Classroom teaching effect detection system based on human body postures

Abstract

The invention provides a classroom teaching effect detection system based on human body postures. The classroom teaching effect detection system comprises a teaching panel, an eye tracker, a camera, a desk pressure sensor group, a seat pressure sensor group and a time module, the eye tracker, the camera, the desk pressure sensor group and the seat pressure sensor group form a student class posture information acquisition module, eyeball movement track data of the student in the class process is acquired through the eye tracker, and face orientation and activity information of the student in the class process is acquired through the camera; the desk pressure sensor group and the seat pressure sensor group are used for collecting physical activity information of students in the class. According to the invention, the time module is used for setting the teaching duration, starting time and ending time of a single classroom to be combined with the eye tracker and the camera, thereby completing the detection of the qualification or disqualification of the classroom teaching effect, determining the optimal teaching part of the teaching content, facilitating the completion of the classroom teaching detection, and being real-time and convenient.

Description

Technical Field

[0001] The invention belongs to the technical field of classroom teaching effect detection, and specifically relates to a classroom teaching effect detection system based on human body posture. Background Art

[0002] With the rapid development of modern information technology, the use of advanced information technology in school classrooms has become a new development trend. Classroom teaching is a process of learning, communication and interaction between teachers and students. The teaching progress can be adjusted through students' feedback information, thereby improving the teaching quality. In the classroom, students' different sitting postures are an important part of feedback information, which can reflect the quality of classroom teaching to a certain extent.

[0003] The existing evaluation system for students' sitting posture usually obtains the results based on human posture detection and recognition technology and network training, and combines student scoring, teacher self-evaluation and student sitting posture scores.

[0004] However, it is rather cumbersome to use and cannot provide intuitive feedback on students' recognition of teaching content during class, thus affecting the detection and evaluation of the teaching process.

[0005] Based on this, a classroom teaching effect detection system based on human posture is proposed. Summary of the invention

[0006] The technical problem to be solved by the present invention is to provide a classroom teaching effect detection system based on human posture in view of the deficiencies of the above-mentioned prior art, so as to solve the problems raised in the above-mentioned background technology.

[0007] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0008] In the first aspect, a classroom teaching effect detection system based on human posture includes a teaching panel, an eye tracker, a camera, a desk pressure sensor group, a seat pressure sensor group and a time module;

[0009] The teaching panel is used by teachers to teach in class, and the teaching content is displayed in an informationized manner through the teaching panel;

[0010] The eye tracker, camera, desk pressure sensor group and seat pressure sensor group form a student posture information collection module during class, the eye tracker collects the student's eye movement trajectory data during class, the camera collects the student's facial orientation and activity information during class, and the desk pressure sensor group and seat pressure sensor group are used to collect the student's body activity information during class;

[0011] The posture information acquisition module signal is connected to a time module, and the time module marks the student posture information collected by the posture information acquisition module with time as the coordinate axis. The posture information acquisition module is also connected to a statistical module, and the statistical module performs statistics on the collected student posture information. After the statistics are completed, the statistical information is sent to the information processing module, and the information processing module integrates, analyzes and summarizes the statistical information to complete the detection and evaluation of classroom teaching effectiveness.

[0012] As a further explanation of the present invention, the teaching panel is an electronic display screen, which displays classroom teaching content on the electronic display screen, which is conducive to detecting and evaluating the teaching effects in different time periods.

[0013] As a further illustration of the present invention, the number of the eye trackers, cameras, desk pressure sensor groups and seat pressure sensor groups is the same as the number of students in the classroom, so that the posture information of students in each classroom can be collected, which is conducive to a comprehensive statistical analysis of the classroom teaching effect.

[0014] As a further explanation of the present invention, the eye tracker is worn on the head of each student. The eye tracker can collect the movement trajectory of the students' eyeballs during class, so that the students' stay time on the teaching panel, the stay time on the desk, and the rest of the free time can be collected separately, which is conducive to comprehensive statistics of the time points and time periods of the students' eye activities during class.

[0015] As a further explanation of the present invention, the camera is installed in front of the student's desk, and the working end of the camera is facing the student's face, so that the camera can completely collect the student's facial information during class.

[0016] As a further explanation of the present invention, the desk pressure sensor group is set on the student's desk, and the contact time and contact area between the student's upper limbs and the desk during class are determined by the pressure area on the desk pressure sensor group, and used in conjunction with a camera.

[0017] As a further explanation of the present invention, when the seat pressure sensor group is set on the student's seat, during the class time, when the seat pressure sensor group collects the pressure information of the student when sitting or standing, the eye tracker, camera and desk pressure sensor group are controlled to turn on, otherwise the eye tracker, camera and desk pressure sensor group are turned off.

[0018] As a further explanation of the present invention, the statistical module performs initial statistics on the information collected by the eye tracker, camera and desk pressure sensor group during students' class with time as the coordinate axis, and after the initial statistics, performs secondary statistics on the time period when the information collected by the eye tracker, camera and desk pressure sensor group during class is stable, and performs tertiary statistics on the initial statistical information and secondary statistical information of each student.

[0019] As a further explanation of the present invention, the information processing module integrates the information collected by the statistical module respectively, and after the integration, integrates the time points and time periods corresponding to the eye tracker and camera of each student with the teaching panel, analyzes and summarizes the classroom teaching effects at different time points and time periods during the class, and completes the detection and evaluation of the classroom teaching effects.

[0020] In a second aspect, a method for using a human body posture classroom teaching effect detection system comprises the following steps:

[0021] S1. First, use the teaching panel to display the classroom teaching content, and use the seat pressure sensor group to determine the working status of the eye tracker, camera and desk pressure sensor group, and collect the student's posture information when the eye tracker, camera and desk pressure sensor group are in the working state;

[0022] S2. After a single class teaching session is over, the student posture information collected by the eye tracker, camera and desk pressure sensor group is sent to the statistical module, and the collected student posture information is counted by the statistical module;

[0023] S3, sending the information collected by the statistical module to the information processing module to use the information processing module to detect and evaluate the classroom teaching effect, as follows:

[0024] Through the time module, the duration of a single class is set as T, the start time is ts, and the end time is te; the time the eye tracker stays on the teaching panel is Tef, the time it stays on the desk is Tet, and the rest of the free state time is Tel;

[0025] The time captured by the camera during the class when the student's face stays on the teaching panel is Tff, the time when it stays on the desk is Tft, and the rest of the time in the free state is Tfl;

[0026] First, calculate and analyze the average value P1 of the ratio of Tef and Tff to T to determine the attractiveness of teaching panel 1. If P1 is greater than or equal to 20, the teacher's teaching is qualified, otherwise it is unqualified;

[0027] Then calculate and analyze the average value P2 of the ratio of Tet and Tft to T. If P2 is greater than or equal to 30, the teacher's teaching is qualified, otherwise it is unqualified;

[0028] Then calculate and analyze the ratio of the sum of Tef and Tet to T (P3), the ratio of the sum of Tff and Tft to T (P4), and calculate the average value of P3 and P4 (P5). If P5 is greater than or equal to 70, the student has passed the class, otherwise, he has failed.

[0029] Then, the starting time of Tef and Tff at different stages is tes and the ending time is tee. By determining the time point at which tes and tee overlap with ts and te, the time point is fed back to the teaching content on the teaching panel to determine the optimal teaching part of the teaching content.

[0030] Compared with the prior art, the present invention has the following advantages:

[0031] The present invention displays classroom teaching content through a teaching panel, and uses a seat pressure sensor group to determine the working state of an eye tracker, a camera and a desk pressure sensor group. When the eye tracker, the camera and the desk pressure sensor group are in the working state, the student posture information in class is collected. After a single class teaching is finished, the student posture information in class collected by the eye tracker, the camera and the desk pressure sensor group is sent to a statistical module, and the collected student posture information in class is statistically analyzed by the statistical module; the information statistically analyzed by the statistical module is sent to an information processing module, and the information processing module is used to detect and evaluate the classroom teaching effect; the single class teaching time is set to T, the start time is ts, and the end time is te through the time module; the stay time of the eye tracker on the teaching panel is Tef, the stay time on the desk is Tet, and the rest of the free state time is Tel; the stay time of the student's face on the teaching panel during the class collected by the camera is T ff, the stay time on the desk is Tft, and the rest of the free state time is Tfl; first calculate and analyze the average value P1 of the ratio of Tef and Tff to T to determine the attractiveness of the teaching panel, P1 is greater than or equal to 20, the teacher's teaching is qualified, otherwise it is unqualified; then calculate and analyze the average value P2 of the ratio of Tet and Tft to T, P2 is greater than or equal to 30, the teacher's teaching is qualified, otherwise it is unqualified; then calculate and analyze the ratio P3 of the sum of Tef and Tet to T, the ratio P4 of the sum of Tff and Tft to T, calculate the average value P5 of P3 and P4, P5 is greater than or equal to 70, the student's class is qualified, otherwise it is unqualified; then use the starting time of Tef and Tff at different stages as tes and the ending time tee, by determining the time point where tes and tee overlap with ts and te, and feedback to the teaching content on the teaching panel, determine the optimal teaching part of the teaching content, facilitate the completion of classroom teaching detection, real-time and convenient. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is the overall principle framework diagram of the present invention.

[0033] Description of reference numerals:

[0034] 1-teaching panel; 2-eye tracker; 3-camera; 4-desk pressure sensor group; 5-seat pressure sensor group; 6-time module; 7-statistics module; 8-information processing module. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] like Figure 1 As shown, the present invention provides a technical solution: a classroom teaching effect detection system based on human posture, comprising a teaching panel 1, an eye tracker 2, a camera 3, a desk pressure sensor group 4, a seat pressure sensor group 5 and a time module 6;

[0037] The teaching panel 1 is used by teachers to teach in class, and the teaching content is displayed in an informationized manner through the teaching panel 1;

[0038] Specifically, the teaching panel 1 is an electronic display screen, which displays classroom teaching content, which is conducive to testing and evaluating the teaching effects in different time periods.

[0039] The eye tracker 2, camera 3, desk pressure sensor group 4 and seat pressure sensor group 5 form a student posture information collection module during class, the eye tracker 2 collects the eye movement trajectory data of the student during class, the camera 3 collects the facial orientation and activity information of the student during class, and the desk pressure sensor group 4 and seat pressure sensor group 5 are used to collect the body activity information of the student during class;

[0040] The number of the eye trackers 2, cameras 3, desk pressure sensor groups 4 and seat pressure sensor groups 5 is the same as the number of students in the classroom, so that the posture information of students in each classroom can be collected, which is conducive to a comprehensive statistical analysis of the classroom teaching effect.

[0041] The eye tracker 2 is worn on the head of each student. The eye tracker can collect the movement trajectory of the student's eyeballs during class, so that the student's stay time on the teaching panel 1, the stay time on the desk, and the rest of the free time can be collected separately, which is conducive to comprehensive statistics of the time points and time periods of the student's eyeball activities during class.

[0042] The camera 3 is installed in front of the student's desk, and the working end of the camera 3 faces the student's face, so that the camera 3 can completely collect the student's facial information during class.

[0043] The desk pressure sensor group 4 is set on the student's desk. The contact time and contact area between the student's upper limbs and the desk during class are determined by the pressure area on the desk pressure sensor group 4, and are used in conjunction with the camera 3.

[0044] When the seat pressure sensor group 5 is set on the student's seat, during the class time, when the seat pressure sensor group 5 collects the pressure information of the student when sitting, the eye tracker 2, the camera 3 and the desk pressure sensor group 4 are controlled to turn on, otherwise the eye tracker 2, the camera 3 and the desk pressure sensor group 4 are turned off.

[0045] The posture information acquisition module signal is connected to the time module 6, and the time module 6 marks the student posture information collected by the posture information acquisition module with time as the coordinate axis. The posture information acquisition module is also connected to the statistics module 7, and the statistics module 7 performs statistics on the collected student posture information;

[0046] Specifically, the statistical module 7 performs initial statistics on the information collected by the eye tracker 2, camera 3 and desk pressure sensor group 4 during class with time as the coordinate axis, and after the initial statistics, performs secondary statistics on the time period when the information collected by the eye tracker 2, camera 3 and desk pressure sensor group 4 during class is stable, and performs tertiary statistics on the initial statistical information and secondary statistical information of each student. After the statistics, feedback on the teaching content in the teaching panel 1 is determined, which is beneficial for teachers to improve and adjust the teaching content outside the optimal teaching part, and facilitates the interaction with students' classroom teaching.

[0047] After the statistics are completed, the statistical information is sent to the information processing module 8, and the information processing module 8 integrates the information collected by the statistical module 7 respectively. After the integration, the eye tracker 2 and camera 3 of each student are integrated with the time points and time periods corresponding to the teaching panel 1, and the classroom teaching effects at different time points and time periods during the class are analyzed and summarized to complete the detection and evaluation of the classroom teaching effects.

[0048] The method for using the above-mentioned human body posture classroom teaching effect detection system comprises the following steps:

[0049] S1, first use the teaching panel 1 to display the classroom teaching content, and at the same time use the seat pressure sensor group 5 to determine the working status of the eye tracker 2, the camera 3 and the desk pressure sensor group 4, and collect the student's posture information when the eye tracker 2, the camera 3 and the desk pressure sensor group 4 are in the working state;

[0050] S2. After a single class teaching session is finished, the student posture information collected by the eye tracker 2, the camera 3 and the desk pressure sensor group 4 is sent to the statistical module 7, and the collected student posture information is counted by the statistical module 7;

[0051] S3, sending the information collected by the statistical module 7 to the information processing module 8, and using the information processing module 8 to detect and evaluate the classroom teaching effect, as follows:

[0052] The duration of a single class teaching is set as T through the time module 6, the start time is ts, and the end time is te; the stay time of the eye tracker 2 on the teaching panel 1 is Tef, the stay time on the desk is Tet, and the rest of the free state time is Tel;

[0053] The time captured by camera 3 during the class when the student's face stays on the teaching panel 1 is Tff, the time when it stays on the desk is Tft, and the rest of the time in the free state is Tfl;

[0054] First, calculate and analyze the average value P1 of the ratio of Tef and Tff to T to determine the attractiveness of teaching panel 1. If P1 is greater than or equal to 20, the teacher's teaching is qualified, otherwise it is unqualified;

[0055] Then calculate and analyze the average value P2 of the ratio of Tet and Tft to T. If P2 is greater than or equal to 30, the teacher's teaching is qualified, otherwise it is unqualified;

[0056] Then calculate and analyze the ratio of the sum of Tef and Tet to T (P3), the ratio of the sum of Tff and Tft to T (P4), and calculate the average value of P3 and P4 (P5). If P5 is greater than or equal to 70, the student has passed the class, otherwise, he has failed.

[0057] Then, the starting time of Tef and Tff in different stages is used as tes and the ending time is tee. By determining the overlapping time points between tes and tee and ts and te, feedback is given to the teaching content on the teaching panel 1 to determine the optimal teaching part of the teaching content.

[0058] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0059] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A classroom teaching effect detection system based on human posture, characterized by: It includes a teaching panel (1), an eye tracker (2), a camera (3), a desk pressure sensor group (4), a seat pressure sensor group (5) and a time module (6); The teaching panel (1) is used by teachers to teach in class, and the teaching content of the class is displayed in an informationized manner through the teaching panel (1); The eye tracker (2), the camera (3), the desk pressure sensor group (4) and the seat pressure sensor group (5) form a module for collecting student posture information during class. The eye tracker (2) is used to collect eye movement trajectory data of students during class, the camera (3) is used to collect facial orientation and activity information of students during class, and the desk pressure sensor group (4) and the seat pressure sensor group (5) are used to collect body activity information of students during class. The posture information acquisition module signal is connected to a time module (6), and the time module (6) marks the student posture information collected by the posture information acquisition module with time as the coordinate axis. The posture information acquisition module is also connected to a statistical module (7), and the statistical module (7) performs statistics on the collected student posture information. After the statistics are completed, the statistical information is sent to an information processing module (8), and the information processing module (8) integrates, analyzes and summarizes the statistical information to complete the detection and evaluation of classroom teaching effects.

2. According to claim 1, a classroom teaching effect detection system based on human posture is characterized in that: The teaching panel (1) is an electronic display screen, which displays classroom teaching content, facilitating the detection and evaluation of teaching effects in different time periods.

3. According to the human body posture classroom teaching effect detection system of claim 1, it is characterized in that: The number of the eye trackers (2), cameras (3), desk pressure sensor groups (4) and seat pressure sensor groups (5) is the same as the number of students in the classroom, so that posture information of students in each classroom can be collected, which is conducive to comprehensive statistical analysis of classroom teaching effects.

4. According to the human body posture classroom teaching effect detection system of claim 1, it is characterized in that: The eye tracker (2) is worn on the head of each student. The eye tracker can collect the movement trajectory of the student's eyeballs during class, so that the time the student stays on the teaching panel (1), the time the student stays on the desk, and the rest of the time in the free state can be collected separately, which is conducive to comprehensive statistics of the time points and time periods of the student's eyeball activities during class.

5. The human body posture classroom teaching effect detection system according to claim 1 is characterized in that: The camera (3) is installed in front of the student's desk, and the working end of the camera (3) faces the student's face, so that the camera (3) can completely collect the student's facial information during the class.

6. The human body posture classroom teaching effect detection system according to claim 1 is characterized in that: The desk pressure sensor group (4) is arranged on the student's desk, and the contact time and contact area between the student's upper limbs and the desk during class are determined by the pressure area on the desk pressure sensor group (4), and is used in conjunction with the camera (3).

7. The human body posture classroom teaching effect detection system according to claim 1 is characterized in that: When the seat pressure sensor group (5) is arranged on a student's seat, during class time, when the seat pressure sensor group (5) collects pressure information of the student when sitting or standing, the eye tracker (2), the camera (3) and the desk pressure sensor group (4) are controlled to be turned on; otherwise, the eye tracker (2), the camera (3) and the desk pressure sensor group (4) are turned off.

8. The human body posture classroom teaching effect detection system according to claim 1 is characterized in that: The statistical module (7) performs initial statistics on the information collected by the eye tracker (2), the camera (3) and the desk pressure sensor group (4) during the class with time as the coordinate axis, and after the initial statistics, performs secondary statistics on the time period when the information collected by the eye tracker (2), the camera (3) and the desk pressure sensor group (4) during the class is stable, and performs tertiary statistics on the initial statistical information and the secondary statistical information of each student.

9. The human body posture classroom teaching effect detection system according to claim 1 is characterized in that: The information processing module (8) integrates the information collected by the statistical module (7) respectively, and after the integration, integrates the time points and time periods corresponding to each student's eye tracker (2) and camera (3) and the teaching panel (1), analyzes and summarizes the classroom teaching effects at different time points and time periods during the class, and completes the detection and evaluation of the classroom teaching effects.

10. The method for using the human body posture classroom teaching effect detection system according to claim 1, characterized in that: The following steps are involved: S1, firstly, using the teaching panel (1) to display the classroom teaching content, and at the same time using the seat pressure sensor group (5) to determine the working status of the eye tracker (2), the camera (3) and the desk pressure sensor group (4), and collecting the student's posture information when the eye tracker (2), the camera (3) and the desk pressure sensor group (4) are in the working state; S2. After a single class teaching session is finished, the information on the students' postures in class collected by the eye tracker (2), the camera (3) and the desk pressure sensor group (4) is sent to the statistical module (7), and the statistical module (7) collects statistics on the collected information on the students' postures in class; S3, sending the information collected by the statistical module (7) to the information processing module (8) to detect and evaluate the classroom teaching effect using the information processing module (8), as follows: The time module (6) is used to set the duration of a single class as T, the start time as ts, and the end time as te; the time that the eye tracker (2) stays on the teaching panel (1) is Tef, the time that it stays on the desk is Tet, and the rest of the free time is Tel; The camera (3) captures the time during class when the student's face stays on the teaching panel (1) as Tff, the time when it stays on the desk as Tft, and the rest of the time when it is in a free state as Tfl; First, calculate and analyze the average value P1 of the ratio of Tef and Tff to T to determine the attractiveness of the teaching panel (1). If P1 is greater than or equal to 20, the teacher's teaching is qualified, otherwise it is unqualified; Then calculate and analyze the average value P2 of the ratio of Tet and Tft to T. If P2 is greater than or equal to 30, the teacher's teaching is qualified, otherwise it is unqualified; Then calculate and analyze the ratio of the sum of Tef and Tet to T (P3), the ratio of the sum of Tff and Tft to T (P4), and calculate the average value of P3 and P4 (P5). If P5 is greater than or equal to 70, the student has passed the class, otherwise, he has failed. Then, the starting time of Tef and Tff at different stages is tes and the ending time is tee. By determining the time point when tes and tee overlap with ts and te, the time point is fed back to the teaching content on the teaching panel (1) to determine the optimal teaching part of the teaching content.

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