CN111310560A

CN111310560A - Learning state monitoring system based on big data

Info

Publication number: CN111310560A
Application number: CN201911424863.0A
Authority: CN
Inventors: 上超望; 刘沈; 马丽茹; 刘雨佳; 裴晓旭; 李文秀
Original assignee: Central China Normal University
Current assignee: Central China Normal University
Priority date: 2019-12-31
Filing date: 2019-12-31
Publication date: 2020-06-19

Abstract

The invention discloses a learning state monitoring system based on big data, which comprises a glasses body, a behavior database module, a comparison analysis and judgment module, an inquiry module and a monitoring device detachably mounted on the glasses body, wherein the monitoring device comprises an infrared detector for collecting eye images of students, an image processing module, a vibration device and a wireless transmission module, the image processing module is used for analyzing and processing the eye images obtained by the infrared detector, and when the eyes of the students are closed, the eyes of the students do not blink or the time of the sight line deviating from the center exceeds a preset threshold value, the learning state is judged to be abnormal, and the vibration device vibrates; the wireless transmission module wirelessly transmits the eye images and the abnormal duration of the learning state to the behavior database module, and the comparison analysis and judgment module counts the number of students with abnormal learning states in each period. The invention can effectively monitor the learning state of students and assist teachers in making adjustments.

Description

Learning state monitoring system based on big data

Technical Field

The invention relates to a learning state monitoring system based on big data.

Background

With the continuous development of scientific technology, deep learning, education big data and the like become the hotspots of education research, and it is very important to deeply analyze the learning behaviors of students in the big data background, however, students are still easy to be tired in the learning process, fatigue is a physiological phenomenon caused by excessive labor of physical or mental, the fatigue of students can be caused by various factors, and how to effectively monitor the fatigue state of students in the learning process under the big data background further corrects the learning behaviors of students, so that the students can reach a better learning state, which becomes a big problem.

Disclosure of Invention

The invention aims to overcome the defects of the prior art and provides a learning state monitoring system based on big data.

The technical scheme adopted by the invention for solving the technical problems is as follows:

a learning state monitoring system based on big data comprises a glasses body, a behavior database module, a comparison analysis and judgment module, an inquiry module and a monitoring device detachably mounted on the glasses body, wherein the monitoring device comprises an infrared detector used for collecting eye images of students, an image processing module, a vibration device and a wireless transmission module; the wireless transmission module wirelessly transmits the eye images and the abnormal duration of the learning state to the behavior database module, the comparison analysis and judgment module counts the number of students with abnormal learning states at each time period, and the query module is used for querying data in the behavior database module.

In another preferred embodiment, the comparison analysis and judgment module comprises an individual learning state database and a group learning state database, wherein the individual learning state is used for judging whether the individual is in a fatigue state, and the group learning state database is used for counting the abnormal number of students in the learning state in each period.

In another preferred embodiment, the threshold is 2 s.

In another preferred embodiment, the monitoring devices are two, and the two monitoring devices are symmetrically distributed on the upper parts of the two glasses frames of the glasses body.

In another preferred embodiment, the image processing module analyzes the eye image, and determines that the learning state is abnormal when the pupil size deviates from a preset normal pupil size range.

The invention has the beneficial effects that:

the eye condition of the student is monitored through the infrared detector, the eye closing condition, the eye blinking condition and the pupil area condition of the student are monitored mainly through monitoring, whether the student is in a fatigue learning state or not is judged through algorithm analysis at last, a teacher can timely find the student in the learning state abnormity to give help to the student, when the student is in group fatigue, the teacher can think back that the student is not enough in the teaching process and adjusts the student, the method for monitoring the fatigue state through eye movement has the advantages of higher monitoring efficiency and lower cost.

The invention is further explained in detail with the accompanying drawings and the embodiments; a big data-based learning state monitoring system of the present invention is not limited to the embodiments.

Drawings

FIG. 1 is a schematic structural diagram of a preferred embodiment of the present invention;

FIG. 2 is a schematic structural diagram of an infrared detector according to a preferred embodiment of the present invention;

FIG. 3 is a system block diagram of a preferred embodiment of the present invention;

FIG. 4 is a flow chart of individual learning state determination according to a preferred embodiment of the present invention;

FIG. 5 is a flow chart of the group learning state determination according to a preferred embodiment of the present invention.

Detailed Description

Embodiment, referring to fig. 1 to 5, the big data based learning state monitoring system of the present invention comprises a glasses body 10, a behavior database module 20, a comparison analysis and judgment module 30, a query module 40, and two monitoring devices 11 detachably mounted on the glasses body 10, wherein the two monitoring devices 11 are symmetrically distributed on the upper parts of two lens frames of the glasses body 10, the monitoring devices 11 comprise an infrared detector 12 for collecting images of eyes of students, an image processing module 13, a vibration device 14, a wireless transmission module 15, and a switch button 16, the image processing module 13 analyzes and processes the images of eyes obtained by the infrared detector 12, and when the time for which the eyes of the students are closed, the eyes of the students do not blink, or the sight line deviates from the center exceeds 2s, the learning state is determined to be abnormal, and the students are in a fatigue state, when the pupil size deviates from the preset normal pupil size, the learning state is determined to be abnormal, the embodiment adopts a conventional blink detection algorithm for judging the blink state of the student by calculating the aspect ratio value of the eyes, detects the sight line state of the student by a conventional driver sight line detection algorithm, and judges the pupil state of the student by positioning and size detection of the pupil, when the student is tired or the emotional fluctuation is large, the pupil deviates from the preset normal pupil size, when the learning state is abnormal, the vibration device 14 vibrates, the wireless transmission module 15 wirelessly transmits the eye image and the duration time of the learning state abnormality to the behavior database module 20, the contrast analysis determination module 30 counts the number of the students with abnormal learning state at each time period, the query module 40 is used for querying the data in the behavior database module 20, the comparison analysis and judgment module 30 includes a group learning state database, which counts the abnormal number of students in each period of time to form a student learning state line graph for teachers to observe the learning state of students in class through visual images.

In the classroom, the student wears glasses and installs monitoring devices 11, turn on shift knob 16, when the student is in fatigue state, student is reminded in slight vibrations of its vibrator 14, after a class, the teacher accessible consults the crowd database and observes the analysis to the holistic classroom learning state of student of a class, if appear that a moment or a plurality of moments student's total fatigue number is greater than or equal to fifty percent of classroom number, then, the teacher can think about oneself in this teaching in-process not enough and adjust.

The above embodiments are only used to further illustrate the big data based learning status monitoring system of the present invention, but the present invention is not limited to the embodiments, and any simple modifications, equivalent changes and modifications made to the above embodiments according to the technical spirit of the present invention fall within the protection scope of the technical solution of the present invention.

Claims

1. A big data-based learning state monitoring system is characterized in that: the glasses comprise a glasses body, a behavior database module, a comparison analysis and judgment module, an inquiry module and a monitoring device detachably mounted on the glasses body, wherein the monitoring device comprises an infrared detector used for collecting eye images of students, an image processing module, a vibration device and a wireless transmission module, the image processing module is used for analyzing and processing the eye images obtained by the infrared detector, when the eyes of the students are closed, the eyes do not blink or the sight line deviates from the center for more than a preset threshold value, the learning state is judged to be abnormal, and the vibration device vibrates; the wireless transmission module wirelessly transmits the eye images and the abnormal duration of the learning state to the behavior database module, the comparison analysis and judgment module counts the number of students with abnormal learning states at each time period, and the query module is used for querying data in the behavior database module.

2. The big-data-based learning state monitoring system according to claim 1, wherein: the comparison, analysis and judgment module comprises an individual learning state database and a group learning state database, the individual learning state judges whether the individual is in a fatigue state, and the group learning state database counts the abnormal number of students in each period of time.

3. The big-data-based learning state monitoring system according to claim 1, wherein: the threshold is 2 s.

4. The big-data-based learning state monitoring system according to claim 1, wherein: the monitoring devices are two, and the two monitoring devices are symmetrically distributed on the upper parts of the two glasses frames of the glasses body.

5. The big-data-based learning state monitoring system according to claim 1, wherein: and the image processing module analyzes and processes the eye image, and judges that the learning state is abnormal when the pupil size deviates from a preset normal pupil size range.