CN111861204A - Course mobile learning evaluation system and method based on intelligent platform - Google Patents
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Abstract
The invention belongs to the technical field of course mobile learning evaluation, and discloses a course mobile learning evaluation system and method based on an intelligent platform, wherein the course mobile learning evaluation system based on the intelligent platform comprises: the system comprises a user account registration module, a user login module, a course video acquisition module, a main control module, a course video enhancement module, a course video downloading module, a course testing module, a learning history recording module, a learning effect evaluation module, a teaching quality evaluation module, a cloud storage module and an updating display module. The course video enhancement module saves the resource consumption of course video image enhancement and improves the instantaneity of the course video image enhancement; the teaching quality evaluation module can be used for detecting the voice time of a teacher and the voice time of students in real time in the teaching process, and objectively evaluating the teaching quality from the dimensions such as the input degree of the teacher and the participation degree of the students.
Description
Technical Field
The invention belongs to the technical field of course mobile learning evaluation, and particularly relates to a course mobile learning evaluation system and method based on an intelligent platform.
Background
The existing course mobile learning evaluation system based on an intelligent platform has poor instantaneity and large resource consumption on the acquired course video image enhancement mode; meanwhile, the assessment of the teaching quality is generally carried out in a mode of scoring by people, and the mode is subjective and cannot objectively and truly reflect the teaching quality.
In summary, the problems and disadvantages of the prior art are: the existing course mobile learning evaluation system based on an intelligent platform has poor instantaneity and large resource consumption on the acquired course video image enhancement mode; meanwhile, the assessment of the teaching quality is generally carried out in a mode of scoring by people, and the mode is subjective and cannot objectively and truly reflect the teaching quality.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a course mobile learning evaluation system and method based on an intelligent platform.
The invention is realized in such a way that a course mobile learning evaluation method based on an intelligent platform comprises the following steps:
and step one, registering a user account of the intelligent platform-based course mobile learning evaluation system by using a registration interface and a registration program through a user account registration module.
And secondly, logging in the intelligent platform-based course mobile learning evaluation system by using a user login module and a login interface in combination with a login program.
Acquiring original video data of the course by using a camera through a course video acquisition module; and the main control module utilizes the main controller to control the normal work of each module of the intelligent platform-based course mobile learning evaluation system.
Step four, acquiring the course video data output by the course video decoding program through a course video enhancement module; inputting a course video stream on a field programmable gate array FPGA platform, and carrying out serial-parallel conversion on the course video stream to generate an odd pixel course video stream and an even pixel course video stream.
Counting the number of pixels of each gray value of a first frame image of the odd pixel course video stream by using a video enhancement program to generate a histogram of the first frame image; and enhancing the histogram of the first frame image to obtain a mapping function of the first frame image.
And step six, according to the similarity of adjacent frame images, processing by using the mapping function of the first frame image to obtain the mapping function of the second frame image, and by analogy, processing by using the mapping function of the previous frame image to obtain the mapping function of the current frame image, and generating the odd-pixel image enhancement course video stream.
And seventhly, copying the mapping function of all the frame images of the odd pixel course video stream, and processing the even pixel course video stream by using the copied mapping function to obtain an even pixel image enhanced course video stream.
And step eight, performing parallel-to-serial conversion on the odd-pixel image enhancement course video stream and the even-pixel image enhancement course video stream, and outputting an image enhancement course video stream.
Step nine, downloading the course video by using a downloading program through a course video downloading module; and testing the course knowledge of the user by using a test program through a course test module.
Step ten, recording the learning course record of the user by using a recording program through a learning history recording module; and evaluating the effect of the learning course of the user by utilizing the evaluation program through the learning effect evaluation module.
Step eleven, registering the student numbers and the teacher work numbers through a registration program, identifying the student numbers through a teaching quality evaluation module before teaching starts, correspondingly activating a first wireless microphone, and correspondingly storing the identification of the activated first wireless microphone and the student numbers in a mapping table.
Step twelve, before teaching begins, identifying a teacher's job number, activating a second wireless microphone, and correspondingly storing the identification of the second wireless microphone and the teacher's job number in a mapping table; and comparing the first accumulated value with a first threshold value, and triggering the corresponding counting program to count for 1 time when the first accumulated value is larger than the first threshold value.
Step thirteen, counting the total number of the counting programs in specific time, and storing each total number of the counting programs in a mapping table at a position corresponding to the identification of the counting program; calculating the voice time of each student and the voice time of the teacher in a specific time based on each counting sum, and storing the voice time of each student in a position corresponding to the student number in a mapping table; storing teacher voice time in a mapping table and at a position corresponding to the teacher job number; wherein the specific time is the time of a class.
And step fourteen, calculating by using an evaluation program based on the teacher voice time, the sum of the voice times of all students and the specific time in the mapping table to obtain a teaching quality evaluation result.
And fifthly, storing the acquired course videos, the registration interface, the login interface, the learning record, the learning effect evaluation result and the teaching quality evaluation result by using the cloud database server through the cloud storage module.
Sixthly, updating the course mobile learning evaluation data by using a data updating program through an updating display module, and displaying the collected course video, the registration interface, the login interface, the learning record, the learning effect evaluation result and the real-time data of the teaching quality evaluation result through a display.
Further, in step five, the method for counting the number of pixels of each gray value of a first frame image of the odd-pixel course video stream to generate a histogram of the first frame image includes:
(I) counting the pixel number of each gray value of the red channel, the green channel and the blue channel of the first frame of image of the odd pixel course video stream;
and (II) accumulating the pixel numbers of the gray values of the three channels to generate a histogram of the first frame image.
Further, in step five, the method for obtaining the mapping function of the first frame image by performing enhancement processing on the histogram of the first frame image includes:
(1) clipping the number of pixels of the histogram of the first frame image exceeding the amplitude limiting threshold value;
(2) and averagely distributing the pixel numbers exceeding the amplitude limiting threshold value to the histogram of the first frame image after cutting to obtain a mapping function of the first frame image.
Further, in step five, the method for obtaining the mapping function of the first frame image by performing enhancement processing on the histogram of the first frame image further includes:
quantizing the histogram of the first frame image to generate a first mapping function Tk；
Noting said first mapping function T kThe minimum gray value of the middle pixel number larger than the stretching threshold value is M, and the first mapping function T is subjected tokStretching to obtain a mapping function of the first frame image:
where L is the number of gray levels, k is 0,1, …, L-1.
Further, in the eleventh step and the twelfth step, the identifier of the first wireless microphone is used for uniquely identifying the first wireless microphone, and the identifier of the first wireless microphone may be a serial number of the first wireless microphone or a nickname used by the first wireless microphone to access a class teaching quality device;
the identification of the second wireless microphone can be a serial number of the second wireless microphone or a nickname used by the second wireless microphone for accessing the class teaching quality device; receiving teacher voice data frames transmitted by the second wireless microphone and student voice data frames transmitted by each first wireless microphone in real time in the teaching process, and accumulating all sampling point values in each frame of student voice data to obtain a first accumulated value; and accumulating all sampling point values in each frame of teacher voice data to obtain a second accumulated value.
Further, in the thirteenth step, the corresponding counting program is a counting program whose identifier corresponds to the frame header of the student voice data frame;
Comparing the second accumulated value with a second threshold value, and triggering a specific counting program to count for 1 time when the second accumulated value is greater than the second threshold value; the frame header of the student voice data frame is the identifier of the first wireless microphone, and the frame header of the teacher voice data frame is the identifier of the second wireless microphone;
the specific counting program is a counting program of which the identification corresponds to the frame header of the teacher voice data frame; wherein the identifier of the counting program may be a serial number of the counting program.
Further, in step fourteen, the method for calculating the teaching quality assessment result based on the teacher voice time, the sum of the voice times of all students and the specific time in the mapping table includes:
1) dividing the teacher voice time by the specific time to obtain a first ratio, and multiplying the first ratio by the occupation value of the teacher voice time in the whole evaluation system to obtain a first calculation result;
2) dividing the sum of all the student voice time by specific time to obtain a second ratio, dividing the second ratio by the number of students making voice to obtain a third ratio, and multiplying the third ratio by the occupation value of the student voice time in the whole evaluation system to obtain a second calculation result; and adding the first calculation result and the second calculation result to obtain a teaching quality evaluation result.
Another object of the present invention is to provide a curriculum mobile learning evaluation system based on an intelligent platform, which applies the curriculum mobile learning evaluation method based on an intelligent platform, and the curriculum mobile learning evaluation system based on an intelligent platform comprises:
the system comprises a user account registration module, a user login module, a course video acquisition module, a main control module, a course video enhancement module, a course video downloading module, a course testing module, a learning history recording module, a learning effect evaluation module, a teaching quality evaluation module, a cloud storage module and an updating display module.
The user account registration module is connected with the main control module and used for registering a user account of the intelligent platform-based course mobile learning evaluation system through a registration interface by using a registration program;
the user login module is connected with the main control module and used for logging in the course mobile learning evaluation system based on the intelligent platform through a login interface by using a login program;
the course video acquisition module is connected with the main control module and is used for acquiring original video data of courses through the camera;
the main control module is connected with the user account registration module, the user login module, the course video acquisition module, the course video enhancement module, the course video downloading module, the course testing module, the learning history recording module, the learning effect evaluation module, the teaching quality evaluation module, the cloud storage module and the updating display module and is used for controlling the normal work of each module of the intelligent platform-based course mobile learning evaluation system through the main controller;
The course video enhancement module is connected with the main control module and is used for enhancing the collected course video through a video enhancement program;
the course video downloading module is connected with the main control module and is used for downloading the course video through a downloading program;
the course testing module is connected with the main control module and used for testing the course knowledge of the user through a testing program;
the learning history recording module is connected with the main control module and is used for recording the learning course records of the user through a recording program;
the learning effect evaluation module is connected with the main control module and is used for evaluating the learning course effect of the user through an evaluation program;
the teaching quality evaluation module is connected with the main control module and used for evaluating the course teaching quality through an evaluation program;
the cloud storage module is connected with the main control module and used for storing the acquired course videos, the registration interface, the login interface, the learning record, the learning effect evaluation result and the teaching quality evaluation result through the cloud database server;
and the updating display module is connected with the main control module and used for updating the course mobile learning evaluation data through a data updating program and displaying the acquired course video, the registration interface, the login interface, the learning record, the learning effect evaluation result and the real-time data of the teaching quality evaluation result through the display.
Another object of the present invention is to provide a computer program product stored on a computer readable medium, which includes a computer readable program for providing a user input interface to implement the intelligent platform-based course mobile learning evaluation method when the computer program product is executed on an electronic device.
Another object of the present invention is to provide a computer-readable storage medium, which stores instructions for causing a computer to execute the intelligent platform-based course mobile learning evaluation method when the instructions are executed on the computer.
By combining all the technical schemes, the invention has the advantages and positive effects that: according to the course video enhancement module, input course video streams are subjected to serial-parallel conversion on a field programmable gate array FPGA platform to generate odd pixel course video streams and even pixel course video streams, histogram statistics is only carried out on the odd pixel course video streams, and then the odd pixel course video streams are subjected to image enhancement according to the similarity of adjacent frame images, so that the resource consumption of course video image enhancement is saved, and the instantaneity of the course video image enhancement is improved; meanwhile, a teaching quality evaluation module collects student voice data frames and teacher voice data frames in real time, all sampling point values in each frame of student voice data are accumulated to obtain a first accumulated value, all sampling point values in each frame of teacher voice data are accumulated to obtain a second accumulated value, the first accumulated value is compared with a first threshold value, when the first accumulated value is larger than the first threshold value, a corresponding counting program is triggered to count for 1 time, the second accumulated value is compared with a second threshold value, when the second accumulated value is larger than the second threshold value, a specific counting program is triggered to count for 1 time, the total number of counts of each counting program in specific time is counted to calculate the teacher voice time and the student voice time in specific time, and therefore a teaching quality evaluation result is calculated The voice time of the students is detected in real time, and the teaching quality is objectively evaluated from dimensions such as the input degree of a teacher and the participation degree of the students.
Drawings
Fig. 1 is a flowchart of a course mobile learning evaluation method based on an intelligent platform according to an embodiment of the present invention.
FIG. 2 is a block diagram of a course mobile learning evaluation system based on an intelligent platform according to an embodiment of the present invention;
in the figure: 1. a user account registration module; 2. a user login module; 3. a course video acquisition module; 4. A main control module; 5. a course video enhancement module; 6. a course video downloading module; 7. a course testing module; 8. a learning history recording module; 9. a learning effect evaluation module; 10. a teaching quality evaluation module; 11. A cloud storage module; 12. and updating the display module.
Fig. 3 is a flowchart of a method for enhancing a captured curriculum video by a video enhancement program according to an embodiment of the present invention.
Fig. 4 is a flowchart of a method for evaluating the quality of course instruction by an evaluation program according to an embodiment of the present invention.
Fig. 5 is a flowchart of a method for calculating a teaching quality assessment result based on the teacher's voice time and the sum of the voice times of all students and the specific time in the mapping table according to an embodiment of the present invention.
Detailed Description
In order to further understand the contents, features and effects of the present invention, the following embodiments are illustrated and described in detail with reference to the accompanying drawings.
The structure of the present invention will be described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the course mobile learning evaluation method based on the intelligent platform provided by the embodiment of the present invention includes the following steps:
and S101, registering the user account of the intelligent platform-based course mobile learning evaluation system by using a registration interface and a registration program through a user account registration module.
And S102, logging in the course mobile learning evaluation system based on the intelligent platform by using a user login module and a login interface in combination with a login program.
S103, acquiring original video data of the course by using a camera through a course video acquisition module; and the main control module utilizes the main controller to control the normal work of each module of the intelligent platform-based course mobile learning evaluation system.
And S104, enhancing the collected course video by utilizing a video enhancement program through a course video enhancement module.
S105, downloading the course video by using a downloading program through a course video downloading module; and testing the course knowledge of the user by using a test program through a course test module.
S106, recording the learning course record of the user by using a recording program through a learning history recording module; and evaluating the effect of the learning course of the user by utilizing the evaluation program through the learning effect evaluation module.
S107, evaluating the course teaching quality by using an evaluation program through a teaching quality evaluation module; and the acquired course videos, the registration interface, the login interface, the learning records, the learning effect evaluation result and the teaching quality evaluation result are stored by the cloud storage module through the cloud database server.
And S108, updating the course mobile learning evaluation data by using the data updating program through the updating display module, and displaying the collected course video, the registration interface, the login interface, the learning record, the learning effect evaluation result and the real-time data of the teaching quality evaluation result through the display.
As shown in fig. 2, the course mobile learning evaluation system based on the intelligent platform according to the embodiment of the present invention includes: the system comprises a user account registration module 1, a user login module 2, a course video acquisition module 3, a main control module 4, a course video enhancement module 5, a course video downloading module 6, a course testing module 7, a learning history recording module 8, a learning effect evaluation module 9, a teaching quality evaluation module 10, a cloud storage module 11 and an updating display module 12.
The user account registration module 1 is connected with the main control module 4 and used for registering a user account of the intelligent platform-based course mobile learning evaluation system through a registration interface by using a registration program;
The user login module 2 is connected with the main control module 4 and used for logging in the course mobile learning evaluation system based on the intelligent platform through a login interface by using a login program;
the course video acquisition module 3 is connected with the main control module 4 and is used for acquiring original video data of courses through a camera;
the main control module 4 is connected with the user account registration module 1, the user login module 2, the course video acquisition module 3, the course video enhancement module 5, the course video download module 6, the course test module 7, the learning history recording module 8, the learning effect evaluation module 9, the teaching quality evaluation module 10, the cloud storage module 11 and the update display module 12, and is used for controlling the normal work of each module of the intelligent platform-based course mobile learning evaluation system through the main controller;
the course video enhancement module 5 is connected with the main control module 4 and is used for enhancing the collected course video through a video enhancement program;
the course video downloading module 6 is connected with the main control module 4 and is used for downloading the course video through a downloading program;
the course testing module 7 is connected with the main control module 4 and used for testing the course knowledge of the user through a testing program;
The learning history recording module 8 is connected with the main control module 4 and is used for recording the learning course records of the user through a recording program;
the learning effect evaluation module 9 is connected with the main control module 4 and is used for evaluating the learning course effect of the user through an evaluation program;
the teaching quality evaluation module 10 is connected with the main control module 4 and used for evaluating the course teaching quality through an evaluation program;
the cloud storage module 11 is connected with the main control module 4 and used for storing the acquired course videos, the registration interface, the login interface, the learning records, the learning effect evaluation results and the teaching quality evaluation results through a cloud database server;
and the updating display module 12 is connected with the main control module 4 and is used for updating the course mobile learning evaluation data through a data updating program and displaying the acquired course video, the registration interface, the login interface, the learning record, the learning effect evaluation result and the real-time data of the teaching quality evaluation result through a display.
The invention is further described with reference to specific examples.
Example 1
As shown in fig. 1 and fig. 3, the method for evaluating course mobile learning based on an intelligent platform according to an embodiment of the present invention for enhancing a collected course video by a video enhancement program includes:
S201, obtaining the course video data output by the course video decoding program through the course video enhancement module.
S202, inputting a course video stream on a field programmable gate array FPGA platform, and performing serial-parallel conversion on the course video stream to generate an odd pixel course video stream and an even pixel course video stream.
S203, counting the number of pixels of each gray value of a first frame image of the odd pixel course video stream by using a video enhancement program, and generating a histogram of the first frame image; and enhancing the histogram of the first frame image to obtain a mapping function of the first frame image.
And S204, according to the similarity of adjacent frame images, processing by using the mapping function of the first frame image to obtain the mapping function of the second frame image, and processing by using the mapping function of the previous frame image to obtain the mapping function of the current frame image in the same way to generate the odd-pixel image enhancement course video stream.
S205, copying the mapping function of all the frame images of the odd pixel course video stream, and processing the even pixel course video stream by using the copied mapping function to obtain an even pixel image enhanced course video stream.
S206, the odd pixel image enhancement course video stream and the even pixel image enhancement course video stream are subjected to parallel-to-serial conversion, and the image enhancement course video stream is output.
The method for counting the number of pixels of each gray value of a first frame image of the odd pixel course video stream and generating the histogram of the first frame image, provided by the embodiment of the invention, comprises the following steps:
(I) counting the pixel number of each gray value of the red channel, the green channel and the blue channel of the first frame of image of the odd pixel course video stream;
and (II) accumulating the pixel numbers of the gray values of the three channels to generate a histogram of the first frame image.
The method for obtaining the mapping function of the first frame image by enhancing the histogram of the first frame image, provided by the embodiment of the invention, comprises the following steps:
(1) clipping the number of pixels of the histogram of the first frame image exceeding the amplitude limiting threshold value;
(2) and averagely distributing the pixel numbers exceeding the amplitude limiting threshold value to the histogram of the first frame image after cutting to obtain a mapping function of the first frame image.
The method for obtaining the mapping function of the first frame image by enhancing the histogram of the first frame image, provided by the embodiment of the invention, further includes:
quantizing the histogram of the first frame image to generate a first mapping function Tk；
Noting said first mapping function T kThe minimum gray value of the middle pixel number larger than the stretching threshold value is M, and the first mapping function T is subjected tokStretching to obtain a mapping function of the first frame image:
where L is the number of gray levels, k is 0,1, …, L-1.
Example 2
The course mobile learning evaluation method based on the intelligent platform provided by the embodiment of the invention is shown in fig. 1, and as a preferred embodiment, as shown in fig. 4, the method for evaluating the course teaching quality through an evaluation program provided by the embodiment of the invention comprises the following steps:
s301, the student number and the teacher' S work number are registered through a registration program, before teaching starts, the student number is identified through a teaching quality evaluation module, a first wireless microphone is correspondingly activated, and the identification of the activated first wireless microphone and the student number are correspondingly stored in a mapping table.
S302, before teaching starts, a teacher work number is identified, a second wireless microphone is activated, and the identification of the second wireless microphone and the teacher work number are correspondingly stored in a mapping table; and comparing the first accumulated value with a first threshold value, and triggering the corresponding counting program to count for 1 time when the first accumulated value is larger than the first threshold value.
S303, counting the total counting number of each counting program in a specific time, and storing each counting number in a mapping table at a position corresponding to the identifier of the counting program; and calculating the voice time of each student and the voice time of the teacher in a specific time based on each counting sum, and storing the voice time of each student in a position corresponding to the student number in the mapping table.
S304, storing the teacher voice time in a mapping table and at a position corresponding to the teacher job number; wherein the specific time is the time of a class; and calculating by using an evaluation program based on the teacher voice time, the sum of the voice times of all students and the specific time in the mapping table to obtain a teaching quality evaluation result.
The identifier of the first wireless microphone provided by the embodiment of the present invention is used to uniquely identify the first wireless microphone, and the identifier of the first wireless microphone may be a serial number of the first wireless microphone or a nickname used by the first wireless microphone to access a class teaching quality device; the identification of the second wireless microphone can be a serial number of the second wireless microphone or a nickname used by the second wireless microphone for accessing the class teaching quality device; receiving teacher voice data frames transmitted by the second wireless microphone and student voice data frames transmitted by each first wireless microphone in real time in the teaching process, and accumulating all sampling point values in each frame of student voice data to obtain a first accumulated value; and accumulating all sampling point values in each frame of teacher voice data to obtain a second accumulated value.
The corresponding counting program provided by the embodiment of the invention is a counting program of which the identification corresponds to the frame header of the student voice data frame; comparing the second accumulated value with a second threshold value, and triggering a specific counting program to count for 1 time when the second accumulated value is greater than the second threshold value; the frame header of the student voice data frame is the identifier of the first wireless microphone, and the frame header of the teacher voice data frame is the identifier of the second wireless microphone; the specific counting program is a counting program of which the identification corresponds to the frame header of the teacher voice data frame; wherein the identifier of the counting program may be a serial number of the counting program.
As shown in fig. 5, the method for calculating the teaching quality assessment result based on the teacher's voice time, the sum of the voice times of all students and the specific time in the mapping table according to the embodiment of the present invention includes:
s401, dividing the teacher voice time by the specific time to obtain a first ratio, and multiplying the first ratio by the occupation value of the teacher voice time in the whole evaluation system to obtain a first calculation result.
S402, dividing the sum of all the student voice time by specific time to obtain a second ratio, dividing the second ratio by the number of the students who send out voice to obtain a third ratio, and multiplying the third ratio by the occupation value of the student voice time in the whole evaluation system to obtain a second calculation result.
And S403, adding the first calculation result and the second calculation result to obtain a teaching quality evaluation result.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When used in whole or in part, can be implemented in a computer program product that includes one or more computer instructions. When loaded or executed on a computer, cause the flow or functions according to embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center via wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL), or wireless (e.g., infrared, wireless, microwave, etc.)). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that includes one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. The course mobile learning evaluation method based on the intelligent platform is characterized by comprising the following steps of:
registering a user account of the intelligent platform-based course mobile learning evaluation system by using a registration interface and a registration program through a user account registration module;
logging in the course mobile learning evaluation system based on the intelligent platform by using a user login module through a login interface in combination with a login program;
acquiring original video data of the course by using a camera through a course video acquisition module; the main control module utilizes the main controller to control the normal work of each module of the intelligent platform-based course mobile learning evaluation system;
step four, acquiring the course video data output by the course video decoding program through a course video enhancement module; inputting a course video stream on a Field Programmable Gate Array (FPGA) platform, and performing serial-parallel conversion on the course video stream to generate an odd-pixel course video stream and an even-pixel course video stream;
Counting the number of pixels of each gray value of a first frame image of the odd pixel course video stream by using a video enhancement program to generate a histogram of the first frame image; enhancing the histogram of the first frame image to obtain a mapping function of the first frame image;
processing the mapping function of the first frame image to obtain the mapping function of the second frame image according to the similarity of the adjacent frame images, and processing the mapping function of the previous frame image to obtain the mapping function of the current frame image by analogy to generate an odd pixel image enhancement course video stream;
step seven, copying mapping functions of all frame images of the odd pixel course video stream, and processing the even pixel course video stream by using the copied mapping functions to obtain an even pixel image enhanced course video stream;
step eight, performing parallel-to-serial conversion on the odd-pixel image enhancement course video stream and the even-pixel image enhancement course video stream, and outputting an image enhancement course video stream;
step nine, downloading the course video by using a downloading program through a course video downloading module; testing the course knowledge of the user by using a test program through a course test module;
Step ten, recording the learning course record of the user by using a recording program through a learning history recording module; evaluating the effect of the learning course of the user by utilizing an evaluation program through a learning effect evaluation module;
step eleven, registering student numbers and teacher work numbers through a registration program, identifying the student numbers through a teaching quality evaluation module before teaching starts, correspondingly activating a first wireless microphone, and correspondingly storing the identification of the activated first wireless microphone and the student numbers in a mapping table;
step twelve, before teaching begins, identifying a teacher's job number, activating a second wireless microphone, and correspondingly storing the identification of the second wireless microphone and the teacher's job number in a mapping table; comparing the first accumulated value with a first threshold value, and triggering a corresponding counting program to count for 1 time when the first accumulated value is larger than the first threshold value;
step thirteen, counting the total number of the counting programs in specific time, and storing each total number of the counting programs in a mapping table at a position corresponding to the identification of the counting program; calculating the voice time of each student and the voice time of the teacher in a specific time based on each counting sum, and storing the voice time of each student in a position corresponding to the student number in a mapping table; storing teacher voice time in a mapping table and at a position corresponding to the teacher job number; wherein the specific time is the time of a class;
Step fourteen, calculating by using an evaluation program based on the teacher voice time, the sum of the voice times of all students and specific time in the mapping table to obtain a teaching quality evaluation result;
fifteen, storing the acquired course video, a registration interface, a login interface, a learning record, a learning effect evaluation result and a teaching quality evaluation result by using a cloud database server through a cloud storage module;
sixthly, updating the course mobile learning evaluation data by using a data updating program through an updating display module, and displaying the collected course video, the registration interface, the login interface, the learning record, the learning effect evaluation result and the real-time data of the teaching quality evaluation result through a display.
2. The intelligent platform based course mobile learning evaluation method as claimed in claim 1, wherein in step five, the method for counting the number of pixels of each gray value of the first frame image of the odd pixel course video stream to generate the histogram of the first frame image comprises:
(I) counting the pixel number of each gray value of the red channel, the green channel and the blue channel of the first frame of image of the odd pixel course video stream;
And (II) accumulating the pixel numbers of the gray values of the three channels to generate a histogram of the first frame image.
3. The intelligent platform based course mobile learning evaluation method as claimed in claim 1, wherein in step five, the method for obtaining the mapping function of the first frame image by performing enhancement processing on the histogram of the first frame image includes:
(1) clipping the number of pixels of the histogram of the first frame image exceeding the amplitude limiting threshold value;
(2) and averagely distributing the pixel numbers exceeding the amplitude limiting threshold value to the histogram of the first frame image after cutting to obtain a mapping function of the first frame image.
4. The intelligent platform based course mobile learning evaluation method as claimed in claim 1, wherein in step five, the method for enhancing the histogram of the first frame image to obtain the mapping function of the first frame image further comprises:
quantizing the histogram of the first frame image to generate a first mapping function Tk；
Noting said first mapping function TkThe minimum gray value of the middle pixel number larger than the stretching threshold value is M, and the first mapping function T is subjected tokStretching to obtain a mapping function of the first frame image:
Where L is the number of gray levels, k is 0,1, …, L-1.
5. The intelligent platform based course mobile learning evaluation method of claim 1, wherein in the eleventh and twelfth steps, the identification of the first wireless microphone is used to uniquely identify the first wireless microphone, and the identification of the first wireless microphone can be the serial number of the first wireless microphone or a nickname used by the first wireless microphone to access a class teaching quality device;
the identification of the second wireless microphone can be a serial number of the second wireless microphone or a nickname used by the second wireless microphone for accessing the class teaching quality device; receiving teacher voice data frames transmitted by the second wireless microphone and student voice data frames transmitted by each first wireless microphone in real time in the teaching process, and accumulating all sampling point values in each frame of student voice data to obtain a first accumulated value; and accumulating all sampling point values in each frame of teacher voice data to obtain a second accumulated value.
6. The intelligent platform based course mobile learning evaluation method as claimed in claim 1, wherein in step thirteen, the corresponding counting program is a counting program whose identification corresponds to the frame header of the student voice data frame;
Comparing the second accumulated value with a second threshold value, and triggering a specific counting program to count for 1 time when the second accumulated value is greater than the second threshold value; the frame header of the student voice data frame is the identifier of the first wireless microphone, and the frame header of the teacher voice data frame is the identifier of the second wireless microphone;
the specific counting program is a counting program of which the identification corresponds to the frame header of the teacher voice data frame; wherein the identifier of the counting program may be a serial number of the counting program.
7. The intelligent platform based course mobile learning evaluation method as claimed in claim 1, wherein in step fourteen, the method for calculating the teaching quality evaluation result based on the teacher's voice time and the sum of all students' voice times and the specific time in the mapping table comprises:
1) dividing the teacher voice time by the specific time to obtain a first ratio, and multiplying the first ratio by the occupation value of the teacher voice time in the whole evaluation system to obtain a first calculation result;
2) dividing the sum of all the student voice time by specific time to obtain a second ratio, dividing the second ratio by the number of students making voice to obtain a third ratio, and multiplying the third ratio by the occupation value of the student voice time in the whole evaluation system to obtain a second calculation result; and adding the first calculation result and the second calculation result to obtain a teaching quality evaluation result.
8. An intelligent platform based course mobile learning evaluation system applying the intelligent platform based course mobile learning evaluation method according to any one of claims 1 to 7, wherein the intelligent platform based course mobile learning evaluation system comprises:
the system comprises a user account registration module, a user login module, a course video acquisition module, a main control module, a course video enhancement module, a course video downloading module, a course testing module, a learning history recording module, a learning effect evaluation module, a teaching quality evaluation module, a cloud storage module and an updating display module;
the user account registration module is connected with the main control module and used for registering a user account of the intelligent platform-based course mobile learning evaluation system through a registration interface by using a registration program;
the user login module is connected with the main control module and used for logging in the course mobile learning evaluation system based on the intelligent platform through a login interface by using a login program;
the course video acquisition module is connected with the main control module and is used for acquiring original video data of courses through the camera;
the main control module is connected with the user account registration module, the user login module, the course video acquisition module, the course video enhancement module, the course video downloading module, the course testing module, the learning history recording module, the learning effect evaluation module, the teaching quality evaluation module, the cloud storage module and the updating display module and is used for controlling the normal work of each module of the intelligent platform-based course mobile learning evaluation system through the main controller;
The course video enhancement module is connected with the main control module and is used for enhancing the collected course video through a video enhancement program;
the course video downloading module is connected with the main control module and is used for downloading the course video through a downloading program;
the course testing module is connected with the main control module and used for testing the course knowledge of the user through a testing program;
the learning history recording module is connected with the main control module and is used for recording the learning course records of the user through a recording program;
the learning effect evaluation module is connected with the main control module and is used for evaluating the learning course effect of the user through an evaluation program;
the teaching quality evaluation module is connected with the main control module and used for evaluating the course teaching quality through an evaluation program;
the cloud storage module is connected with the main control module and used for storing the acquired course videos, the registration interface, the login interface, the learning record, the learning effect evaluation result and the teaching quality evaluation result through the cloud database server;
and the updating display module is connected with the main control module and used for updating the course mobile learning evaluation data through a data updating program and displaying the acquired course video, the registration interface, the login interface, the learning record, the learning effect evaluation result and the real-time data of the teaching quality evaluation result through the display.
9. A computer program product stored on a computer readable medium, comprising a computer readable program for providing a user input interface to implement the intelligent platform based course mobile learning evaluation method of any one of claims 1-7 when executed on an electronic device.
10. A computer-readable storage medium storing instructions which, when executed on a computer, cause the computer to perform the intelligent platform based course mobile learning evaluation method according to any one of claims 1 to 7.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112990677A (en) * | 2021-03-04 | 2021-06-18 | 青岛海科创新科技有限公司 | Teaching system, computer equipment and storage medium based on artificial intelligence |
| CN112995178A (en) * | 2021-02-25 | 2021-06-18 | 上海吉盛网络技术有限公司 | Elevator multi-party call device with remote callback function |
| CN117807631A (en) * | 2023-12-29 | 2024-04-02 | 北京万讯博通科技发展有限公司 | Online evaluation method and system based on multiparty security calculation |
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2020
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112995178A (en) * | 2021-02-25 | 2021-06-18 | 上海吉盛网络技术有限公司 | Elevator multi-party call device with remote callback function |
| CN112995178B (en) * | 2021-02-25 | 2023-04-25 | 上海吉盛网络技术有限公司 | Elevator multiparty call device with remote callback function |
| CN112990677A (en) * | 2021-03-04 | 2021-06-18 | 青岛海科创新科技有限公司 | Teaching system, computer equipment and storage medium based on artificial intelligence |
| CN112990677B (en) * | 2021-03-04 | 2022-03-01 | 青岛海科虚拟现实研究院 | Teaching system, computer equipment and storage medium based on artificial intelligence |
| CN117807631A (en) * | 2023-12-29 | 2024-04-02 | 北京万讯博通科技发展有限公司 | Online evaluation method and system based on multiparty security calculation |
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