through the management server, and the comprehensive interest coefficient of the students corresponding to the cloud desktop teaching is calculated according to the analysis, wherein the specific statistical method is as follows:
f1, extracting facial expression characteristics of the collected facial images of the students, matching the extracted facial expression characteristics with facial expression characteristics corresponding to various expression types in a teaching database, and screening out the expression types of the students corresponding to the logged-in cloud desktop teaching extensions;
f2, comparing the expression types of students corresponding to the logged-in cloud desktop extension sets, judging whether the same expression types exist, if so, summarizing and classifying the students corresponding to the same expression types to obtain a student set corresponding to the same expression types, and numbering the same expression types at the moment, wherein the numbers of the student sets are respectively marked as 1,2, a.
F3, counting the number of students in the student set corresponding to each same expression type, and comparing the expression type corresponding to each same expression type with the student learning interest index corresponding to each expression type in the teaching database to obtain the student learning interest index corresponding to each same expression type;
f4, counting the student learning comprehensive interest coefficient corresponding to the cloud desktop teaching according to the number of students in the student set corresponding to each same expression type and the student learning interest index, wherein the calculation formula is
Eta is expressed as the student learning comprehensive interest coefficient, epsilon, corresponding to the cloud desktop teachingjExpressed as the student learning interest index, k, corresponding to the jth same expression typejThe expression that the jth same expression type corresponds to the number of students in the student set.
9. The utility model provides an education and teaching cloud desktop intelligent analysis management system which characterized in that: including cloud desktop teaching login module, student to class rate analysis module, cloud desktop teaching environment automatic switch-over module, control effect parameter detection module, student's facial image acquisition module, the teaching database, management server and display module, wherein cloud desktop teaching login module is connected with student to class rate analysis module, student to class rate analysis module is connected with cloud desktop teaching environment automatic switch-over module, cloud desktop teaching environment automatic switch-over module is connected with control effect parameter detection module and student's facial image acquisition module respectively, control effect parameter detection module and student's facial image acquisition module all are connected with management server, student to class rate analysis module, student's facial image acquisition module and management server all are connected with display module.
10. A computer storage medium, characterized in that: the computer storage medium is burned with a computer program, which when run in the memory of the server implements the method of any of the above claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110690587.3A CN113434229A (en) | 2021-06-22 | 2021-06-22 | Education and teaching cloud desktop intelligent analysis management method and system and computer storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110690587.3A CN113434229A (en) | 2021-06-22 | 2021-06-22 | Education and teaching cloud desktop intelligent analysis management method and system and computer storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113434229A true CN113434229A (en) | 2021-09-24 |
Family
ID=77757026
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110690587.3A Withdrawn CN113434229A (en) | 2021-06-22 | 2021-06-22 | Education and teaching cloud desktop intelligent analysis management method and system and computer storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113434229A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114240118A (en) * | 2021-12-09 | 2022-03-25 | 华特数字科技有限公司 | Cloud desktop scheduling method and system |
| CN114240117A (en) * | 2021-12-09 | 2022-03-25 | 华特数字科技有限公司 | Cloud desktop education and teaching system and method |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111583079A (en) * | 2020-06-03 | 2020-08-25 | 何润东 | Classroom teaching management system based on wireless network |
-
2021
- 2021-06-22 CN CN202110690587.3A patent/CN113434229A/en not_active Withdrawn
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111583079A (en) * | 2020-06-03 | 2020-08-25 | 何润东 | Classroom teaching management system based on wireless network |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114240118A (en) * | 2021-12-09 | 2022-03-25 | 华特数字科技有限公司 | Cloud desktop scheduling method and system |
| CN114240117A (en) * | 2021-12-09 | 2022-03-25 | 华特数字科技有限公司 | Cloud desktop education and teaching system and method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11151892B2 (en) | Internet teaching platform-based following teaching system | |
| Kovanović et al. | Penetrating the black box of time-on-task estimation | |
| CN109657529A (en) | Classroom teaching effect evaluation system based on human facial expression recognition | |
| CN109727172A (en) | A kind of artificial intelligence machine study experimental skill points-scoring system | |
| CN109118091A (en) | A kind of artistic accomplishment evaluation system | |
| CN113434229A (en) | Education and teaching cloud desktop intelligent analysis management method and system and computer storage medium | |
| CN108154304A (en) | There is the server of Teaching Quality Assessment | |
| CN114038256B (en) | Teaching interactive system based on artificial intelligence | |
| RU2673010C1 (en) | Method for monitoring behavior of user during their interaction with content and system for its implementation | |
| CN111027865A (en) | Classroom teaching analysis and quality assessment system and method based on intelligent behavior and expression recognition | |
| CN111144275A (en) | Intelligent running test system and method based on face recognition | |
| CN110580470A (en) | Monitoring method and device based on face recognition, storage medium and computer equipment | |
| CN113269662A (en) | Intelligent teaching system based on big data | |
| CN112288239A (en) | Intelligent terminal online education platform | |
| CN111523444A (en) | Classroom behavior detection method based on improved Openpos model and facial micro-expressions | |
| CN110009539A (en) | A kind of student is in school learning state smart profile system and application method | |
| CN111369408A (en) | Hospital home intern teaching management system and method | |
| CN112862639A (en) | Online education method and online education platform based on big data analysis | |
| CN111523445A (en) | Examination behavior detection method based on improved Openpos model and facial micro-expression | |
| CN111127967A (en) | Intelligent education learning system for primary and secondary school students | |
| CN109903410A (en) | Roll-call based on recognition of face is registered method, apparatus, equipment and storage medium | |
| Psihountas | Flipped classrooms and finance—Is this a better way to learn? | |
| CN110111011A (en) | A kind of quality of instruction monitoring and managing method, device and electronic equipment | |
| CN109949189A (en) | A kind of online teaching interaction effect evaluation method and device | |
| CN116629708B (en) | Professional simulation practical training management system based on data analysis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20210924 |
|
| WW01 | Invention patent application withdrawn after publication |