CN116346659A - Cloud education English teaching platform and teaching method - Google Patents
Cloud education English teaching platform and teaching method Download PDFInfo
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Abstract
The invention discloses a cloud education English teaching platform and a teaching method, which belong to the field of cloud education and are used for solving the problem that online remote teaching quality is affected by easily neglecting network, data transmission and the like during online remote teaching.
Description
Technical Field
The invention belongs to the field of cloud education, relates to English teaching technology, and particularly relates to a cloud education English teaching platform and a teaching method.
Background
Cloud education is development of a cloud technology platform and application of the cloud education in the field of education and training, and is called cloud education for short. Cloud education breaks through the traditional education informatization boundary, promotes a brand new education informatization concept, and integrates teaching, management, learning, entertainment, sharing and interactive communication. The schools, teachers, students, parents and other education workers can complete different works according to the authority on the same platform. On the cloud education platform, educational resources, educational achievements, interactions between educators and educators in education can be shared.
When on-line remote teaching is performed, a teaching end usually sends a classroom link, then a student terminal enters a classroom through the classroom link, and when the subsequent on-line remote teaching is performed, a teacher terminal still adopts the on-line classroom to perform teaching, so that the condition of network, data transmission and the like of the on-line classroom is ignored, and the teaching quality of the on-line remote teaching is affected;
therefore, we propose a cloud education English teaching platform and teaching method.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention aims to provide a cloud education English teaching platform and a teaching method.
The technical problems to be solved by the invention are as follows:
how to measure and analyze based on the comprehensive conditions of the multiple factors so as to ensure the teaching quality of the cloud education English teaching platform.
The aim of the invention can be achieved by the following technical scheme:
the utility model provides a cloud education english teaching platform, includes data acquisition module, storage module, history analysis module, monitoring setting module, user module, result judging module, network monitoring module, transmission monitoring module and teaching platform, user module is used for teacher and student to get into the online classroom that has the classroom serial number and carries out english cloud education; the storage module is used for storing the classroom history data of the online classroom and sending the classroom history data of the corresponding online classroom to the history analysis module according to the classroom number;
the history analysis module is used for analyzing the classroom history of the online classroom, and acquiring a classroom monitoring value of the online classroom and transmitting the classroom monitoring value to the monitoring definition module through the teaching platform; the monitoring definition module is used for setting the monitoring force of the online classroom, obtaining the monitoring points of the online classroom, sending the monitoring points to the data acquisition module through the teaching platform, wherein the data acquisition module is used for acquiring the real-time classroom data of the online classroom and the real-time network data of the online classroom when the monitoring points are reached and sending the real-time classroom data to the teaching platform, and the teaching platform sends the real-time classroom data to the transmission monitoring module and sends the real-time network data to the network monitoring module;
the transmission monitoring module is used for monitoring the transmission condition of an online classroom, generating a transmission abnormal signal or transmitting a transmission normal signal and sending the transmission abnormal signal to the result judging module through the teaching platform; the network monitoring is used for monitoring the network condition of an online classroom, generating a network speed abnormal signal or a network speed normal signal and feeding the network speed abnormal signal or the network speed normal signal back to the teaching platform, and the teaching platform sends the network speed abnormal signal or the network speed normal signal to the result judging module;
the result judging module is used for judging the result of the classroom condition of the online classroom, generating a classroom abnormal signal and feeding back to the teaching platform or not carrying out any operation; if the teaching platform receives the classroom abnormal signal, the classroom abnormal signal is sent to the user module, and the user module is used for receiving the classroom abnormal signal and adjusting the online classroom.
Further, the class history data is the transmission abnormality times of the online class, the transmission abnormality time when each transmission abnormality, the network abnormality times and the network abnormality time when each network abnormality.
Further, the analysis process of the history analysis module is specifically as follows:
acquiring the transmission abnormal times and the transmission abnormal interval equal duration of an online classroom;
then acquiring the network anomaly times and the network anomaly interval equal duration of the online class;
and calculating a classroom monitoring value of the online classroom.
Further, the setting process of the monitoring and defining module is specifically as follows:
acquiring a classroom monitoring value of an online classroom;
then acquiring a classroom monitoring threshold of an online classroom stored in the teaching platform;
and comparing the classroom monitoring value of the online classroom with the classroom monitoring threshold value to obtain the monitoring points of the online classroom.
Further, the real-time classroom data is real-time sending voice and real-time receiving voice of the online classroom during monitoring points;
the real-time network data is the real-time uploading network speed value and the real-time downloading network speed value of the online class.
Further, the monitoring process of the transmission monitoring module is specifically as follows:
acquiring real-time sending voice and real-time receiving voice of an online class at the same monitoring point;
converting the real-time transmit speech to a first audio waveform map and converting the real-time receive speech to a second audio waveform map;
stacking the first audio waveform diagram and the second audio waveform diagram;
if the first audio waveform diagram is overlapped with the second audio waveform diagram, generating a normal transmission signal;
if the first audio waveform diagram and the second audio waveform diagram are not overlapped, counting the number of the crossing points when the first audio waveform diagram and the second audio waveform diagram are crossed, marking the number as the number of the deviation points, and simultaneously, calculating the area of the non-overlapped area of the first audio waveform diagram and the second audio waveform diagram and marking the area as the deviation area;
calculating a transmission deviation value of an online classroom during monitoring points;
and generating a transmission abnormal signal if the transmission deviation value is greater than or equal to the transmission deviation threshold value, and generating a transmission normal signal if the transmission deviation value is less than the transmission deviation threshold value.
Further, the monitoring process of the network monitoring is specifically as follows:
intercepting a network monitoring analysis period of any duration in the class duration of an online class, and setting a plurality of time points in the network monitoring analysis period;
acquiring a real-time uploading network speed value and a real-time downloading network speed value of an online classroom at a plurality of time points;
calculating a difference value of the real-time uploading network speed value when adjacent time points are calculated, taking an absolute value to obtain a real-time uploading network speed difference value, and then calculating a time difference value corresponding to the adjacent time points, wherein the real-time uploading network speed difference value is divided by the real-time uploading network speed difference value to obtain uploading network speed fluctuation rate corresponding to the adjacent time points;
similarly, obtaining the fluctuation rate of the download network speed corresponding to the adjacent time points;
if the uploading network speed fluctuation rate of the adjacent time point exceeds the uploading network speed fluctuation rate threshold or the downloading network speed fluctuation rate of the adjacent time point exceeds the downloading network speed fluctuation rate threshold, generating a network speed abnormal signal;
if the uploading network speed fluctuation rate of the adjacent time point does not exceed the uploading network speed fluctuation rate threshold value, and the downloading network speed fluctuation rate of the adjacent time point does not exceed the downloading network speed fluctuation rate threshold value, generating a network speed normal signal.
Further, the result determination module specifically works as follows:
if the transmission normal signal and the network speed normal signal are received at the same time, no operation is performed;
if any one of the transmission abnormal signal and the network speed abnormal signal is received, generating a class abnormal signal.
A teaching method of a cloud education English teaching platform comprises the following specific steps:
step S101, a history analysis module analyzes the classroom history of an online classroom, and a classroom monitoring value of the online classroom is obtained and sent to a monitoring definition module;
step S102, a monitoring definition module sets the monitoring force of an online classroom, the monitoring points of the online classroom are obtained and sent to a data acquisition module, and the data acquisition module acquires real-time classroom data of the online classroom and real-time network data of the online classroom when the monitoring points are reached;
step S103, a transmission monitoring module monitors the transmission condition of an online classroom, generates a transmission abnormal signal or a transmission normal signal and sends the transmission abnormal signal or the transmission normal signal to a result judging module;
step S104, monitoring the network condition of an online classroom by network monitoring, generating a network speed abnormal signal or a network speed normal signal and sending the network speed abnormal signal or the network speed normal signal to a result judging module;
and step 105, the result judging module judges the result of the class condition of the online class, generates a class abnormal signal and sends the class abnormal signal to the user module or does not perform any operation, and the user module adjusts the online class.
Compared with the prior art, the invention has the beneficial effects that:
the invention utilizes the history analysis module to analyze the classroom history condition of the online classroom, and sends the obtained classroom monitoring value of the online classroom to the monitoring definition module, the monitoring definition module sets the monitoring force of the online classroom to obtain the monitoring points of the online classroom, meanwhile, the invention monitors the transmission condition of the online classroom through the transmission monitoring module to generate transmission abnormal signals or transmission normal signals and sends the transmission abnormal signals to the result judgment module, monitors the network condition of the online classroom through the network monitoring to generate network speed abnormal signals or network speed normal signals and sends the network speed abnormal signals to the result judgment module, and finally utilizes the result judgment module to judge the classroom condition of the online classroom to generate classroom abnormal signals or does not perform any operation.
Drawings
The present invention is further described below with reference to the accompanying drawings for the convenience of understanding by those skilled in the art.
FIG. 1 is an overall system block diagram of the present invention;
fig. 2 is a flow chart of the operation of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In an embodiment, referring to fig. 1, a cloud education english teaching platform is provided, including a data acquisition module, a storage module, a history analysis module, a monitoring setting module, a user module, a result determination module, a network monitoring module, a transmission monitoring module, and a teaching platform;
specifically, the user module comprises a plurality of teacher terminals and a plurality of student terminals, wherein the teacher terminals are used for inputting personal information by a teacher, registering and logging in a teaching platform and sending the personal information to the teaching platform, and the student terminals are used for registering and logging in the teaching platform after inputting the personal information by a student and sending the personal information to the teaching platform, wherein the personal information of the teacher comprises the name, an identity card number, a mobile phone number, a taught subject and the like of the teacher, and the personal information of the student comprises the name, the identity card number, the number and the like of the student;
in the implementation, the user module is used for teachers and students to enter an online classroom with classroom numbers to carry out English cloud education;
in this embodiment, the storage module is configured to store classroom history data of an online classroom, and send the classroom history data corresponding to the online classroom to the history analysis module according to the classroom number;
the specific explanation is that the class history data is the transmission abnormality times of the online class, the transmission abnormality time when each transmission abnormality is carried out, the network abnormality times and the network abnormality time when each network abnormality is carried out;
the history analysis module is used for analyzing the class history of the online class, and the analysis process is specifically as follows:
marking an online class as u, u=1, 2, … …, z, z being a positive integer;
acquiring the abnormal transmission times of an online classroom, and marking the abnormal transmission as CYu;
then acquiring transmission abnormal time when each transmission abnormality of the online classroom, calculating a difference value of the transmission abnormal time when each transmission abnormality to obtain a plurality of groups of transmission abnormal interval duration, adding and summing the plurality of groups of transmission abnormal interval duration to obtain an average transmission abnormal interval duration CYTu of the online classroom;
meanwhile, acquiring network anomaly times WYu of online class and network anomaly time of each network anomaly;
according to the method, the network abnormal interval average duration WYTU of the online class is obtained;
calculating to obtain a classroom monitoring value KJu of the online classroom by using a formula KJu = (CYu + WYu) x a < 1+ > (CYTu+WYTU) x a < 2 >; wherein a1 and a2 are proportionality coefficients with fixed values, and the values of a1 and a2 are larger than zero;
the history analysis module feeds back a classroom monitoring value KJu of the online classroom to the teaching platform, and the teaching platform sends a classroom monitoring value KJu of the online classroom to the monitoring definition module;
in this embodiment, the monitoring defining module is configured to set monitoring force of an online classroom, and the setting process is specifically as follows:
acquiring the classroom monitoring value KJu of the online classroom obtained by calculation;
then acquiring a classroom monitoring threshold of an online classroom stored in the teaching platform, and comparing the classroom monitoring value of the online classroom with the classroom monitoring threshold;
if KJu is less than X1, the number of monitoring points in the online class is Y1;
if X1 is less than or equal to KJu and less than X2, the number of monitoring points in the online class is Y1;
if X2 is less than or equal to KJu, the number of monitoring points in the online class is Y1; wherein X1 and X2 are classroom monitoring thresholds, X1 is less than X2, Y1, Y2 and Y3 are positive integers with fixed values, and Y1 is more than 0 and Y2 is more than 0 and Y3 is more than 2;
the monitoring definition module feeds back the monitoring points of the online class to the teaching platform, the teaching platform sends the monitoring parameters to the data acquisition module, the data acquisition module is used for acquiring real-time class data of the online class and real-time network data of the online class when the monitoring points are reached, and sending the real-time class data and the real-time network data to the teaching platform, the teaching platform sends the real-time class data to the transmission monitoring module, and the teaching platform sends the real-time network data to the network monitoring module;
the real-time classroom data is real-time sending voice and real-time receiving voice of an online classroom during monitoring points, the real-time sending voice is the real-time voice sent by a teacher terminal during teaching, the data acquisition module can be a voice receiver, the voice receiver and sound amplifying equipment are worn on the body of the teacher, meanwhile, the real-time receiving voice can be acquired through teaching equipment of a student terminal, the teaching equipment is a tablet, a mobile phone, a computer and the like of the student, and the data acquisition module is the voice receiver in the teaching equipment; the real-time network data are the real-time uploading network speed value and the real-time downloading network speed value of the online class;
the transmission monitoring module is used for monitoring the transmission condition of an online classroom, and the monitoring process is specifically as follows:
acquiring real-time sending voice and real-time receiving voice of an online class at the same monitoring point;
converting the real-time transmitted voice into a first audio waveform diagram through the prior art such as premierro software;
similarly, converting the real-time received voice into a second audio waveform diagram;
stacking the first audio waveform diagram and the second audio waveform diagram;
if the first audio waveform diagram is overlapped with the second audio waveform diagram, generating a normal transmission signal;
if the first audio waveform diagram and the second audio waveform diagram are not overlapped, counting the number of the crossing points when the first audio waveform diagram and the second audio waveform diagram are crossed, and marking the number as the number of the deviation points PD;
meanwhile, calculating the area of the non-overlapping area of the first audio waveform diagram and the second audio waveform diagram and marking the area as an offset area PM;
calculating to obtain a transmission deviation value CP of an online classroom during monitoring points through a formula CP=PD×b1+PM×b3; wherein b1 and b2 are weight coefficients with fixed values, and the values of b1 and b2 are larger than zero;
if the transmission deviation value is greater than or equal to the transmission deviation threshold value, generating a transmission abnormal signal;
in this embodiment, when the next monitoring point is reached, according to the above analysis step, the transmission deviation value of the online class at the next monitoring point is still greater than or equal to the transmission deviation threshold value, and then a transmission abnormal signal is generated;
if the transmission deviation value is smaller than the transmission deviation threshold value, generating a transmission normal signal;
the transmission monitoring module feeds back the transmission abnormal signal or the transmission normal signal to the teaching platform, and the teaching platform sends the transmission abnormal signal or the transmission normal signal to the result judging module;
in this embodiment, the network monitoring is used to monitor the network situation of the online class, and the monitoring process specifically includes the following steps:
intercepting network monitoring analysis time periods of any duration in the class duration of an online class;
setting a plurality of time points in a network monitoring analysis period;
acquiring a real-time uploading network speed value and a real-time downloading network speed value of an online classroom at a plurality of time points;
calculating a difference value of the real-time uploading network speed value when adjacent time points are calculated, taking an absolute value to obtain a real-time uploading network speed difference value, and then calculating a time difference value corresponding to the adjacent time points, wherein the real-time uploading network speed difference value is divided by the real-time uploading network speed difference value to obtain uploading network speed fluctuation rate corresponding to the adjacent time points;
similarly, the download network speed fluctuation rate corresponding to the adjacent time points is calculated according to the method;
the calculation process of the uploading network speed fluctuation rate and the downloading network speed fluctuation rate is exemplified as follows:
if time points are set in the network monitoring analysis period, the time points are divided into t1, t2 and t3, real-time uploading network speed values corresponding to the time points are SWut1, SWut2 and SWut3, real-time downloading network speed values corresponding to the time points are XWut1, XWut2 and XWut3, uploading network speed fluctuation rate from the time point t1 to the time point t2 is |SWut2-SWut1|/(t 2-t 1), and downloading network speed fluctuation rate from the time point t1 to the time point t2 is |XWut2-XWut1|/(t 2-t 1);
if the uploading network speed fluctuation rate of the adjacent time point exceeds the uploading network speed fluctuation rate threshold or the downloading network speed fluctuation rate of the adjacent time point exceeds the downloading network speed fluctuation rate threshold, generating a network speed abnormal signal;
if the uploading network speed fluctuation rate of the adjacent time point does not exceed the uploading network speed fluctuation rate threshold value, and the downloading network speed fluctuation rate of the adjacent time point does not exceed the downloading network speed fluctuation rate threshold value, generating a network speed normal signal;
the network monitoring module feeds back a network speed abnormal signal or a network speed normal signal to the teaching platform, and the teaching platform sends the network speed abnormal signal or the network speed normal signal to the result judging module;
the result judging module is used for judging the result of the class condition of the online class, and the work is as follows:
if the transmission normal signal and the network speed normal signal are received at the same time, no operation is performed;
if any one of the transmission abnormal signal or the network speed abnormal signal is received, generating a classroom abnormal signal and feeding back to the teaching platform;
if the teaching platform receives the classroom abnormal signal, the classroom abnormal signal is sent to a user module, and the user module is used for receiving the classroom abnormal signal and adjusting an online classroom;
specific adjustment measures may include: the network for exchanging the teacher terminal or the student terminal for an online classroom, the network for exchanging another classroom number for an online classroom, and the like are not particularly limited.
In the present application, if a corresponding calculation formula appears, the above calculation formulas are all dimensionality-removed and numerical calculation, and the size of the weight coefficient, the scale coefficient and other coefficients existing in the formulas is a result value obtained by quantizing each parameter, so long as the proportional relation between the parameter and the result value is not affected.
In another embodiment, referring to fig. 2, a teaching method of a cloud education english teaching platform is now provided, which is based on another concept of the same invention, and the teaching method specifically includes:
step S101, a history analysis module analyzes the classroom history condition of an online classroom to obtain the transmission anomaly times of the online classroom, then obtains the transmission anomaly time when the online classroom is abnormal in transmission each time, calculates the difference value of the transmission anomaly time when the online classroom is abnormal each time to obtain a plurality of groups of transmission anomaly interval time, adds and sums the groups of transmission anomaly interval time to obtain the average transmission anomaly interval time of the online classroom, and simultaneously obtains the network anomaly times of the online classroom and the network anomaly interval average time when the online classroom is abnormal each time, calculates the classroom monitoring value of the online classroom, and the history analysis module feeds back the classroom monitoring value of the online classroom to a teaching platform which sends the classroom monitoring value of the online classroom to a monitoring definition module;
step S102, a monitoring definition module sets monitoring force of an online classroom, acquires a classroom monitoring value of the online classroom, acquires a classroom monitoring threshold of the online classroom stored in a teaching platform, compares the classroom monitoring value of the online classroom with the classroom monitoring threshold to obtain monitoring points of the online classroom, the monitoring definition module feeds the monitoring points of the online classroom back to the teaching platform, the teaching platform sends monitoring parameters to a data acquisition module, when a user module enters the online classroom with a classroom number to conduct English cloud education, and when the user module reaches a monitoring point, real-time classroom data of the online classroom and real-time network data of the online classroom are acquired and sent to the teaching platform, and the teaching platform sends the real-time classroom data to a transmission monitoring module and sends the real-time network data to a network monitoring module;
step S103, a transmission monitoring module monitors the transmission condition of an online classroom, acquires real-time transmission voice and real-time receiving voice of the online classroom when the same monitoring point is adopted, converts the real-time transmission voice into a first audio waveform image, converts the real-time reception voice into a second audio waveform image, stacks the first audio waveform image and the second audio waveform image, generates a transmission normal signal if the first audio waveform image is overlapped with the second audio waveform image, counts the number of crossing points when the first audio waveform image is not overlapped with the second audio waveform image, marks the number of crossing points when the first audio waveform image is crossed with the second audio waveform image as the number of deviation points, calculates the area of a non-overlapped area of the first audio waveform image and the second audio waveform image and marks the area of the deviation, calculates the transmission deviation value of the online classroom when the monitoring point is adopted, generates a transmission abnormal signal if the transmission deviation value is larger than or equal to a transmission deviation threshold, generates the transmission normal signal if the transmission deviation value is smaller than the transmission deviation threshold, feeds back the transmission abnormal signal or the transmission normal signal to a teaching platform, and the teaching platform sends the transmission abnormal signal or the transmission abnormal signal to the transmission judgment module;
step S104, the network monitoring monitors the network condition of the online classroom, intercepts network monitoring analysis time periods of any duration in the classroom duration of the online classroom, sets a plurality of time points in the network monitoring analysis time periods, acquires real-time uploading network speed values and real-time downloading network speed values of the online classroom when the time points are set, calculates the difference value of the real-time uploading network speed values when the time points are adjacent to each other and takes absolute value to obtain real-time uploading network speed values, then calculates the time difference value corresponding to the time points, divides the real-time uploading network speed values by the real-time uploading network speed values to obtain uploading network speed fluctuation rates corresponding to the adjacent time points, and similarly calculates the downloading network speed fluctuation rates corresponding to the adjacent time points according to the method, if the uploading network speed fluctuation rates of the adjacent time points exceed uploading network speed fluctuation rate threshold values or the downloading network speed fluctuation rate of the adjacent time points exceed downloading network speed fluctuation rate threshold values, generates abnormal network speed signals, and if the uploading network speed fluctuation rates of the adjacent time points do not exceed uploading network speed fluctuation rate threshold values, and the abnormal network speed fluctuation rate signals of the adjacent time points do not exceed the uploading network speed fluctuation rate threshold values, and the abnormal teaching network speed fluctuation signal is judged to be normal by the teaching network speed fluctuation module;
step S105, the result judging module judges the result of the class situation of the online class, if the transmission normal signal and the network speed normal signal are received at the same time, no operation is performed, if any one of the transmission abnormal signal and the network speed abnormal signal is received, a class abnormal signal is generated and fed back to the teaching platform, if the teaching platform receives the class abnormal signal, the class abnormal signal is sent to the user module, and the user module receives the class abnormal signal to adjust the online class.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (9)
1. The cloud education English teaching platform is characterized by comprising a data acquisition module, a storage module, a history analysis module, a monitoring setting module, a user module, a result judging module, a network monitoring module, a transmission monitoring module and a teaching platform, wherein the user module is used for teachers and students to enter an online classroom with classroom numbers to carry out English cloud education; the storage module is used for storing the classroom history data of the online classroom and sending the classroom history data of the corresponding online classroom to the history analysis module according to the classroom number;
the history analysis module is used for analyzing the classroom history of the online classroom, and acquiring a classroom monitoring value of the online classroom and transmitting the classroom monitoring value to the monitoring definition module through the teaching platform; the monitoring definition module is used for setting the monitoring force of the online classroom, obtaining the monitoring points of the online classroom, sending the monitoring points to the data acquisition module through the teaching platform, wherein the data acquisition module is used for acquiring the real-time classroom data of the online classroom and the real-time network data of the online classroom when the monitoring points are reached and sending the real-time classroom data to the teaching platform, and the teaching platform sends the real-time classroom data to the transmission monitoring module and sends the real-time network data to the network monitoring module;
the transmission monitoring module is used for monitoring the transmission condition of an online classroom, generating a transmission abnormal signal or transmitting a transmission normal signal and sending the transmission abnormal signal to the result judging module through the teaching platform; the network monitoring is used for monitoring the network condition of an online classroom, generating a network speed abnormal signal or a network speed normal signal and feeding the network speed abnormal signal or the network speed normal signal back to the teaching platform, and the teaching platform sends the network speed abnormal signal or the network speed normal signal to the result judging module;
the result judging module is used for judging the result of the classroom condition of the online classroom, generating a classroom abnormal signal and feeding back to the teaching platform or not carrying out any operation; if the teaching platform receives the classroom abnormal signal, the classroom abnormal signal is sent to the user module, and the user module is used for receiving the classroom abnormal signal and adjusting the online classroom.
2. The cloud education English teaching platform according to claim 1, wherein the class history data is transmission abnormality times of online class, transmission abnormality time of each transmission abnormality, network abnormality times and network abnormality time of each network abnormality.
3. The cloud education english teaching platform according to claim 2, wherein the history analysis module has the following analysis process:
acquiring the transmission abnormal times and the transmission abnormal interval equal duration of an online classroom;
then acquiring the network anomaly times and the network anomaly interval equal duration of the online class;
and calculating a classroom monitoring value of the online classroom.
4. The cloud education english teaching platform according to claim 3, wherein the setting process of the monitoring definition module is specifically as follows:
acquiring a classroom monitoring value of an online classroom;
then acquiring a classroom monitoring threshold of an online classroom stored in the teaching platform;
and comparing the classroom monitoring value of the online classroom with the classroom monitoring threshold value to obtain the monitoring points of the online classroom.
5. The cloud education English teaching platform according to claim 1, wherein the real-time classroom data is real-time sending voice and real-time receiving voice of an online classroom at the monitoring point;
the real-time network data is the real-time uploading network speed value and the real-time downloading network speed value of the online class.
6. The cloud education english teaching platform according to claim 5, wherein the monitoring process of the transmission monitoring module is as follows:
acquiring real-time sending voice and real-time receiving voice of an online class at the same monitoring point;
converting the real-time transmit speech to a first audio waveform map and converting the real-time receive speech to a second audio waveform map;
stacking the first audio waveform diagram and the second audio waveform diagram;
if the first audio waveform diagram is overlapped with the second audio waveform diagram, generating a normal transmission signal;
if the first audio waveform diagram and the second audio waveform diagram are not overlapped, counting the number of the crossing points when the first audio waveform diagram and the second audio waveform diagram are crossed, marking the number as the number of the deviation points, and simultaneously, calculating the area of the non-overlapped area of the first audio waveform diagram and the second audio waveform diagram and marking the area as the deviation area;
calculating a transmission deviation value of an online classroom during monitoring points;
and generating a transmission abnormal signal if the transmission deviation value is greater than or equal to the transmission deviation threshold value, and generating a transmission normal signal if the transmission deviation value is less than the transmission deviation threshold value.
7. The cloud education english teaching platform according to claim 6, wherein the network monitoring process specifically comprises the following steps:
intercepting a network monitoring analysis period of any duration in the class duration of an online class, and setting a plurality of time points in the network monitoring analysis period;
acquiring a real-time uploading network speed value and a real-time downloading network speed value of an online classroom at a plurality of time points;
calculating a difference value of the real-time uploading network speed value when adjacent time points are calculated, taking an absolute value to obtain a real-time uploading network speed difference value, and then calculating a time difference value corresponding to the adjacent time points, wherein the real-time uploading network speed difference value is divided by the real-time uploading network speed difference value to obtain uploading network speed fluctuation rate corresponding to the adjacent time points;
similarly, obtaining the fluctuation rate of the download network speed corresponding to the adjacent time points;
if the uploading network speed fluctuation rate of the adjacent time point exceeds the uploading network speed fluctuation rate threshold or the downloading network speed fluctuation rate of the adjacent time point exceeds the downloading network speed fluctuation rate threshold, generating a network speed abnormal signal;
if the uploading network speed fluctuation rate of the adjacent time point does not exceed the uploading network speed fluctuation rate threshold value, and the downloading network speed fluctuation rate of the adjacent time point does not exceed the downloading network speed fluctuation rate threshold value, generating a network speed normal signal.
8. The cloud education english teaching platform according to claim 7, wherein the result determining module works as follows:
if the transmission normal signal and the network speed normal signal are received at the same time, no operation is performed;
if any one of the transmission abnormal signal and the network speed abnormal signal is received, generating a class abnormal signal.
9. A teaching method of a cloud education english teaching platform according to any of claims 1 to 8, wherein the teaching method specifically comprises the following steps:
step S101, a history analysis module analyzes the classroom history of an online classroom, and a classroom monitoring value of the online classroom is obtained and sent to a monitoring definition module;
step S102, a monitoring definition module sets the monitoring force of an online classroom, the monitoring points of the online classroom are obtained and sent to a data acquisition module, and the data acquisition module acquires real-time classroom data of the online classroom and real-time network data of the online classroom when the monitoring points are reached;
step S103, a transmission monitoring module monitors the transmission condition of an online classroom, generates a transmission abnormal signal or a transmission normal signal and sends the transmission abnormal signal or the transmission normal signal to a result judging module;
step S104, monitoring the network condition of an online classroom by network monitoring, generating a network speed abnormal signal or a network speed normal signal and sending the network speed abnormal signal or the network speed normal signal to a result judging module;
and step 105, the result judging module judges the result of the class condition of the online class, generates a class abnormal signal and sends the class abnormal signal to the user module or does not perform any operation, and the user module adjusts the online class.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116862729A (en) * | 2023-09-04 | 2023-10-10 | 南京恒点信息技术有限公司 | Multi-classroom online interconnection management system |
| CN116862729B (en) * | 2023-09-04 | 2023-12-08 | 南京恒点信息技术有限公司 | Multi-classroom online interconnection management system |
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