CN116138780B - Student attention evaluation method, terminal and computer readable storage medium - Google Patents
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Abstract
The application discloses a student attention evaluation method, a terminal and a computer readable storage medium, wherein the method firstly acquires electroencephalogram data of a plurality of students acquired by a plurality of electroencephalograms, processes the electroencephalogram data to obtain concentration parameter data of the plurality of students, and takes the concentration parameter data of a target student as first concentration data; then, obtaining and calculating the average value of the concentration parameter data of other students except the target student to obtain second concentration data; and finally, continuously calculating the first concentration data and the second concentration data in a continuous time interval to obtain a first concentration data array and a second concentration data array, calculating the correlation between the first concentration data array and the second concentration data array, and processing the obtained correlation result to obtain the attention evaluation result of the target student. Thereby improving the accuracy of the attention evaluation of the students in the learning process.
Description
Technical Field
The present invention relates to the field of data analysis technologies, and in particular, to a student attention evaluation method, a terminal, and a computer readable storage medium.
Background
The level of attention of a student during class can greatly affect the efficiency and effectiveness of the student's learning. To achieve objective assessment of student learning effects, attention levels of individuals have been analyzed and evaluated by electroencephalography.
However, in the existing method, the evaluation of the attention level may be irrelevant to tasks, that is, if the student does not carefully listen and talk in the course of the lesson, but is focused on doing other things irrelevant to the lesson, the measured attention level at this time may also be high, so that the attention level of the student learned in the lesson cannot be accurately evaluated. Therefore, the prior art has low accuracy in evaluating the level of attention that students learn in a class.
Disclosure of Invention
Based on this, the embodiment of the application provides a student attention evaluation method, a terminal and a computer readable storage medium, which can improve the accuracy of attention evaluation of students in the learning process.
In a first aspect, there is provided a student attention assessment method, the method comprising:
acquiring electroencephalogram data of a plurality of students acquired by a plurality of electroencephalograms, processing the electroencephalogram data to obtain concentration parameter data of the plurality of students, and taking the concentration parameter data of a target student as first concentration data; wherein, each electroencephalograph collects electroencephalogram data of one student;
acquiring and calculating average values of concentration parameter data of other students except the target students to obtain second concentration data;
continuously calculating first concentration data and second concentration data in a continuous time interval to obtain a first concentration data array and a second concentration data array, calculating the correlation between the first concentration data array and the second concentration data array, and processing the obtained correlation result to obtain the attention evaluation result of the target students.
Optionally, acquiring and calculating an average value of concentration parameter data of students other than the target student to obtain second concentration data, including:
acquiring concentration parameter data of other students except the target student;
calculating the average value of the concentration parameter data of other students as first preprocessing data;
calculating standard deviation of concentration parameter data of other students as second preprocessing data;
calculating third preprocessing data of each student in other students according to the first preprocessing data and the second preprocessing data; the third preprocessing data is used for representing the degree of dispersion of the student concentration parameter data;
screening out the third preprocessed data according to the first preset threshold value and the second preset threshold value;
and calculating the average value of the concentration parameter data of the students remaining after screening to obtain second concentration data.
Optionally, calculating third preprocessing data of each of the other students according to the first preprocessing data and the second preprocessing data, including:
determining and obtaining third preprocessing data of each student in other students according to a first formula, wherein the first formula specifically comprises the following steps:
wherein Z is i Third pre-processed data representing the ith student, X i Representing the value of the concentration parameter of the ith student,representing first pre-processed data and S representing second pre-processed data.
Optionally, screening the third preprocessed data according to the first preset threshold and the second preset threshold includes:
and removing the data corresponding to the students with the third preprocessing data larger than the first preset threshold value or smaller than the second preset threshold value.
Optionally, calculating the correlation between the first concentration data array and the second concentration data array, and processing the obtained correlation result to obtain the attention evaluation result of the target student, including:
determining a correlation result according to a second formula, wherein the second formula specifically comprises:
wherein X represents the first focused data array, Y represents the second focused data array, N represents the number of data in the array, and P represents the correlation result of the student.
Optionally, processing the obtained correlation result to obtain an attention evaluation result of the target student includes:
determining the attention evaluation result of the target student according to a third formula, wherein the third formula specifically comprises:
in the above formula, A max A maximum threshold value representing the result of attention evaluation, A min The minimum threshold value of the attention evaluation result is represented by P, the correlation result of the student, and a, the attention evaluation result.
Optionally, the method further comprises:
performing continuous calculation on the time sequence to obtain an attention evaluation result array of the target students in time continuity;
traversing all students to obtain an attention evaluation result array of each student;
calculating standard deviations of the attention evaluation result arrays of all students in each period in the time sequence to obtain a first score curve;
calculating the average value of the attention evaluation result arrays of all students in each period in the time sequence to obtain a second score curve;
determining a first teaching effect evaluation index according to the first score curve and the second score curve;
and processing the first teaching effect evaluation index to obtain a second teaching effect evaluation index, wherein the second teaching effect evaluation index is used for representing the teaching effect of a classroom.
Optionally, determining a first teaching effect evaluation index according to the first score curve and the second score curve, and processing the first teaching effect evaluation index to obtain a second teaching effect evaluation index, including:
determining a first teaching effect evaluation index according to a fourth formula, wherein the fourth formula specifically comprises:
wherein sigma i A first score curve, x, representing teaching effects i A second score curve representing teaching effect, T representing total duration of lessons, E 1 Representing a first teaching effect evaluation index;
and processing the first teaching effect evaluation index according to a fifth formula to obtain a second teaching effect evaluation index, wherein the fifth formula specifically comprises:
wherein E is 2 Representing a second teaching effect evaluation index, E max Is the maximum threshold value of the second teaching effect evaluation index, E min Is the minimum threshold value of the second teaching effect evaluation index, E 1 And the first teaching effect evaluation index is represented.
In a second aspect, there is provided a student attention evaluation terminal including a memory and a processor, the memory storing a computer program, the processor implementing the student attention evaluation method of any one of the first aspects described above when executing the computer program.
In a third aspect, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the student attention assessment method of any one of the above first aspects.
The beneficial effects of this application lie in:
when the conventional technique evaluates the level of attention of a student in a course by electroencephalogram, it is impossible to accurately evaluate the level of attention of the student in the course because it is impossible to distinguish whether the student is carefully listening to the course or is concentrating on doing something unrelated to the content of the class.
The method provided by the invention can effectively eliminate the interference on the assessment of the class attention level caused by the concentration of students and other things, and can accurately assess the attention level of students in class. In addition, through analysis and calculation of the teaching attention levels of all students, evaluation indexes of teaching effects of the classes can be obtained, so that teachers can be helped to know the learning conditions of the students in the classes, and the teachers can be helped to adjust teaching methods according to the evaluation of the teaching effects.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It will be apparent to those of ordinary skill in the art that the drawings in the following description are exemplary only and that other implementations can be obtained from the extensions of the drawings provided without inventive effort.
FIG. 1 is a flow chart of steps of a student attention assessment method provided in an embodiment of the present application;
fig. 2 is a step flowchart of a teaching effect evaluation method provided in an embodiment of the present application;
fig. 3 is a schematic diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Other advantages and advantages of the present invention will become apparent to those skilled in the art from the following detailed description, which, by way of illustration, is to be read in connection with certain specific embodiments, but 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 the description of the present invention, unless otherwise indicated, "a plurality" means two or more. The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the invention and in the foregoing drawings are intended to distinguish between the objects referred to. For schemes with time sequence flows, such term expressions are not necessarily to be understood as describing a specific order or sequence, nor are such term expressions to distinguish between importance levels, positional relationships, etc. for schemes with device structures.
Furthermore, the terms "comprises," "comprising," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements that are expressly listed but may include other steps or elements not expressly listed but inherent to such process, method, article, or apparatus or steps or elements that may be added based on a further optimization of the inventive concept.
The main object of the present invention is to provide a method, a terminal and a computer-readable storage medium for attention assessment, which aim to improve the accuracy of attention assessment in learning. In order to achieve the above object, in an implementation scenario of the present application, the present invention provides an attention evaluation method applied to a plurality of electroencephalographs and an attention evaluation terminal. Meanwhile, in the embodiment of the application, attention evaluation applied to the learning process of students is given, and follow-up contents can evaluate attention of scenes such as staff training and working.
Referring to fig. 1, a flowchart of a student attention evaluation method according to an embodiment of the present application is shown, where the method may include the following steps:
step 101, acquiring electroencephalogram data of a plurality of students acquired by a plurality of electroencephalograms, processing the electroencephalogram data to obtain concentration parameter data of the plurality of students, and taking the concentration parameter data of a target student as first concentration data.
The target student may refer to a student currently waiting for attention evaluation, and the electroencephalogram data may be EEG data.
In the embodiment of the application, in the course of class, each student wears an electroencephalogram instrument, and the electroencephalogram data of each student in the course of class is collected simultaneously through the electroencephalogram instrument, and the electroencephalogram data of each student is transmitted to the attention evaluation terminal. And the electroencephalogram data extraction module of the terminal obtains the concentration parameter value of each student through the electroencephalogram data.
An attention assessment value for an individual student is calculated by a first analysis module. And acquiring the concentration parameter value of the student through an electroencephalogram data extraction module to obtain first concentration data.
And 102, acquiring and calculating the average value of the concentration parameter data of other students except the target student to obtain second concentration data.
In this step, first, concentration parameter data of students other than the target student is acquired.
And extracting the concentration parameter values of other students in the whole class, and calculating the average value of the concentration parameter values of the students to obtain first preprocessing data.
And extracting the concentration parameter values of other students in the whole class, and calculating the standard deviation of the concentration parameter values of the students to obtain second preprocessing data.
Calculating the average value of the concentration parameter data of other students as second preprocessing data;
according to the first preprocessing data and the second preprocessing data, third preprocessing data of each student are obtained through calculation; the third pre-processing data is used to characterize the degree of discretion of the student's concentration parameter data.
Determining and obtaining third preprocessing data of each student in other students according to a first formula, wherein the first formula specifically comprises:
wherein Z is i Third pre-processed data representing the ith student, X i Representing the value of the concentration parameter of the ith student,representing the first pre-processed data, S representing the second pre-processingAnd (5) data management.
Screening the third preprocessed data according to the first preset threshold value and the second preset threshold value, wherein the specific screening method comprises the following steps: and removing the data of the students with the third preprocessing data being larger than the first preset threshold value or smaller than the second preset threshold value, and then calculating the average value of the concentration parameters of the rest students after screening to obtain second concentration data.
The first preset threshold value and the second preset threshold value can be set manually.
Step 103, continuously calculating the first concentration data and the second concentration data in a continuous time interval to obtain a first concentration data array and a second concentration data array, calculating the correlation between the first concentration data array and the second concentration data array, and processing the obtained correlation result to obtain the attention evaluation result of the target student.
Continuously calculating first concentration data and second concentration data in a continuous time interval to obtain a first concentration data array and a second concentration data array, determining the correlation of the 2 array values of the target students by adopting a second formula, and obtaining a correlation result (first attention evaluation value) of the students.
Wherein X represents the first focused data array, Y represents the second focused data array, N represents the number of data in the array, and P represents the correlation result of the student.
Processing the correlation result to obtain attention evaluation result, wherein the calculation formula is as follows
In the above formula, A max A maximum threshold value representing the result of attention evaluation, A min Minimum threshold value representing attention evaluation result, P represents correlation result of the student, A tableThe attention evaluation result (second attention evaluation value) is shown. Wherein the threshold value may be determined manually; wherein A is max Can take the value of 100, A min The threshold value of the attention evaluation result is 0 to 100 when the value is 0. The attention preset first threshold may take the value 80 and the attention preset second threshold may take the value 50.
In an alternative embodiment of the present application, the student's attention level over this time frame is evaluated with an attention evaluation result. When the attention evaluation result is greater than or equal to the attention preset first threshold, the attention level of the student is a first level. The student's attention level is a second level when the attention evaluation result is greater than or equal to the attention preset second threshold value and less than the attention preset first threshold value. When the attention evaluation result is smaller than the attention preset second threshold value, the attention level of the student is a third grade.
In an optional embodiment of the present application, the present application further provides a teaching evaluation method based on the student attention evaluation method, which specifically includes:
step 201, performing continuous calculation on the time sequence to obtain an attention evaluation result array of the target students which is continuous in time.
Specifically, according to the method, a sliding window algorithm is utilized to perform continuous calculation on a time sequence, so as to obtain an attention evaluation result array of the student, which is continuous in time. The method specifically comprises the following steps:
(1) Firstly continuously acquiring brain electricity data for a period of time t, and calculating attention evaluation results of the student by using t data from time 1 to time t in the period of time t to obtain attention evaluation results A of the student at the time t 1 ；
(2) At time t+1, t data from time 2 to time t+1 are used to calculate the student's attention assessment result A at time t+1 2 ；
(3) At time t+2, t data from time 3 to time t+2 are used to calculate the student's attention assessment result A at time t+2 3 ；
(4) By analogy with one another, i.eThe continuous attention evaluation result A of the student at the time t and each subsequent time can be obtained from the time t i ；
(5)A 1 、A 2 、A 3 ……A i Namely the attention evaluation result array of the student.
Step 202, traversing all students to obtain an attention evaluation result array of each student.
And traversing all students in the whole class according to the calculation method of the attention evaluation result array of the students, and obtaining the attention evaluation result array of each student.
Step 203, calculating standard deviations of the attention evaluation result arrays of all students in each period in the time sequence to obtain a first score curve; and calculating the average value of the attention evaluation result arrays of all students in each period in the time sequence to obtain a second score curve.
And 204, determining a first teaching effect evaluation index according to the first score curve and the second score curve.
Specifically, a fourth formula is utilized according to the first score curve of the teaching effect and the second score curve of the teaching effect to obtain a first teaching effect evaluation index, and the formula is as follows:
wherein sigma i A first score curve, x, representing teaching effects i A second score curve representing teaching effect, T representing total duration of lessons, E 1 And the first teaching effect evaluation index is represented.
Step 205, processing the first teaching effect evaluation index to obtain a second teaching effect evaluation index, where the second teaching effect evaluation index is used for characterizing a classroom teaching effect.
And processing the first teaching effect evaluation index according to a fifth formula to obtain a second teaching effect evaluation index, wherein the fifth formula specifically comprises:
wherein E is 2 Representing a second teaching effect evaluation index, E max Is the maximum threshold value of the second teaching effect evaluation index, E min Is the minimum threshold value of the second teaching effect evaluation index, E 1 And the first teaching effect evaluation index is represented.
In an alternative embodiment of the application, the second teaching effect evaluation index is used for teaching effect in class. And when the second teaching effect evaluation index is greater than or equal to a preset first teaching effect evaluation index threshold, the classroom teaching effect is of a first grade. And when the second teaching effect evaluation index is larger than or equal to a preset second teaching effect evaluation index threshold and smaller than a preset first teaching effect evaluation index threshold, the classroom teaching effect is of a second grade. And when the second teaching effect evaluation index is smaller than a preset second teaching effect evaluation index threshold, the classroom teaching effect is of a third grade.
In summary, it can be seen that the electroencephalograph acquires the electroencephalogram data of all students in a class, and evaluates the attention level of the student in the course of lesson through the correlation calculation of the attention parameters of a certain student and other students in the electroencephalogram data, so that the interference factors of high attention indexes caused by the student doing other tasks can be effectively eliminated.
Through comprehensive assessment of learning attention levels of all students in a class, technical indexes for evaluating teaching effects of the class can be obtained.
In one embodiment, a student attention evaluation terminal is provided, and the electronic device may be a computer, and an internal structure diagram thereof may be as shown in fig. 3. The electronic device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the device is configured to provide computing and control capabilities. The memory of the device includes a non-volatile storage medium, an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of computer devices is used for student attention assessment data. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a student attention assessment method.
It will be appreciated by those skilled in the art that the structure shown in fig. 3 is merely a block diagram of some of the structures associated with the present application and does not constitute a limitation of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment of the present application, a computer-readable storage medium is provided, on which a computer program is stored, which when executed by a processor, implements the steps of the student attention evaluation method described above.
The computer readable storage medium provided in this embodiment has similar principles and technical effects to those of the above method embodiment, and will not be described herein.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in M forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SyMchlimk) DRAM (SLDRAM), memory bus (RaMbus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the claims. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (8)
1. A student attention assessment method, the method comprising:
acquiring electroencephalogram data of a plurality of students acquired by a plurality of electroencephalograms, processing the electroencephalogram data to obtain concentration parameter data of the plurality of students, and taking the concentration parameter data of a target student as first concentration data; wherein, each electroencephalograph collects electroencephalogram data of one student;
acquiring and calculating average values of concentration parameter data of other students except the target students to obtain second concentration data;
continuously calculating first concentration data and second concentration data in a continuous time interval to obtain a first concentration data array and a second concentration data array, calculating the correlation between the first concentration data array and the second concentration data array, and processing the obtained correlation result to obtain the attention evaluation result of the target student;
the method further comprises the steps of:
performing continuous calculation on the time sequence to obtain an attention evaluation result array of the target students in time continuity;
traversing all students to obtain an attention evaluation result array of each student;
calculating standard deviations of the attention evaluation result arrays of all students in each period in the time sequence to obtain a first score curve;
calculating the average value of the attention evaluation result arrays of all students in each period in the time sequence to obtain a second score curve;
determining a first teaching effect evaluation index according to the first score curve and the second score curve;
processing the first teaching effect evaluation index to obtain a second teaching effect evaluation index, wherein the second teaching effect evaluation index is used for representing classroom teaching effects;
determining a first teaching effect evaluation index according to the first score curve and the second score curve, and processing the first teaching effect evaluation index to obtain a second teaching effect evaluation index, wherein the method comprises the following steps:
determining a first teaching effect evaluation index according to a fourth formula, wherein the fourth formula specifically comprises:
wherein sigma i A first score curve, x, representing teaching effects i A second score curve representing teaching effect, T representing total duration of lessons, E 1 Representing a first teaching effect evaluation index;
and processing the first teaching effect evaluation index according to a fifth formula to obtain a second teaching effect evaluation index, wherein the fifth formula specifically comprises:
wherein E is 2 Representing a second teaching effect evaluation index, E max Is the maximum threshold value of the second teaching effect evaluation index, E min Is the minimum threshold value of the second teaching effect evaluation index, E 1 And the first teaching effect evaluation index is represented.
2. The method according to claim 1, wherein obtaining and calculating an average value of concentration parameter data of students other than the target student to obtain second concentration data, comprises:
acquiring concentration parameter data of other students except the target student;
calculating the average value of the concentration parameter data of other students as first preprocessing data;
calculating standard deviation of concentration parameter data of other students as second preprocessing data;
calculating third preprocessing data of each student in other students according to the first preprocessing data and the second preprocessing data; the third preprocessing data is used for representing the degree of dispersion of the student concentration parameter data;
screening out the third preprocessed data according to the first preset threshold value and the second preset threshold value;
and calculating the average value of the concentration parameter data of the students remaining after screening to obtain second concentration data.
3. The method of claim 2, wherein calculating third pre-processed data for each of the other students from the first pre-processed data and the second pre-processed data comprises:
determining and obtaining third preprocessing data of each student in other students according to a first formula, wherein the first formula specifically comprises the following steps:
wherein Z is i Third pre-processed data representing the ith student, X i Concentration parameter value representing ith student，Representing first pre-processed data and S representing second pre-processed data.
4. The method of claim 2, wherein screening the third pre-processed data according to the first pre-set threshold and the second pre-set threshold comprises:
and removing the data corresponding to the students with the third preprocessing data larger than the first preset threshold value or smaller than the second preset threshold value.
5. The method of claim 1, wherein calculating the correlation between the first and second attentive data arrays and processing the obtained correlation results to obtain attention assessment results of the target students comprises:
determining a correlation result according to a second formula, wherein the second formula specifically comprises:
wherein X represents the first focused data array, Y represents the second focused data array, N represents the number of data in the array, and P represents the correlation result of the student.
6. The method according to claim 5, wherein processing the obtained correlation result to obtain the attention evaluation result of the target student comprises:
determining the attention evaluation result of the target student according to a third formula, wherein the third formula specifically comprises:
in the above formula, A max A maximum threshold value representing the result of attention evaluation, A min The minimum threshold value of the attention evaluation result is represented by P, the correlation result of the student, and a, the attention evaluation result.
7. A student's attention assessment terminal, characterized by comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, implements the student's attention assessment method according to any one of claims 1 to 6.
8. A computer-readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, implements the student's attention assessment method as claimed in any one of claims 1 to 6.
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