CN117934220A - Teaching quality evaluation system and method based on 5G network - Google Patents
Teaching quality evaluation system and method based on 5G network Download PDFInfo
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Abstract
The invention provides a teaching quality evaluation system and method based on a 5G network, and relates to the technical field of teaching quality evaluation systems. According to the invention, the integral growth module, the integral rewarding module and the integral counting module are arranged, and the integral and rewarding module is introduced in course learning to serve as positive feedback of student learning, so that the learning enthusiasm of students can be improved, the students are encouraged to participate in courses all around, communication interaction is carried out with teachers, positive feedback is provided for the students, the effects of activating classroom atmosphere and improving teaching quality are achieved, meanwhile, the teaching quality can be comprehensively evaluated through integral data and score of the students, and the unilaterality of judging the teaching quality only by score is reduced.
Description
Technical Field
The invention relates to the technical field of teaching quality evaluation systems, in particular to a teaching quality evaluation system and method based on a 5G network.
Background
The 5G network service platform is used for providing various telecommunication and data services, including telephone, video data messaging, etc., and has many applications in the work and life of people.
Along with the development of technology, when students are inconvenient to go to school, teachers often use a 5G video call mode to give lessons, and the video call mode is not long in time, so that the teaching mode has a plurality of technical pain points. For example, in video call teaching, interaction between a teacher and students is lacking, students are easy to cause lack of teaching enthusiasm, meanwhile, as the teacher cannot observe the whole of the students, it is difficult to judge the mastering condition of the students to a certain knowledge point by means of teaching experience, and how to judge the teaching quality of the students is not, if the teaching quality is evaluated by means of test only, other problems are difficult to find on the premise of exceeding the teaching quality, the students are easy to generate adverse psychological effects, and the test result is poor after long time. Therefore, for the above reasons, it is necessary to provide a system capable of improving the enthusiasm of students in class, increasing interactions between students and teachers, and evaluating the teaching quality through multiple angles.
The above information disclosed in the background section is only for enhancement of understanding of the background of the disclosure and therefore it may include information that does not form the prior art that is already known to a person of ordinary skill in the art.
Disclosure of Invention
The invention aims to provide a teaching quality evaluation system and method based on a 5G network, which are used for solving the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions:
A teaching quality evaluation system based on a 5G network comprises a teacher end and a plurality of groups of student ends, wherein:
the student end comprises a data acquisition module, a first data transmission module, an operation module and a first storage module;
The data acquisition module is electrically connected with the first data transmission module and is used for acquiring learning data of students during video learning and transmitting the learning data to the first data transmission module;
The first data transmission module is electrically connected with the operation module and the first storage module, is in communication connection with the teacher end, and is used for sending personal point data, point growth data and point exchange data received from the teacher end to the first storage module, sending test data to the operation module and sending learning data and a score coefficient to the teacher end;
The operation module is used for generating a scoring coefficient according to the test data and sending the scoring coefficient to the first data transmission module;
The first storage module is electrically connected with the first data transmission module and used for storing personal point data, point growth data and point exchange data;
The teacher end comprises a second data transmission module, an integral growth module, an integral rewarding module, an integral statistics module, a test module, a second storage module and a data analysis module;
The second data transmission module is in communication connection with the first data transmission module and is used for receiving the learning data and the score coefficient and sending the learning data and the score coefficient to the integral growth module;
The integral growth module is electrically connected with the second data transmission module and the integral statistics module and is used for generating integral growth data according to the learning data and the score coefficient and sending the integral growth data and the score coefficient to the integral statistics module;
the point rewarding module is electrically connected with the point counting module and is used for setting different rewarding items to be converted, generating point conversion data according to conversion contents and sending the point conversion data to the point counting module;
The point counting module is electrically connected with the point growing module, the point rewarding module, the second storage module and the data analysis module and is used for generating personal point data and maximum point data according to the point growing data and the point exchange data, sending the personal point data, the point growing data and the point exchange data to the second data transmission module and the second storage module and sending the maximum point data and the score coefficient to the data analysis module;
The test module is electrically connected with the second data transmission module and is used for generating test data and transmitting the test data to the second data transmission module;
The second storage module is used for storing personal point data, point growth data and point exchange data;
The data analysis module is used for evaluating the teaching quality according to the maximum integral data and the score coefficient.
Preferably, the learning data includes a learning start time, a learning end time, and the number of interactions.
Preferably, the quiz data includes question data and encrypted answer data.
Preferably, the generating logic of the score coefficient is as follows:
The operation module is utilized to answer the question data, answer data are generated, the answer data are compared with the answer data, a score coefficient A (x,y) is calculated, and the calculation mode is as follows: a (x,y) =n/N, where N represents the number of questions in the answer data that are answered correctly, N represents the total number of questions in the question data, X and Y represent the number of tests and the number of labels at the student's end, respectively, X and Y are positive integers, x=1, 2,3 … X, and y=1, 2,3 … Y.
Preferably, the generating logic of the personal integral data and the maximum integral data is as follows:
When each course starts and ends, collecting learning starting time and learning ending time of students, comparing the learning starting time and the learning ending time with preset standard starting time and standard ending time to obtain the times of the students on-time class and off-time class, calibrating the times as time keeping times j, generating time keeping rate B (x,m) according to the time keeping times j, and calculating in a mode of B (x,m) =j/M, wherein M represents the course times, M is a positive integer, and m=1, 2 and 3 … M;
Generating first growth data Dz1 (x,y) according to the score coefficient A (x,y), generating second growth data Dz2 (x,m) according to the time keeping rate B (x,m) and the interaction times C (x,m), wherein the calculation formulas of the first growth data Dz1 (x,y) and the second growth data Dz2 (x,m) are respectively as follows:
After the calculation is completed, rounding the first increment data Dz1 (x,y) and the second increment data Dz2 (x,m) according to a tail-removing method, wherein mu represents the minimum unit integral, and mu is a positive integer;
The integral growth data D x is obtained according to the first growth data Dz1 (x,y) and the second growth data Dz2 x, and the calculation formula is as follows:
And then calculating personal integral data F x and maximum integral data G, wherein the calculation formula is as follows:
Wherein E (x,p) represents point redemption data, subscript P represents redemption times, P is a positive integer, and p=1, 2,3 … P.
Preferably, the logic for evaluating the teaching quality is:
taking the end of each test as an evaluation node of a teaching stage, and generating an evaluation coefficient according to the score coefficient A (x,y) By means of the evaluation coefficient/>Evaluating course score in teaching quality, wherein the calculation formula is as follows:
Wherein A' represents a preset passing ratio coefficient;
Comparing the maximum integral data G with a preset integral threshold Gyz to evaluate the teaching atmosphere in the teaching quality;
when evaluating coefficient When the course score in the teaching quality is considered to reach the standard;
when evaluating coefficient When the course score in the teaching quality is considered to be not up to the standard;
when the maximum integral data G is more than or equal to Gyz, the teaching atmosphere in the teaching quality is considered to reach the standard;
And when the maximum integral data G is less than Gyz, the teaching atmosphere in the teaching quality is considered to be unsatisfied with the standard.
The teaching quality evaluation method based on the 5G network is suitable for the evaluation system and comprises the following steps:
Collecting learning data and score coefficients of each student end;
Obtaining integral growth data of each student end according to the learning data and the score coefficient, and respectively calculating personal integral data and maximum integral data according to the integral growth data and the integral exchange data;
And generating an evaluation coefficient according to the score coefficient, and comprehensively evaluating the teaching quality by using the evaluation coefficient and the maximum integral data.
Compared with the prior art, the invention has the beneficial effects that: according to the invention, the integral growth module, the integral rewarding module and the integral counting module are arranged, and the integral and rewarding module is introduced in course learning to serve as positive feedback of student learning, so that the learning enthusiasm of students can be improved, the students are encouraged to participate in courses all around, communication interaction is performed more than teachers, positive feedback is provided for the students, the effects of activating classroom atmosphere and improving teaching quality are achieved, meanwhile, the teaching quality can be comprehensively evaluated through integral data and score of the students, and the unilaterality of the teaching quality only judged by score is reduced.
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FIG. 1 is a schematic diagram of the overall module of the present invention;
FIG. 2 is a flow chart of the present invention.
Detailed Description
The present invention will be further described in detail with reference to specific embodiments in order to make the objects, technical solutions and advantages of the present invention more apparent.
It is to be noted that unless otherwise defined, technical or scientific terms used herein should be taken in a general sense as understood by one of ordinary skill in the art to which the present invention belongs. The terms "first," "second," and the like, as used herein, do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that elements or items preceding the word are included in the element or item listed after the word and equivalents thereof, but does not exclude other elements or items. The terms "connected" or "connected," and the like, are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "up", "down", "left", "right" and the like are used only to indicate a relative positional relationship, and when the absolute position of the object to be described is changed, the relative positional relationship may be changed accordingly.
Examples:
Referring to fig. 1-2, the present invention provides a technical solution:
The teaching quality evaluation system based on the 5G network comprises a teacher end and a plurality of groups of student ends, wherein the teaching quality evaluation system is respectively suitable for teachers and students, the teacher end and the student ends are both formed based on PC computers, and a one-to-many mode is formed by using the 5G network, wherein:
The student end comprises a data acquisition module, a first data transmission module, an operation module and a first storage module.
The data acquisition module is electrically connected with the first data transmission module and is used for acquiring learning data of students during video learning and sending the learning data to the first data transmission module, wherein the learning data comprises learning start time, learning end time and interaction times, the learning start time and the learning end time are used for judging whether the students have early and late situations such as falling back to an open class or not, the interaction mode comprises the steps of asking questions to a teacher through videos, answering the questions of the teacher and other teachers and students, the interaction can be initiated by the student end or the teacher end, but the students can be judged to be effective only after the teacher end confirms the learning data, and then the interaction times on the corresponding students are increased.
The first data transmission module is electrically connected with the operation module and the first storage module, is in communication connection with the teacher end, and is used for sending personal point data, point increase data and point exchange data received from the teacher end to the first storage module, sending test data to the operation module and sending learning data and a score coefficient to the teacher end.
The operation module is used for providing answering environments for students, including but not limited to input modules such as a touch screen and a virtual keyboard, and can enable the students to fill in test data, generate score coefficients and send the score coefficients to the first data transmission module.
The first storage module is electrically connected with the first data transmission module and used for storing personal point data, point growth data and point exchange data.
The teacher end comprises a second data transmission module, an integral growth module, an integral rewarding module, an integral statistics module, a test module, a second storage module and a data analysis module.
The second data transmission module is in communication connection with the first data transmission module and is used for receiving the learning data and the score coefficient and sending the learning data and the score coefficient to the integral growth module.
The integral growth module is electrically connected with the second data transmission module and the integral statistics module, and is used for generating integral growth data according to the learning data and the score coefficient and sending the integral growth data and the score coefficient to the integral statistics module.
The point rewarding module is electrically connected with the point counting module and is used for setting different rewarding items to be converted, generating point conversion data according to conversion contents and sending the point conversion data to the point counting module.
The point statistics module is electrically connected with the point growth module, the point rewarding module, the second storage module and the data analysis module, and is used for generating personal point data and maximum point data according to the point growth data and the point exchange data, sending the personal point data, the point growth data and the point exchange data to the second data transmission module and the second storage module, and sending the maximum point data and the score coefficient to the data analysis module.
The test module is electrically connected with the second data transmission module and is used for generating test data and sending the test data to the second data transmission module, wherein the test data comprises question data and encrypted answer data.
The second storage module is used for storing personal point data, point growth data and point exchange data, and the first storage module and the second storage module are arranged for storing the personal point data, the point growth data and the point exchange data together, so that teachers and students can check the change of the data conveniently, and the second storage module plays a role in backup, and the situation that the data at a certain end is difficult to retrieve after losing is avoided.
The data analysis module is used for evaluating the teaching quality according to the maximum integral data and the score coefficient.
The generation logic of the score coefficient is as follows:
The operation module is utilized to answer the question data, answer data are generated, the answer data are compared with the answer data, a score coefficient A (x,y) is calculated and used for representing the accuracy of the student in the test, and the calculation mode is as follows: a (x,y) =n/N, where N represents the number of questions in the answer data that are answered correctly, N represents the total number of questions in the question data, X and Y represent the number of tests and the number of labels at the student's end, respectively, X and Y are positive integers, x=1, 2,3 … X, and y=1, 2,3 … Y.
The generation logic of the personal integral data and the maximum integral data is as follows:
And when each course starts and ends, collecting the learning starting time and the learning ending time of the student, comparing the learning starting time and the learning ending time with the preset standard starting time and standard ending time to obtain the times of the student on-time class and the time class, calibrating the times as the time keeping times j, generating a time keeping rate B (x,m) according to the time keeping times j, wherein the calculation mode is B (x,m) =j/M, M represents the course times, M is a positive integer, m=1, 2,3 … M, and the time keeping rate B (x,m) represents the duty ratio of the student on-time class and the time class in M courses.
Generating first growth data Dz1 (x,y) according to the score coefficient A (x,y), generating second growth data Dz2 (x,m) according to the time keeping rate B (x,m) and the interaction times C (x,m), wherein the calculation formulas of the first growth data Dz1 (x,y) and the second growth data Dz2 (x,m) are respectively as follows:
After the calculation is completed, the first growth data Dz1 (x,y) and the second growth data Dz2 (x,m) are rounded according to a tail-biting method, that is, the decimal part is completely truncated to be rounded, wherein μ represents the minimum unit integral, and μ is a positive integer.
In the middle ofThe average score coefficient of the whole class students in the test is represented, and the average score coefficient of the whole class students is close to the score coefficient A (x,y) of a certain student, so that when the score coefficient A (x,y) of the certain student is larger than or equal to the average score coefficient of the whole class students, the value of the first increment data Dz1 (x,y) is larger than or equal to mu and smaller than 2 mu, the value is mu after rounding, when the score coefficient A (x,y) of the certain student is smaller than the average score coefficient of the whole class students, the value of the second increment data Dz2 (x,m) is larger than 0 and smaller than mu, the value is 0 after rounding, in other words, when the test score of the certain student is larger than or equal to the average score coefficient of the whole class students, the mu integral can be obtained, otherwise, the mu integral is not obtained.
In the same way, the processing method comprises the steps of,The average time keeping rate of all class students in m courses is represented, when a certain student finishes the course, the time keeping rate B (x,m) of the student is larger than or equal to the average time keeping rate of all class students, mu integral can be obtained, otherwise, mu integral is not obtained.
It can be seen that the scores available through the examination and on-time lessons are less, and because the scores belong to some basic responsibilities of students, the obtained returns are also lower, but the scores available through interaction with teachers are more, so that the students are encouraged to participate in the lessons all around, and the students are mostly in communication interaction with the teachers, so that positive feedback is provided for the students, and the functions of activating the atmosphere of the classroom and improving the teaching quality are achieved.
The integral growth data D x is obtained according to the first growth data Dz1 (x,y) and the second growth data Dz2 x, and the calculation formula is as follows:
The integral increment data D x represents the integral sum obtained by the student through testing, on-time lesson taking, and interaction with the teacher, and the second increment data Dz2 (x,m) is accumulated from m=3, which considers that the teacher may be used to conduct lesson introduction, self introduction, outline combing, and other works in the previous two lessons, and the student may not be familiar with the fact that no standard point is available in the first lesson taking, so that the influence of uncontrollable reasons on subsequent evaluation is avoided.
And then calculating personal integral data F x and maximum integral data G, wherein the calculation formula is as follows:
Wherein E (x,p) represents point redemption data, subscript P represents redemption times, P is a positive integer, and p=1, 2,3 … P.
For example, a teacher sets "exempt from homework once" as a reward, and certain points are required to be exchanged correspondingly, after a certain student exchanges, point exchange data E (x,p) is generated, personal point data F x represents the current remaining point number of a certain student after exchange, maximum point data G represents the sum of all student point increase data D x, and as can be seen from the calculation formula of the point increase data D x, the larger the maximum point data G is, the more the class atmosphere of the student is consistent.
The logic for evaluating the teaching quality is as follows:
taking the end of each test as an evaluation node of a teaching stage, and generating an evaluation coefficient according to the score coefficient A (x,y) By means of the evaluation coefficient/>Evaluating course score in teaching quality, wherein the calculation formula is as follows:
wherein A' represents a predetermined passing scale factor.
And comparing the maximum integral data G with a preset integral threshold Gyz to evaluate the teaching atmosphere in the teaching quality.
In the middle ofRepresenting average score coefficient of students in whole class, and when the average score coefficient is greater than or equal to the pass proportion coefficient A', carrying out the process of/>When the average score coefficient is smaller than the pass ratio coefficient A', the method comprises the following steps of
When evaluating coefficientAnd when the course score in the teaching quality reaches the standard.
When evaluating coefficientAnd when the course performance in the teaching quality is not up to the standard.
And when the maximum integral data G is more than or equal to Gyz, the teaching atmosphere in the teaching quality is considered to reach the standard.
And when the maximum integral data G is less than Gyz, the teaching atmosphere in the teaching quality is considered to be unsatisfied with the standard.
No matter which aspect is not up to standard, targeted improvement is needed.
The invention also provides a teaching quality evaluation method based on the 5G network, which is suitable for the evaluation system and comprises the following steps:
Learning data and scoring coefficients of each student are collected.
And obtaining integral growth data of each student end according to the learning data and the score coefficient, and respectively calculating personal integral data and maximum integral data according to the integral growth data and the integral exchange data.
And generating an evaluation coefficient according to the score coefficient, and comprehensively evaluating the teaching quality by using the evaluation coefficient and the maximum integral data.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. Those of skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application.
Claims (7)
1. The teaching quality evaluation system based on the 5G network is characterized by comprising a teacher end and a plurality of groups of student ends, wherein:
the student end comprises a data acquisition module, a first data transmission module, an operation module and a first storage module;
The data acquisition module is electrically connected with the first data transmission module and is used for acquiring learning data of students during video learning and transmitting the learning data to the first data transmission module;
The first data transmission module is electrically connected with the operation module and the first storage module, is in communication connection with the teacher end, and is used for sending personal point data, point growth data and point exchange data received from the teacher end to the first storage module, sending test data to the operation module and sending learning data and a score coefficient to the teacher end;
The operation module is used for generating a scoring coefficient according to the test data and sending the scoring coefficient to the first data transmission module;
The first storage module is electrically connected with the first data transmission module and used for storing personal point data, point growth data and point exchange data;
The teacher end comprises a second data transmission module, an integral growth module, an integral rewarding module, an integral statistics module, a test module, a second storage module and a data analysis module;
The second data transmission module is in communication connection with the first data transmission module and is used for receiving the learning data and the score coefficient and sending the learning data and the score coefficient to the integral growth module;
The integral growth module is electrically connected with the second data transmission module and the integral statistics module and is used for generating integral growth data according to the learning data and the score coefficient and sending the integral growth data and the score coefficient to the integral statistics module;
the point rewarding module is electrically connected with the point counting module and is used for setting different rewarding items to be converted, generating point conversion data according to conversion contents and sending the point conversion data to the point counting module;
The point counting module is electrically connected with the point growing module, the point rewarding module, the second storage module and the data analysis module and is used for generating personal point data and maximum point data according to the point growing data and the point exchange data, sending the personal point data, the point growing data and the point exchange data to the second data transmission module and the second storage module and sending the maximum point data and the score coefficient to the data analysis module;
The test module is electrically connected with the second data transmission module and is used for generating test data and transmitting the test data to the second data transmission module;
The second storage module is used for storing personal point data, point growth data and point exchange data;
The data analysis module is used for evaluating the teaching quality according to the maximum integral data and the score coefficient.
2. The teaching quality evaluation system based on the 5G network according to claim 1, wherein: the learning data comprises learning start time, learning end time and interaction times.
3. The teaching quality evaluation system based on the 5G network according to claim 2, wherein: the quiz data includes question data and encrypted answer data.
4. A system for evaluating teaching quality based on a 5G network according to claim 3, wherein: the generation logic of the score coefficient is as follows:
The operation module is utilized to answer the question data, answer data are generated, the answer data are compared with the answer data, a score coefficient A (x,y) is calculated, and the calculation mode is as follows: a (x,y) =n/N, where N represents the number of questions in the answer data that are answered correctly, N represents the total number of questions in the question data, X and Y represent the number of tests and the number of labels at the student's end, respectively, X and Y are positive integers, x=1, 2,3 … X, and y=1, 2,3 … Y.
5. The teaching quality evaluation system based on the 5G network according to claim 4, wherein: the generation logic of the personal integral data and the maximum integral data is as follows:
When each course starts and ends, collecting learning starting time and learning ending time of students, comparing the learning starting time and the learning ending time with preset standard starting time and standard ending time to obtain the times of the students on-time class and off-time class, calibrating the times as time keeping times j, generating time keeping rate B (x,m) according to the time keeping times j, and calculating in a mode of B (x,m) =j/M, wherein M represents the course times, M is a positive integer, and m=1, 2 and 3 … M;
Generating first growth data Dz1 (x,y) according to the score coefficient A (x,y), generating second growth data Dz2 (x,m) according to the time keeping rate B (x,m) and the interaction times C (x,m), wherein the calculation formulas of the first growth data Dz1 (x,y) and the second growth data Dz2 (x,m) are respectively as follows:
After the calculation is completed, rounding the first increment data Dz1 (x,y) and the second increment data Dz2 (x,m) according to a tail-removing method, wherein mu represents the minimum unit integral, and mu is a positive integer;
The integral growth data D x is obtained according to the first growth data Dz1 (x,y) and the second growth data Dz2 x, and the calculation formula is as follows:
And then calculating personal integral data F x and maximum integral data G, wherein the calculation formula is as follows:
Wherein E (x,p) represents point redemption data, subscript P represents redemption times, P is a positive integer, and p=1, 2,3 … P.
6. The teaching quality evaluation system based on the 5G network according to claim 5, wherein: the logic for evaluating the teaching quality is as follows:
taking the end of each test as an evaluation node of a teaching stage, and generating an evaluation coefficient according to the score coefficient A (x,y) Evaluating course score in the teaching quality by using an evaluation coefficient phi, wherein a calculation formula is as follows:
Wherein A' represents a preset passing ratio coefficient;
Comparing the maximum integral data G with a preset integral threshold Gyz to evaluate the teaching atmosphere in the teaching quality;
when evaluating coefficient When the course score in the teaching quality is considered to reach the standard;
when evaluating coefficient When the course score in the teaching quality is considered to be not up to the standard;
when the maximum integral data G is more than or equal to Gyz, the teaching atmosphere in the teaching quality is considered to reach the standard;
And when the maximum integral data G is less than Gyz, the teaching atmosphere in the teaching quality is considered to be unsatisfied with the standard.
7. A teaching quality evaluation method based on a 5G network is characterized by comprising the following steps: the evaluation method is applicable to the evaluation system of any one of claims 1-6, and comprises the following steps:
Collecting learning data and score coefficients of each student end;
Obtaining integral growth data of each student end according to the learning data and the score coefficient, and respectively calculating personal integral data and maximum integral data according to the integral growth data and the integral exchange data;
And generating an evaluation coefficient according to the score coefficient, and comprehensively evaluating the teaching quality by using the evaluation coefficient and the maximum integral data.
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