CN109447050B - Online classroom user emotion visualization system - Google Patents
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Abstract
The invention relates to an online classroom user emotion visualization system, which comprises: the online classroom emotion data acquisition module is used for acquiring online classroom user facial expression video streams in real time and acquiring online classroom emotion data based on the video streams; the learning behavior log acquisition module is used for acquiring the learning behavior log of the online classroom in real time; and the emotion model visualization module is used for carrying out time axis matching processing on the online classroom emotion data and the learning behavior log, drawing and displaying an online classroom user emotion sequence chart. Compared with the prior art, the method has the advantages of strong intuition, timely realization of early warning purpose, improvement of learning efficiency and the like.
Description
Technical Field
The invention relates to the technical field of online education, in particular to an online classroom user emotion visualization system.
Background
In the school environment, students can learn the knowledge taught by teachers in class, and once the students encounter puzzles or problems in the learning process, the students can obtain technical answers and replies of the teachers and feel emotional concerns of the teachers, so that good teacher-student interaction and emotional support can play a key role in learning of the students. The online classroom environment effectively shares the efficiency of teaching and homework correction of the teacher on knowledge, however, the teaching and learning activities in the online classroom are separated from the students in time and space, and the emotional factors of the students are rarely considered in the learning process, which leads to the lack of emotional support of the students in the learning process. If students cannot obtain real-time emotional care of teachers when encountering difficult problems in the learning process, the learning effect of the students is negatively influenced, and the technical problem to be solved urgently in the field of online education is solved. The existing online education system also has the following disadvantages in this respect:
1. timeliness is not enough, an on-line classroom generally evaluates a classroom by students after class to know the experience of the students on the class, a teacher can only see the evaluation or leave a message of the students after class, the teacher cannot react immediately in the class, and the experience of the students in the class is improved, and the students are not intuitive when the experience is not in time;
2. the best moment for capturing the real emotion of the student is missed, Chinese students are often silent and impound, even if some students are lost, the students may not have good meaning or cannot clearly hear where to hear, most of the students not only do not ask questions in class, but also are puzzled after class, if children do not influence the class order, teachers only take lessons, and important information which is exposed by the micro-expression of the students can be easily ignored;
3. the emotion recognition system is used for analyzing emotion states of students in classes through big data, knowing how many students in a class are absorbed, and what the average absorption value of the classes is, so that the emotion recognition system is used for evaluating teaching quality of teachers.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide an online classroom user emotion visualization system.
The purpose of the invention can be realized by the following technical scheme:
an online classroom user emotion visualization system comprising:
the online classroom emotion data acquisition module is used for acquiring online classroom user facial expression video streams in real time and acquiring online classroom emotion data based on the video streams;
the learning behavior log acquisition module is used for acquiring the learning behavior log of the online classroom in real time;
and the emotion model visualization module is used for carrying out time axis matching processing on the online classroom emotion data and the learning behavior log, drawing and displaying an online classroom user emotion sequence chart.
Further, the online classroom emotion data acquisition module comprises:
the system comprises a video stream acquisition unit, a video processing unit and a video processing unit, wherein the video stream acquisition unit is used for acquiring facial expression video streams of online classroom users in real time and storing the video streams according to a time axis;
and the emotion recognition engine unit is used for carrying out emotion recognition on the video stream by utilizing an emotion recognition engine to acquire emotion intensity of each emotion type according to the emotion type.
Further, the learning behavior log includes a learning activity label and online classroom learning activity time information.
Further, the online classroom learning activity time comprises the time from the user watching an online video to the end, the time from the user reading a lecture to the end of reading, the time from the user checking a question to submitting an answer, the time from the user checking an answer and the beginning of the question analysis to the end, the time from the user checking a study report summary to closing a page, and the time from the user repeating a wrong question to the end of reviewing.
Further, the emotional categories include emotional states that are appropriate for learning and emotional states that are not appropriate for learning.
Further, the online classroom emotion data acquisition module further comprises:
and the normalization processing unit is used for performing normalization processing on the emotion intensity.
Further, the online classroom user emotion sequence chart comprises lesson basic attributes, learning activity labels and emotion time sequences.
Further, the system further comprises:
the emotion fluctuation early warning generation module is used for obtaining an emotion fluctuation early warning index according to the emotion type and the emotion intensity, and the calculation formula of the emotion fluctuation early warning index is as follows:
in the formula, EmoAlerttAn emotional fluctuation early warning index in the t-th period, eiThe number of emotional states that are unsuitable for learning is n.
Further, after obtaining the emotion fluctuation early warning index, the emotion fluctuation early warning generation module generates an emotion fluctuation early warning index sequence based on a time axis and adds the emotion fluctuation early warning index sequence into the online classroom user emotion sequence chart.
Compared with the prior art, the invention has the following beneficial effects:
first, the invention extracts the emotion data in the user online classroom and visualizes the emotion data, so that the emotion data can be visually displayed, and the learning efficiency is effectively improved.
Secondly, the teacher can immediately provide emotional support for the students from the visualized student emotion model by acquiring the data of the emotions of the students in real time through the emotion recognition engine, the emotions are dynamically changed, and students with negative emotions can reduce self learning confusion and negative emotions after being guided by the teacher or discussed by a partner, so that the learning effect of the students can be improved.
Thirdly, in the self-adaptive teaching, the online classroom adopting the pure self-adaptive system can realize the mastery degree of students through the evaluation condition by the system through student answering and system interaction, the students do not have the bidirectional communication of emotion between the students and the system, the emotions of the students such as anxiety feeling and autism occur sometimes, after the learner model of the self-adaptive engine is added with emotion perception, the existing learning system can understand the emotion of the students and make proper response, and the key factor that the bidirectional emotion communication restricts the self-adaptive learning effect can be effectively solved.
Fourthly, in an online classroom with a real teacher, the teacher can see various emotions triggered by students along with classroom activities and the intensity of each emotion from the emotion sequence diagram of the students in online classroom activities at a glance, the emotion fluctuation early warning index enables the teacher to clearly see whether the emotion of the students in online classroom learning is in a state suitable for learning or not in a visual mode, and according to the characteristic of the emotion fluctuation early warning index, when the teacher sees that the emotion fluctuation early warning index of the students is in a high level, timely intervention processing can be realized, and the early warning purpose is achieved.
Fifthly, the invention establishes an emotion fluctuation early warning index calculation formula, considers the number of emotional states which are not suitable for learning and the emotion intensity thereof, can accurately obtain the time point which needs to be subjected to intervention processing, and greatly improves the learning efficiency.
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FIG. 1 is a schematic diagram of the principles of the present invention;
fig. 2 is a schematic view of the visualization result of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
As shown in fig. 1, the invention provides an online classroom user emotion visualization system, which comprises an online classroom emotion data acquisition module, a learning behavior log acquisition module and an emotion model visualization module, wherein the online classroom emotion data acquisition module is used for acquiring online classroom user facial expression video streams in real time and acquiring online classroom emotion data based on the video streams; the learning behavior log acquisition module is used for acquiring a learning behavior log of an online classroom in real time; and the emotion model visualization module is used for carrying out time axis matching processing on the online classroom emotion data and the learning behavior log, drawing and displaying an online classroom user emotion sequence chart.
The online classroom emotion data acquisition module comprises a video stream acquisition unit and an emotion recognition engine unit, wherein the video stream acquisition unit is used for acquiring online classroom user facial expression video streams in real time and storing the video streams according to a time axis; the emotion recognition engine unit is used for performing emotion recognition on the video stream by using the emotion recognition engine to acquire emotion intensity of each emotion type. One sampling frequency has a plurality of emotions, and the average emotional intensity value of each emotion in a period of time is calculated.
The online classroom emotion data acquisition module may generate an emotion model for the student user using an emotion recognition engine. In the embodiment, the emotion is divided into three-dimensional emotion models with interestingness, concentration and pleasure degrees, and six emotions of interest, boredom, excitement, fatigue, pleasure and annoyance are respectively included.
The learning behavior log comprises a learning activity label and online classroom learning activity time information. The on-line classroom learning activity time comprises the duration of a series of learning activities, such as the time from the user watching an on-line video to the end, the time from the user reading a lecture to the end of reading, the time from the user examining a question to submitting the answer, the time from the user examining the answer and analyzing the question to the end, the time from the user examining a summary of a learning report to closing a page, the time from the user redoing a wrong question to the end of reviewing, and the like. The corresponding learning activity labels are: the classroom activity labels of a series of online classrooms such as watching videos, reading lectures, examining questions and answering questions, analyzing answers, checking reports, redoing wrong questions and the like.
The emotional categories include emotional states that are appropriate for learning and emotional states that are not appropriate for learning. Such as interest, excitement and pleasure are emotional states suitable for learning, and boredom, fatigue and distress are emotional states unsuitable for learning.
The online classroom emotion data acquisition module further comprises a normalization processing unit for performing normalization processing on the emotion intensity, wherein if the emotion intensity can be normalized to a number in a range of 0-100, the higher the value is, the greater the emotion intensity is.
In some embodiments, the system further includes an emotion fluctuation warning generation module, configured to obtain an emotion fluctuation warning indicator according to the emotion category and the emotion intensity. After obtaining the emotion fluctuation early warning index, the emotion fluctuation early warning generation module generates an emotion fluctuation early warning index sequence based on a time axis and adds the sequence into an online classroom user emotion sequence chart.
The emotion fluctuation early warning index is an index which displays that the emotion fluctuation state of a student has negative influence on learning, and the higher the emotion fluctuation early warning index is, the more emotion of the student needs to be educated by a teacher. The calculation formula of the emotion fluctuation early warning index is as follows:
in the formula, EmoAlerttAn emotional fluctuation early warning index in the t-th period, eiThe number of emotional states that are unsuitable for learning is n.
The emotion fluctuation early warning index value of the 1 st period of the online classroom, namely the intensity mean value of the emotion of the students which are not suitable for learning, effectively reflects the emotion state which is not suitable for learning when the students start to learn, and the teacher should adjust the emotion of the students.
The emotion sequence chart of the online classroom user comprises basic course attributes, learning activity labels and emotion time sequences, and emotion fluctuation early warning indexes can be added, so that the emotion and intensity of students in online classroom learning activities can be known through the emotion time sequences. The basic properties of the course comprise subject, course name, teacher and class time; the classroom learning activity labels comprise classroom activity labels of a series of online classrooms such as watching videos, reading lectures, examining questions and answering, analyzing answers, checking reports, redoing wrong questions and the like; the vertical axis of the emotion fluctuation early warning index map is an emotion fluctuation early warning index value, the horizontal axis is a time axis, the unit is minutes, and the graph shows the fluctuation of the emotion of students in a classroom by a line graph; the vertical axis of the emotion time sequence chart is the intensity of emotion, the scale interval is 20, the horizontal axis is the time axis, the unit is minutes, and the graph shows the emotion distribution of students in one unit time by using a histogram.
In this embodiment, an emotion fluctuation early warning indicator graph and an emotion time sequence graph are drawn on a time axis of a class according to a time sequence of a plurality of unit times, and one student in one unit time has emotion distribution in the emotion time sequence graph, such as happy 80% and surprised 20%, and has a corresponding emotion fluctuation early warning indicator value in the emotion fluctuation early warning indicator graph in the same unit time, and the emotion and emotion fluctuation early warning indicator values of the student change differently along with learning activities in the class until the class ends.
The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (7)
1. An online classroom user emotion visualization system, comprising:
the online classroom emotion data acquisition module is used for acquiring online classroom user facial expression video streams in real time and acquiring online classroom emotion data based on the video streams, wherein the online classroom emotion data comprises emotion types and emotion intensities of the emotion types, and the emotion types comprise emotion states suitable for learning and emotion states unsuitable for learning;
the learning behavior log acquisition module is used for acquiring the learning behavior log of the online classroom in real time;
the emotion model visualization module is used for carrying out time axis matching processing on the online classroom emotion data and the learning behavior log, drawing and displaying an online classroom user emotion sequence chart;
the emotion fluctuation early warning generation module is used for obtaining an emotion fluctuation early warning index according to the emotion type and the emotion intensity, and the calculation formula of the emotion fluctuation early warning index is as follows:
in the formula, EmoAlerttAn emotional fluctuation early warning index in the t-th period, eiThe number of emotional states that are unsuitable for learning is n.
2. The online classroom user emotion visualization system of claim 1, wherein the online classroom emotion data acquisition module comprises:
the system comprises a video stream acquisition unit, a video processing unit and a video processing unit, wherein the video stream acquisition unit is used for acquiring facial expression video streams of online classroom users in real time and storing the video streams according to a time axis;
and the emotion recognition engine unit is used for carrying out emotion recognition on the video stream by utilizing an emotion recognition engine to acquire emotion types and emotion intensities of the emotion types.
3. The online classroom user emotion visualization system of claim 1, wherein the learning behavior log includes a learning activity label and online classroom learning activity time information.
4. The online classroom user emotion visualization system of claim 3, wherein the online classroom learning activity time includes a user watch online video to end time, a user read lecture to end read time, a user review to submit an answer time, a user view answer and question parsing start to end time, a user view learning report summary to close a page time, and a user redo a wrong question to end review time.
5. The online classroom user emotion visualization system of claim 2, wherein the online classroom emotion data acquisition module further comprises:
and the normalization processing unit is used for performing normalization processing on the emotion intensity.
6. The online classroom user emotion visualization system of claim 1, wherein the online classroom user emotion sequence chart includes lesson base attributes, learning activity labels, and emotion time sequences.
7. The online classroom user emotion visualization system of claim 1, wherein the emotion fluctuation early warning generation module generates an emotion fluctuation early warning index sequence based on a time axis after obtaining an emotion fluctuation early warning index, and adds the sequence to the online classroom user emotion sequence chart.
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Address after: Room B381, 588 Tianlin East Road, Xuhui District, Shanghai, 2003 Patentee after: Shanghai squirrel classroom Artificial Intelligence Technology Co., Ltd Address before: Room B381, 588 Tianlin East Road, Xuhui District, Shanghai, 2003 Patentee before: SHANGHAI YIXUE EDUCATION TECHNOLOGY Co.,Ltd. |