CN114916759A - Intelligent stationery box - Google Patents
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Abstract
The invention relates to the technical field of education auxiliary devices, in particular to an intelligent writing case, which comprises a writing case body and a control system, wherein the control system comprises: the personalized knowledge base building module builds a personalized knowledge base of the student; the voice analysis module identifies the teaching content of the teacher; analyzing knowledge points related to the teaching content according to a disciplinary knowledge map to generate a knowledge point analysis result; the image analysis module analyzes whether the students have confused emotion according to the classroom images of the students, the knowledge point analysis results and the exercise data of the students and generates confused emotion analysis results; the education suggestion generation module generates education suggestions according to the perplexing emotion analysis result, the knowledge point analysis result and the student exercise practice data. This scheme of adoption can promote data acquisition device's portability, is favorable to gathering more comprehensive data to the promotion is to student's learning in-process, puzzles emotion analysis's accuracy, in order to provide more accurate education suggestion.
Description
Technical Field
The invention relates to the technical field of education auxiliary devices, in particular to an intelligent writing case.
Background
Personalized education is the current trend of educational development and is one of the goals realized by educational technology application. Personalized education refers to providing a customized learning guidance scheme according to the characteristics of students, but due to the limitation of educational resources, the teaching resources cannot meet the requirements of the students and parents on personalization in time and space. Therefore, in the prior art, a data acquisition device is usually arranged in a classroom to acquire emotions of students in the learning process, so that whether the students are confused about teaching contents of the classroom is analyzed, and personalized learning guidance is provided for the students. Although the technology can collect emotion of students and provide personalized guidance for the students, the following problems exist in the application of the technology in educational practice: data acquisition device is mostly fixed equipment, and its portability is relatively poor, can only gather student's mood in the classroom to lead to the comprehensiveness of data to obtain the guarantee, lead to the analysis result accuracy that finally reachs lower, the education suggestion accuracy that proposes for the student is also lower.
Disclosure of Invention
The invention provides an intelligent writing case which can improve the portability of a data acquisition device, is beneficial to acquiring more comprehensive data, improves the accuracy of confusing emotion analysis in the process of learning students and provides more accurate education suggestions.
In order to achieve the above purpose, the basic scheme of the invention is as follows:
the intelligent stationery box comprises a stationery box body and a control system, wherein the control system comprises a personalized knowledge base construction module, a weak knowledge point analysis module, a voice acquisition module, a voice analysis module, an image acquisition module, an image analysis module and an education suggestion generation module;
the personalized knowledge base building module is used for building a personalized knowledge base of the student; the personalized knowledge base comprises a subject knowledge map and student exercise data; the discipline knowledge graph comprises knowledge points related in a teaching material and the incidence relation of the knowledge points; the student exercise data comprises knowledge points corresponding to correct exercise questions and knowledge points corresponding to wrong exercise questions of students;
the weak knowledge point analysis module is used for analyzing weak knowledge points of students according to exercise data of the students and generating weak knowledge point analysis results;
the voice acquisition module is used for acquiring classroom voice data;
the voice analysis module is used for identifying teaching contents of teachers according to the classroom voice data; the knowledge points are used for analyzing the knowledge points related to the teaching content according to the discipline knowledge graph and generating a knowledge point analysis result;
the image acquisition module is used for acquiring classroom images of students;
the image analysis module comprises a knowledge point matching module, an emotion analysis module and a perplexing emotion judgment module;
the knowledge point matching module is used for matching the knowledge points related to the teaching content with the weak knowledge points of the students in the weak knowledge point analysis result and generating a matching result;
the emotion analysis module is used for analyzing the emotion of the student according to the classroom image of the student and generating an emotion analysis result;
the confusion emotion judging module is used for generating a confusion emotion analysis result according to the matching result and the emotion analysis result;
the image analysis module is used for analyzing whether the students have confusion emotions or not according to the knowledge point analysis result and the emotion analysis result and generating the confusion emotion analysis result;
the education suggestion generation module is used for generating education suggestions according to the perplexing emotion analysis result, the knowledge point analysis result and the student exercise practice data;
the voice acquisition module and the image acquisition module are both arranged on the writing case body.
The principle and the advantages of the invention are as follows: firstly, the collection of pronunciation and image has been realized through this intelligence stationery box, make the place of data acquisition no longer confine places such as fixed mounting data acquisition device's classroom, and the student study in-process, the probability that needs to use the stationery box is very high to can effectively promote the probability that the student can carry out data acquisition when studying, in addition, adopt the stationery box as the carrier of information acquisition equipment portable in, the psychological restraint of other information collection equipment for the student has virtually been reduced and the effect of the excitation that supervisory equipment exists to the student has been kept. More than, can promote data acquisition device's portability, be favorable to gathering more comprehensive data, remain the incentive effect that supervisory equipment exists to the student when reducing other information collection equipment and giving student psychological restraint and feel.
Acquiring knowledge points related in a teaching material and an incidence relation of the knowledge points by constructing a disciplinary knowledge map; acquiring knowledge points corresponding to correct practice problems and knowledge points corresponding to wrong practice problems of the students by constructing exercise data of the students; and analyzing knowledge points related to the teaching content according to the discipline knowledge graph. Therefore, whether the knowledge points related to the teaching contents relate to the knowledge points corresponding to the wrong practice problems of the students or the knowledge points related to the knowledge points corresponding to the wrong practice problems can be analyzed. Therefore, the emotion can be analyzed more accurately, and whether the student really confuses the emotion when listening to the current knowledge point of the teacher or not is judged. Above, can promote to student's learning in-process, the accuracy of perplexing mood analysis is favorable to proposing more accurate education suggestion.
To sum up, this scheme of adoption can promote data acquisition device's portability, is favorable to gathering more comprehensive data, promotes to student's learning in-process, puzzles emotion analysis's accuracy, proposes more accurate education suggestion, can also remain the incentive effect that supervisory equipment exists to the student when reducing the restraint sense of other information collection equipment on giving student psychology.
Further, the matching result is whether the knowledge points related to the teaching content are matched with weak knowledge points of the students in the weak knowledge point analysis result;
the confusion emotion judging module is also used for judging whether the knowledge points related to the teaching content are matched with the weak knowledge points of the students in the weak knowledge point analysis result or not according to the matching result; if yes, generating a confusion emotion analysis result of the confusion emotion of the student when the emotion analysis result shows that the student has surprised emotion; otherwise, generating a confused emotion analysis result that the student does not have confused emotion.
Has the advantages that: in addition, the knowledge points related to the teaching contents are matched with the weak knowledge points of the students in the analysis result of the weak knowledge points, so that whether the students are puzzled on the knowledge points related to the current teaching contents objectively can be obtained. And comprehensively judging by the confused emotion judging module according to the matching result and the emotion analysis result, and mastering the condition and the subjective expression of the student reflected by the emotion analysis result through an objective knowledge point reflected by the matching result to generate a more accurate confused emotion analysis result.
Further, the voice analysis module comprises a teaching content recognition module and a knowledge point analysis module;
the teaching content identification module analyzes the classroom voice data by adopting a voice identification technology and identifies teaching content of a teacher;
the knowledge point analysis module is used for analyzing the teaching content of the teacher by adopting a latent semantic analysis technology and generating a teaching content analysis result; and the knowledge point analysis module is also used for analyzing knowledge points related to the teaching content according to the teaching content analysis result and the disciplinary knowledge graph and generating a knowledge point analysis result.
Has the advantages that: the voice recognition technology is adopted to analyze classroom voice data, and the latent semantic analysis technology is adopted to analyze teaching contents of a teacher, so that the teaching contents of the teacher can be accurately recognized and analyzed, knowledge points related to the teaching contents can be analyzed conveniently, and subsequent knowledge point matching is facilitated.
Further, the confusion emotion analysis result comprises a confusion knowledge point and a confusion emotion judgment result;
the image analysis module also comprises a confusion emotion statistic module and a confusion grade analysis module;
the confusion emotion counting module is used for counting the times of the students for the confusion emotion appearing in the confusion knowledge points and generating a counting result;
and the confusion level analysis module is used for generating a confusion level according to the statistical result and the weak knowledge point analysis result.
Has the advantages that: during analysis, the confusion level of the students to each confusion knowledge point can be analyzed according to the times of the students presenting the confusion emotion to the confusion knowledge point and whether the confusion knowledge point is a weak knowledge point of the students, and personalized learning suggestions can be provided for the confusion level of the students to different knowledge points.
Further, the education suggestion generation module is used for generating education suggestions according to the confusion level.
Has the advantages that: and generating an education suggestion according to the confusion level, so that the education suggestion is more suitable for the real learning condition of each student.
Furthermore, the student exercise data further comprises wrong exercise questions of the student, and the education suggestions comprise the wrong exercise questions of the student and corresponding knowledge points of the wrong exercise questions.
Has the beneficial effects that: the problem of the wrong exercise and the corresponding knowledge point of the wrong exercise are brought into the education suggestion, and the students are helped to practice and consolidate the weak items of the students.
Further, the discipline knowledge graph also comprises the basics of all knowledge points involved in the teaching materials; the education suggestion generation module is used for generating education suggestions according to the basic properties of the knowledge points related in the teaching materials.
Has the beneficial effects that: the educational advice is generated according to the basic property of each knowledge point involved in the teaching material, so that the students can be promoted from basic learning step by step.
Drawings
Fig. 1 is a logic block diagram of an intelligent writing case according to an embodiment of the invention.
Detailed Description
The following is further detailed by way of specific embodiments:
example 1:
example 1 is substantially as shown in figure 1:
intelligent stationery box, including stationery box body and control system. The control system comprises an individualized knowledge base construction module, a weak knowledge point analysis module, a voice acquisition module, a voice analysis module, an image acquisition module, an image analysis module and an education suggestion generation module. Pronunciation collection module and image collection module all set up on the stationery box body, in this embodiment, pronunciation collection module adopts radio equipment, image collection module adopts the camera, camera and radio equipment all set up in the side of stationery box body, are convenient for gather student's facial expression. In this embodiment, each analysis module function of the control system can upload the collected data to the cloud after the voice collection module and the image collection module complete data collection, and then perform data analysis and processing.
The personalized knowledge base building module is used for building a personalized knowledge base of the student; the personalized knowledge base comprises a subject knowledge map and student exercise practice data. The discipline knowledge graph comprises knowledge points related in a teaching material, incidence relations of the knowledge points and the basics of the knowledge points related in the teaching material; the student exercise data comprises correct exercise questions, knowledge points corresponding to the correct exercise questions, wrong exercise questions and knowledge points corresponding to the wrong exercise questions of the student.
And the weak knowledge point analysis module is used for analyzing weak knowledge points of students according to the exercise data of the students and generating a weak knowledge point analysis result. In this embodiment, the weak knowledge point analysis module analyzes weak knowledge points of the student in an artificial intelligence manner according to correct practice problems, knowledge points corresponding to correct practice problems, wrong practice problems, knowledge points corresponding to wrong practice problems, knowledge points related to a teaching material, and an association relationship between knowledge points of the student.
The weak knowledge point analysis module comprises a BP neural network module, the BP neural network module comprises a BP neural network model, the BP neural network module analyzes weak knowledge points of students by using a BP neural network technology, and specifically, a three-point analysis module is firstly constructedIn the embodiment, the incidence relation among correct exercise question, correct exercise question corresponding knowledge point, wrong exercise question corresponding knowledge point, knowledge point related to the wrong exercise question, knowledge point related to teaching material and each knowledge point of the students is used as the input of the input layer, so that the input layer has 6 nodes, and the output is the weak knowledge point of the students, so that 1 node is shared; for hidden layers, the present embodiment uses the following formula to determine the number of hidden layer nodes:
where l is the number of nodes of the hidden layer, n is the number of nodes of the input layer, m is the number of nodes of the output layer, and a is a number between 1 and 10, which is taken as 6 in this embodiment, so that the hidden layer has 9 nodes in total. BP neural networks typically employ Sigmoid differentiable functions and linear functions as the excitation function of the network. This example selects the S-type tangent function tansig as the excitation function for the hidden layer neurons. The prediction model selects an S-shaped logarithmic function tansig as an excitation function of neurons of an output layer. After the BP network model is constructed, the model is trained by using historical data as a sample, and a more accurate analysis result can be obtained through an analysis model obtained after training is completed.
The voice acquisition module is used for acquiring classroom voice data.
The voice analysis module is used for identifying teaching contents of teachers according to classroom voice data; the knowledge points are used for analyzing the knowledge points related to the teaching content according to the discipline knowledge graph and generating a knowledge point analysis result; the voice analysis module comprises a teaching content recognition module and a knowledge point analysis module.
The teaching content identification module analyzes the classroom voice data by adopting a voice identification technology and identifies teaching contents of teachers; the knowledge point analysis module analyzes the teaching content of the teacher by adopting a latent semantic analysis technology and generates a teaching content analysis result, so that more accurate and comprehensive teaching related content can be obtained; and the teaching system is also used for analyzing knowledge points related to teaching contents according to the teaching content analysis results and the subject knowledge graph, generating knowledge point analysis results, and particularly comparing the analyzed teaching related contents in the teaching content analysis results with the knowledge points related to teaching materials in the subject knowledge graph to obtain the knowledge points related to the teaching contents.
The image acquisition module is used for acquiring classroom images of students.
The image analysis module comprises a knowledge point matching module, a sentiment analysis module, a confusion sentiment judgment module, a confusion sentiment statistics module and a confusion grade analysis module.
The knowledge point matching module is used for matching the knowledge points related to the teaching content with the weak knowledge points of the students in the weak knowledge point analysis result and generating a matching result; the emotion analysis module is used for analyzing emotions of students according to the classroom images of the students and generating emotion analysis results. And the matching result is whether the knowledge points related to the teaching content are matched with the weak knowledge points of the students in the analysis result of the weak knowledge points.
And the confusion emotion judging module is used for generating a confusion emotion analysis result according to the matching result and the emotion analysis result. The confusion emotion analysis result comprises a confusion knowledge point and a confusion emotion judgment result. Specifically, the perplexing emotion judging module is used for judging whether the knowledge points related to the teaching content are matched with the weak knowledge points of the students in the weak knowledge point analysis result according to the matching result; if yes, generating a confusion emotion analysis result of the confusion emotion of the student when the emotion analysis result shows that the student has a surprise emotion; otherwise, generating a confused emotion analysis result that the student does not have confused emotion. In this embodiment, the surprised emotion recognition adopts the existing mature technical scheme, and the key recognition feature is equalization of canthus and angle of mouth. The surprise expression is determined mainly by the pupil distance amplification and the time change speed of the neutral expression of the pupil distance amplification distance. A surprise emotion is considered to occur if interpupillary distance enlargement occurs rapidly and for a longer duration (two to five seconds, four seconds in the present embodiment) based on neutral expression.
And the confusion emotion counting module is used for counting the times of the students for the confusion emotions of the confusion knowledge points and generating a counting result.
And the confusion level analysis module is used for generating a confusion level according to the statistical result and the weak knowledge point analysis result. In the embodiment, the confusion level is three levels, and the first confusion emotion of a student on any confusion knowledge point is one level; the students find out the puzzlement emotion for any puzzlement knowledge point twice or find out the puzzlement emotion for any puzzlement knowledge point once, and the puzzlement knowledge points are regarded as the second grade when the puzzlement knowledge points are weak knowledge points; the student shows the confusion mood for any confusion knowledge point more than three times, or shows the confusion mood for any confusion knowledge point more than two times, and when the confusion knowledge point is a weak knowledge point, the student is identified as three levels.
And the education suggestion generation module is used for generating education suggestions according to the perplexing emotion analysis result, the knowledge point analysis result, the student exercise data, the perplexing level and the basic properties of all knowledge points related in the teaching material. The education suggestions comprise wrong practice problems of the students and corresponding knowledge points of the wrong practice problems. Specifically, what the knowledge points currently being taught are is confirmed through the knowledge point analysis result, and then when the confusion emotion analysis result shows that the students have confusion emotion to the confusion knowledge points, wrong practice problems and knowledge points corresponding to the wrong practice problems of the students related to the confusion knowledge points are displayed. The display sequence is confirmed through the confusion levels and the foundation of each knowledge point related in the teaching material, the display contents are firstly sequenced from high to low according to the confusion levels corresponding to the confusion knowledge points related to the display contents, then if the display contents corresponding to a plurality of confusion knowledge points exist in each level, the display contents are sequenced according to the foundation of each knowledge point related in the teaching material, the foundation is stronger, namely the more basic display contents are arranged in the front, and the generated education suggestion is sent to a student end, a teacher end and a keeper end so as to provide a reference basis for learning.
Example 2:
example 2 is substantially as shown in figure 1:
embodiment 2 is the same in basic principle as embodiment 1, and is different in that embodiment 2 further includes a trajectory recognition module, a user identification module, and a user confirmation module.
The track recognition module is used for recognizing the pen holder moving track of the student according to the student classroom image and generating a track recognition result;
the using user identification module is used for storing a using habit library, and the using habit library is used for storing identity information of a plurality of users and pen holder using track habits of the users; the user identification module is used for comparing the track identification result with the use habit library to generate a user identification result, and when the pen holder use track habit of the user in the use habit library is matched with the detected track identification result, the user identification result is generated to identify who the user who uses the pen holder is; and when the penholder use track habit of the user is not matched with the detected track recognition result in the use habit library, newly establishing user identity information and storing the penholder use track habit of the new user. And the identity information of the user is acquired by adopting a face recognition technology.
The user confirmation module is used for collecting the face of a user and generating a face recognition result; and the user confirmation result is generated according to the user identification result, the use habit library and the face identification result. Specifically, according to the user identification result, the identity information of the user using the pen holder is compared with the face identification result, whether the user writes normally is analyzed, and therefore whether the user imitates the handwriting of other people can be judged. That is, when the identity information of the user using the penholder is not matched with the face recognition result, the user confirmation result of the user contradiction is generated, an alarm is given, and the phenomenon of rewriting is prevented.
The foregoing are embodiments of the present invention and are not intended to limit the scope of the invention to the particular forms or details of the structures, methods and materials described herein, which are presently known or later come to be known to those of ordinary skill in the art, such that the present invention may be practiced without departing from the spirit and scope of the appended claims. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (7)
1. Intelligent writing case, including writing case body and control system, its characterized in that: the control system comprises an individualized knowledge base construction module, a weak knowledge point analysis module, a voice acquisition module, a voice analysis module, an image acquisition module, an image analysis module and an education suggestion generation module;
the personalized knowledge base building module is used for building a personalized knowledge base of the student; the personalized knowledge base comprises a subject knowledge map and student exercise practice data; the discipline knowledge graph comprises knowledge points related in a teaching material and the incidence relation of the knowledge points; the student exercise data comprises knowledge points corresponding to correct exercise questions and knowledge points corresponding to wrong exercise questions of students;
the weak knowledge point analysis module is used for analyzing weak knowledge points of students according to student exercise data and generating weak knowledge point analysis results;
the voice acquisition module is used for acquiring classroom voice data;
the voice analysis module is used for identifying teaching contents of teachers according to the classroom voice data; the knowledge points are used for analyzing the knowledge points related to the teaching content according to the discipline knowledge graph and generating a knowledge point analysis result;
the image acquisition module is used for acquiring classroom images of students;
the image analysis module comprises a knowledge point matching module, an emotion analysis module and a perplexing emotion judgment module;
the knowledge point matching module is used for matching the knowledge points related to the teaching content with the weak knowledge points of the students in the weak knowledge point analysis result and generating a matching result;
the emotion analysis module is used for analyzing the emotion of the student according to the classroom image of the student and generating an emotion analysis result;
the confusion emotion judging module is used for generating a confusion emotion analysis result according to the matching result and the emotion analysis result;
the image analysis module is used for analyzing whether the students have confusion emotions or not according to the knowledge point analysis result and the emotion analysis result and generating a confusion emotion analysis result;
the education suggestion generation module is used for generating education suggestions according to the perplexing emotion analysis result, the knowledge point analysis result and the student exercise data;
the voice acquisition module and the image acquisition module are both arranged on the writing case body.
2. The intelligent writing case of claim 1, wherein: the matching result is whether the knowledge points related to the teaching content are matched with the weak knowledge points of the students in the weak knowledge point analysis result;
the perplexing emotion judging module is also used for judging whether the knowledge points related to the teaching content are matched with the weak knowledge points of the students in the weak knowledge point analysis result or not according to the matching result; if yes, generating a confusion emotion analysis result of the confusion emotion of the student when the emotion analysis result shows that the student has a surprise emotion; otherwise, generating a confused emotion analysis result that the student does not have confused emotion.
3. The intelligent writing case of claim 1, wherein: the voice analysis module comprises a teaching content recognition module and a knowledge point analysis module;
the teaching content identification module analyzes the classroom voice data by adopting a voice identification technology and identifies teaching contents of teachers;
the knowledge point analysis module analyzes the teaching content of the teacher by adopting a latent semantic analysis technology and generates a teaching content analysis result; and the knowledge point analysis module is also used for analyzing knowledge points related to the teaching content according to the teaching content analysis result and the disciplinary knowledge graph and generating a knowledge point analysis result.
4. The intelligent writing case of claim 1, wherein: the confusion emotion analysis result comprises a confusion knowledge point and a confusion emotion judgment result;
the image analysis module also comprises a confusion emotion statistic module and a confusion grade analysis module;
the confusion emotion counting module is used for counting the times of the students for the confusion emotion appearing in the confusion knowledge points and generating a counting result;
and the confusion level analysis module is used for generating a confusion level according to the statistical result and the weak knowledge point analysis result.
5. The intelligent writing case of claim 4, wherein: and the education suggestion generating module is used for generating education suggestions according to the confusion level.
6. The intelligent writing case of claim 1, wherein: the student exercise data further comprises wrong exercise questions of the students, and the education suggestions comprise the wrong exercise questions of the students and corresponding knowledge points of the wrong exercise questions.
7. The intelligent writing case of claim 1, wherein: the discipline knowledge graph also comprises the basics of all knowledge points involved in the teaching materials; and the education suggestion generation module is used for generating education suggestions according to the basics of the knowledge points involved in the teaching materials.
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| CN111917850A (en) * | 2020-07-20 | 2020-11-10 | 湖北美和易思教育科技有限公司 | Intelligence thing networking campus knapsack |
| CN112464020A (en) * | 2020-11-24 | 2021-03-09 | 随锐科技集团股份有限公司 | Network classroom information processing method and system and computer readable storage medium |
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