CN111260517A - Intelligent teaching and management platform system and method for mobile phone - Google Patents
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Abstract
According to an example embodiment of the disclosure, a mobile phone intelligent teaching and management platform system and a method are provided. The system comprises an operation module and an evaluation module, wherein the operation module is used for determining whether the student is signed in or not based on the captured face image, fingerprint and voiceprint of the student, the evaluation module is used for determining the proportion of students with the visual angles of the student deviating from the display range of the learning content for more than a preset number of times, the head deviation angle for more than a preset angle, the eye closing time for more than a preset time interval and the mouth opening and closing size for more than a preset size to all the students, if the proportion is more than or equal to 70%, the teaching effect is determined to be poor, if the proportion is less than or equal to 20%, the teaching effect is determined to be good, and if the proportion is more than 20% and less than 70%, the teaching effect is determined to be. Therefore, the invention can realize more complex online teaching function and is beneficial to the application and popularization of new teaching modes such as online and offline, turnover classroom, combination of virtual and real and the like.
Description
Technical Field
The embodiment of the disclosure relates to the field of information processing, in particular to a mobile phone intelligent teaching and management platform system and a method.
Background
With the rapid development of information technology, more and more work, life and other modes adopt information technology such as internet and the like to improve efficiency, and the same is true in the aspect of education. Turning classroom, interactive teaching or mixed teaching mode application with students as the center, and online learning and virtual simulation experiments with internet and mobile communication as carriers are more and more emphasized. However, the current mode is only limited to uploading learning materials for online learning of students and is single.
Disclosure of Invention
The embodiment of the disclosure provides a mobile phone intelligent teaching and management platform system and a method, so that the system and the method can sign in based on the face, voiceprint and fingerprint of a student, send a related question bank based on wrong answer, send related knowledge points based on answer time and expression, extract related knowledge points based on class discussion hot topics and send related electronic books and video data, determine a teaching effect based on the head deviation angle, eye closing time and mouth opening and closing size of the student in the teaching process, adjust the teaching effect based on the score of a hall test, and improve the accuracy of teaching effect evaluation.
In a first aspect of the disclosure, a mobile phone intelligent teaching and management platform system is provided. The system comprises: the device comprises an operation module and an evaluation module; the operation module is used for capturing facial images, fingerprints and voiceprints of students through mobile phones of the students, determining whether the captured facial images, fingerprints and voiceprints of the students are matched with the facial images, fingerprints and voiceprints of the students stored in advance, if the facial images, fingerprints and voiceprints of the students are matched with the prestored facial images, the students are determined to have checked in, the operation module is also used for sending teaching process on-site tests to the checked-in students at the end of teaching courses, obtaining the test results of each checked-in student, determining the questions with the number of wrongly answered students exceeding the preset number, obtaining the question bank associated with the questions, pushing the question bank to the students with the wrongly answered questions, and establishing discussion topics associated with the questions in a class community, the operation module is also used for determining the answering time or the expressions of the questions of the students in the teaching process on-site tests, and if the answering time exceeds the preset answering time or the expressions including scratching heads or frowns, pushing a knowledge point associated with the question to the student, wherein the operation module is further used for determining a hot topic in class community discussion, extracting the knowledge point from the hot topic, acquiring electronic books and video data associated with the knowledge point, and pushing the acquired electronic books and video data to all students, wherein the operation module is further used for capturing face images of the students, determining whether the visual angle of the students deviates from the display area of the learning content based on the face images, and sending a reminding message to the students for reminding the students to pay attention to learning if the visual angle of the students deviates from the display area of the learning content; the evaluation module is used for capturing a plurality of face images of students listening to lessons in the teaching process, determining whether the number of times that the visual angles of the students deviate from the display range of the learning content exceeds a preset number of times, whether the head deviation angle exceeds a preset angle, whether the eye closing time exceeds a preset time interval and whether the mouth opening and closing size exceeds a preset size based on the plurality of face images, determining that the number of times that the visual angles of the students deviate from the display range of the learning content exceeds the preset number of times, the head deviation angle exceeds the preset angle, the eye closing time exceeds the preset time interval and the mouth opening and closing size exceeds the preset size accounts for the proportion of all the students, if the proportion is larger than or equal to 70%, determining that the teaching effect is poor, if the proportion is smaller than or equal to 20%, determining that the teaching effect is good, if the proportion is larger than 20% and smaller than 70, the evaluation module is also used for determining the test results of the in-place test in the teaching process, adjusting the teaching effect to one level upwards if the average score of the test results is greater than or equal to 80, and adjusting the teaching effect to one level downwards if the average score of the test results is less than or equal to 60.
In a second aspect of the disclosure, a method for mobile phone intelligent teaching and management is provided. The method comprises the following steps: capturing, at the server, a face image, a fingerprint and a voiceprint of the student via the student mobile phone, determining whether the captured face image, fingerprint and voiceprint of the student match with a pre-stored face image, fingerprint and voiceprint of the student, and if so, determining that the student has checked in; and capturing a plurality of face images of students attending class in the teaching process, determining whether the number of times that the viewing angle of the students deviates from the display range of the learning content exceeds a predetermined number of times, whether the head deviation angle exceeds a predetermined angle, whether the eye closing time exceeds a predetermined time interval, and whether the mouth opening and closing size exceeds a predetermined size based on the plurality of face images, determining the proportion of the students whose viewing angle deviates from the display range of the learning content exceeds the predetermined number of times, the head deviation angle exceeds the predetermined angle, the eye closing time exceeds the predetermined time interval, and the mouth opening and closing size exceeds the predetermined size to all the students, if the ratio is greater than or equal to 70%, the teaching effect is determined to be poor, if the ratio is less than or equal to 20%, the teaching effect is determined to be good, and if the ratio is more than 20% and less than 70%, the teaching effect is determined to be medium.
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the disclosure, nor is it intended to be used to limit the scope of the disclosure.
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The foregoing and other objects, features and advantages of the disclosure will be apparent from the following more particular descriptions of exemplary embodiments of the disclosure as illustrated in the accompanying drawings wherein like reference numbers generally represent like parts throughout the exemplary embodiments of the disclosure.
FIG. 1 shows a schematic diagram of an example of a cell phone smart tutoring and management platform system in accordance with an embodiment of the present disclosure;
FIG. 2 shows a schematic diagram of an example of a method 200 for cell phone smart tutoring and management in accordance with an embodiment of the present disclosure; and
FIG. 3 schematically illustrates a block diagram of an electronic device 300 suitable for use in implementing embodiments of the present disclosure.
Like or corresponding reference characters designate like or corresponding parts throughout the several views.
Detailed Description
Preferred embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
As described above, the current online teaching mode is single, and a more complicated teaching function cannot be realized.
In order to solve the above problems or other problems not described, the present disclosure provides a mobile phone intelligent teaching and management platform system. This is explained in detail below with reference to fig. 1.
Fig. 1 shows a schematic diagram of an example of a cell phone smart tutoring and management platform system in accordance with an embodiment of the present disclosure. As shown in fig. 1, the mobile phone intelligent teaching and management platform system includes an operation module and an evaluation module.
The operation module is used for capturing the face image, the fingerprint and the voiceprint of the student through the mobile phone of the student, determining whether the captured face image, the fingerprint and the voiceprint of the student are matched with the face image, the fingerprint and the voiceprint of the student which are stored in advance, and if the face image, the fingerprint and the voiceprint of the student are matched, determining that the student is checked in.
An evaluation module for capturing a plurality of face images of students attending class in a teaching process, determining whether the number of times that the angle of view of the student deviates from the display range of the learning content exceeds a predetermined number of times (e.g., 3, 5 times), whether the head deviation angle exceeds a predetermined angle (e.g., 30, 50 degrees), whether the eye closing time exceeds a predetermined time interval (e.g., 10, 20, 30 minutes), and whether the mouth opening size exceeds a predetermined size (e.g., upper and lower lip distances 1.5, 2cm) based on the plurality of face images, determining that the number of times that the angle of view of the student deviates from the display range of the learning content exceeds the predetermined number of times, the head deviation angle exceeds the predetermined angle, the eye closing time exceeds the predetermined time interval, and the mouth opening size exceeds the predetermined size accounts for all students, if the ratio is greater than or equal to 70%, determining that the teaching effect is poor, the teaching effect is determined to be good, and if the ratio is more than 20% and less than 70%, the teaching effect is determined to be medium.
In some embodiments, the operations module is further configured to send a teaching process on-the-fly test to the checked-in students at the end of a teaching course, obtain a test result for each checked-in student, determine a topic for which the number of wrongly answered students in the test exceeds a predetermined number, obtain a question bank associated with the topic, push the question bank to the wrongly answered students of the topic, and establish a discussion topic associated with the topic in a class community.
Alternatively or additionally, in some embodiments, the operation module is further configured to determine an answer time and an expression of a student on a question in the classroom test, and if the answer time exceeds a predetermined answer time (e.g., 10 minutes) and the expression includes scratching a head or frowning a eyebrow, pushing a knowledge point associated with the question to the student.
Alternatively or additionally, in some embodiments, the operation module is further configured to determine a trending topic in the class community discussion, extract a knowledge point from the trending topic, obtain electronic books and video materials associated with the knowledge point, and push the obtained electronic books and video materials to all students.
Alternatively or additionally, in some embodiments, the operation module is further configured to capture a facial image of the student, determine whether the viewing angle of the student deviates from the display area of the learning content based on the facial image, and send a reminding message to the student for reminding the student of the learning if it is determined that the viewing angle of the student deviates from the display area of the learning content.
Alternatively or additionally, in some embodiments, the evaluation module is further configured to determine the test scores of the in-house tests of the teaching process, adjust the teaching effect one level upwards if the average score of the test scores is greater than or equal to 80, and adjust the teaching effect one level downwards if the average score of the test scores is less than or equal to 60.
Therefore, the student can sign in based on the face, voiceprint and fingerprint of the student, the sign-in accuracy is improved, the phenomenon of sign-in on the behalf of the student is avoided, the relevant question bank is sent based on wrong answer, the pertinence of error correction is improved, the relevant knowledge points are sent based on that the answer time exceeds a preset time interval and the answer expression includes scratching or frowning, the proficiency of the relevant knowledge points is improved, the relevant knowledge points are extracted based on class discussion hot topics and are sent to the relevant electronic books and video data, the relevant learning data are accurately provided according to the class student interest points, the reminding is sent to the student based on the visual angle deviation learning content, the teaching effect is determined based on the frequency of the visual angle deviation learning content in the teaching process, the proportion of the head deviation angle, the eye closing time and the size of mouth opening and closing is determined, and the teaching effect is adjusted based on the score of the in-house, the accuracy of teaching effect evaluation is improved. Therefore, the invention is beneficial to the application and popularization of new teaching modes such as online and offline, turnover classroom, combination of virtual and actual teaching and the like.
Fig. 2 shows a schematic diagram of an example of a method 200 for cell phone smart tutoring and management, in accordance with an embodiment of the present disclosure. In fig. 2, the respective actions may be performed by the server, for example, or may be performed by the electronic device shown in fig. 3. It should be understood that method 200 may also include additional acts not shown and/or may omit acts shown, as the scope of the disclosure is not limited in this respect.
At block 202, at the server, a facial image, fingerprint, and voiceprint of the student are captured via the student handset, it is determined whether the captured facial image, fingerprint, and voiceprint of the student match the pre-stored facial image, fingerprint, and voiceprint of the student, and if it is determined that the captured facial image, fingerprint, and voiceprint of the student match the pre-stored facial image, fingerprint, and voiceprint of the student, it is determined that the student has checked in.
At block 204, a plurality of facial images are captured of a student attending a class during a teaching process.
At block 206, it is determined whether the number of times the viewing angle of the student deviates from the display range of the learning content exceeds a predetermined number of times (e.g., 3, 5 times), whether the head offset angle exceeds a predetermined angle (e.g., 30, 50 degrees), whether the eye closing time exceeds a predetermined time interval (e.g., 10, 20, 30 minutes), and whether the mouth opening size exceeds a predetermined size (e.g., upper and lower lip distance 1.5, 2cm) based on the plurality of face images.
At block 208, it is determined that the number of times the viewing angle of the student deviates from the display range of the learning content exceeds a predetermined number of times, the head offset angle exceeds a predetermined angle, the eye closing time exceeds a predetermined time interval, and the proportion of students whose mouth opening size exceeds a predetermined size to all students.
At block 210, the teaching effect is determined to be poor if the ratio is greater than or equal to 70%, good if the ratio is less than or equal to 20%, and medium if the ratio is greater than 20% and less than 70%.
In some embodiments, method 200 may further include sending a teaching process on-the-fly test to checked-in students at the end of a teaching course, obtaining test results for each checked-in student, determining a topic for which the number of wrongly answered students in the test exceeds a predetermined number, obtaining a question bank associated with the topic, pushing the question bank to the wrongly answered students, and establishing a discussion topic associated with the topic in a class community.
Alternatively or additionally, in some embodiments, the method 200 may further comprise determining a question answering time and an expression of a student on the question in the teaching process hall test, and pushing a knowledge point associated with the question to the student if the question answering time exceeds a predetermined question answering time (e.g., 10 minutes) and the expression includes scratching the head or frowning.
Alternatively or additionally, in some embodiments, the method 200 may further include determining a trending topic in the class community discussion, extracting knowledge points from the trending topic, retrieving electronic books and video material associated with the knowledge points, and pushing the retrieved electronic books and video material to all students.
Alternatively or additionally, in some embodiments, the method 200 may further include capturing facial images of the student, determining whether the viewing angle of the student deviates from the display area of the learning content based on the facial images, and sending a reminder message to the student for reminding the student of the attention to learning if it is determined that the viewing angle of the student deviates from the display area of the learning content.
Alternatively or additionally, in some embodiments, method 200 may further include determining the test performance of the in-house test of the teaching process, adjusting the teaching performance one level up if the average score of the test performance is greater than or equal to 80, and adjusting the teaching performance one level down if the average score of the test performance is less than or equal to 60.
Therefore, the student can sign in based on the face, voiceprint and fingerprint of the student, the sign-in accuracy is improved, the phenomenon of sign-in on the behalf of the student is avoided, the relevant question bank is sent based on wrong answer, the pertinence of error correction is improved, the relevant knowledge points are sent based on that the answer time exceeds a preset time interval and the answer expression includes scratching or frowning, the proficiency of the relevant knowledge points is improved, the relevant knowledge points are extracted based on class discussion hot topics and are sent to the relevant electronic books and video data, the relevant learning data are accurately provided according to the class student interest points, the reminding is sent to the student based on the visual angle deviation learning content, the teaching effect is determined based on the frequency of the visual angle deviation learning content in the teaching process, the proportion of the head deviation angle, the eye closing time and the size of mouth opening and closing is determined, and the teaching effect is adjusted based on the score of the in-house, the accuracy of teaching effect evaluation is improved. Therefore, the invention is beneficial to the application and popularization of new teaching modes such as online and offline, turnover classroom, combination of virtual and actual teaching and the like.
FIG. 3 schematically illustrates a block diagram of an electronic device 300 suitable for use in implementing embodiments of the present disclosure. Device 300 may be used to implement the platform system of fig. 1. As shown, device 300 includes a Central Processing Unit (CPU)301 that may perform various appropriate actions and processes in accordance with computer program instructions stored in a Read Only Memory (ROM)302 or loaded from a storage unit 308 into a Random Access Memory (RAM) 303. In the RAM303, various programs and data required for the operation of the device 300 can also be stored. The CPU301, ROM302, and RAM303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
Various components in device 300 are connected to I/O interface 305, including: an input unit 306 such as a keyboard, a mouse, or the like; an output unit 307 such as various types of displays, speakers, and the like; a storage unit 308 such as a magnetic disk, optical disk, or the like; and a communication unit 309 such as a network card, modem, wireless communication transceiver, etc. The communication unit 309 allows the device 300 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The processing unit 301 performs the various methods and processes described above, such as performing the method 200. For example, in some embodiments, the method 200 may be implemented as a computer software program stored on a machine-readable medium, such as the storage unit 308. In some embodiments, part or all of the computer program may be loaded and/or installed onto device 300 via ROM302 and/or communication unit 309. When the computer program is loaded into RAM303 and executed by CPU301, one or more of the operations of method 200 described above may be performed. Alternatively, in other embodiments, the CPU301 may be configured to perform one or more of the acts of the method 200 by any other suitable means (e.g., by way of firmware).
The present disclosure may be methods, apparatus, systems, and/or computer program products. The computer program product may include a computer-readable storage medium having computer-readable program instructions embodied thereon for carrying out various aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store the instructions for use by the instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic memory device, a magnetic memory device, an optical memory device, an electromagnetic memory device, a semiconductor memory device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a Static Random Access Memory (SRAM), a portable compact disc read-only memory (CD-ROM), a Digital Versatile Disc (DVD), a memory stick, a floppy disk, a mechanical coding device, such as punch cards or in-groove projection structures having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media as used herein is not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., optical pulses through a fiber optic cable), or electrical signals transmitted through electrical wires.
The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to a respective computing/processing device, or to an external computer or external storage device via a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. The network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing/processing device.
The computer program instructions for carrying out operations of the present disclosure may be assembler instructions, Instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, the electronic circuitry that can execute the computer-readable program instructions implements aspects of the present disclosure by utilizing the state information of the computer-readable program instructions to personalize the electronic circuitry, such as a programmable logic circuit, a Field Programmable Gate Array (FPGA), or a Programmable Logic Array (PLA).
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer-readable program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processing unit of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer-readable program instructions may also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer-readable medium storing the instructions comprises an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terms used herein were chosen in order to best explain the principles of the embodiments, the practical application, or technical improvements to the techniques in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (12)
1. A mobile phone intelligent teaching and management platform system comprises an operation module and an evaluation module;
the operation module is used for capturing face images, fingerprints and voiceprints of students through mobile phones of the students, determining whether the captured face images, fingerprints and voiceprints of the students are matched with prestored face images, fingerprints and voiceprints of the students, and if the captured face images, fingerprints and voiceprints of the students are matched with prestored face images, fingerprints and voiceprints of the students, determining that the students have checked in; and
the evaluation module is used for capturing a plurality of face images of students attending class in the teaching process, determining whether the number of times that the visual angles of the students deviate from the display range of the learning content exceeds a preset number of times, whether the head deviation angle exceeds a preset angle, whether the eye closing time exceeds a preset time interval and whether the mouth opening and closing size exceeds a preset size based on the plurality of face images, determining the proportion of the students whose visual angles deviate from the display range of the learning content exceeds the preset number of times, the head deviation angle exceeds the preset angle, the eye closing time exceeds the preset time interval and the mouth opening and closing size exceeds the preset size to all the students, if the ratio is greater than or equal to 70%, the teaching effect is determined to be poor, if the ratio is less than or equal to 20%, the teaching effect is determined to be good, and if the ratio is more than 20% and less than 70%, the teaching effect is determined to be medium.
2. The system of claim 1, wherein the operational module is further configured to send a teaching process on-the-fly test to checked-in students at the end of a teaching session, obtain a test result for each checked-in student, determine a topic for which the number of incorrectly answered students in the test exceeds a predetermined number, obtain a question bank associated with the topic, push the question bank to the incorrectly answered students, and establish a discussion topic associated with the topic in a class community.
3. The system of claim 1, wherein the operation module is further configured to determine a question answering time and an expression of a student on a question in the classroom testing, and if the question answering time exceeds a predetermined question answering time and the expression includes scratching or frowning, to push a knowledge point associated with the question to the student.
4. The system of claim 1, wherein the operation module is further configured to determine a trending topic in the class community discussion, extract knowledge points from the trending topic, obtain electronic books and video materials associated with the knowledge points, and push the obtained electronic books and video materials to all students.
5. The system of claim 1, wherein the operating module is further configured to capture facial images of the student, determine whether the viewing angle of the student deviates from the display area of the learning content based on the facial images, and send a reminding message to the student for reminding the student of the attention of the learning if it is determined that the viewing angle of the student deviates from the display area of the learning content.
6. The system of claim 1, wherein the pedagogy evaluation module is further configured to determine the test scores of the in-house tests of the pedagogy process, and adjust the pedagogy effect by one level upward if the average score of the test scores is greater than or equal to 80 scores, and by one level downward if the average score of the test scores is less than or equal to 60 scores.
7. A method for intelligent teaching and management of a mobile phone comprises the following steps:
capturing, at the server, a face image, a fingerprint and a voiceprint of the student via the student mobile phone, determining whether the captured face image, fingerprint and voiceprint of the student match with a pre-stored face image, fingerprint and voiceprint of the student, and if so, determining that the student has checked in; and
capturing a plurality of face images of students attending class in a teaching process, determining whether the number of times that the visual angle of the students deviates from the display range of the learning content exceeds a predetermined number of times, whether the head deviation angle exceeds a predetermined angle, whether the eye closing time exceeds a predetermined time interval, and whether the mouth opening and closing size exceeds a predetermined size based on the plurality of face images, determining the proportion of the students whose visual angle deviates from the display range of the learning content exceeds the predetermined number of times, the head deviation angle exceeds the predetermined angle, the eye closing time exceeds the predetermined time interval, and the mouth opening and closing size exceeds the predetermined size to all the students, if the ratio is greater than or equal to 70%, the teaching effect is determined to be poor, if the ratio is less than or equal to 20%, the teaching effect is determined to be good, and if the ratio is more than 20% and less than 70%, the teaching effect is determined to be medium.
8. The method of claim 7, further comprising:
the method comprises the steps of sending a teaching process on-site test to checked students when a teaching course is finished, obtaining a test result of each checked student, determining questions with the number of wrongly answered students exceeding a preset number in the test, obtaining question banks associated with the questions, pushing the question banks to the wrongly answered students, and establishing discussion topics associated with the questions in a class community.
9. The method of claim 7, further comprising:
determining the question answering time and the expression of a student in the in-class test of the teaching process, and pushing knowledge points associated with the question to the student if the question answering time exceeds the preset question answering time and the expression comprises head scratching or eyebrow creasing.
10. The method of claim 7, further comprising:
determining hot topics in class community discussions, extracting knowledge points from the hot topics, acquiring electronic books and video data associated with the knowledge points, and pushing the acquired electronic books and video data to all students.
11. The method of claim 7, further comprising:
the method comprises the steps of capturing face images of students, determining whether the visual angles of the students deviate from the display area of learning contents or not based on the face images, and sending reminding messages to the students for reminding the students to pay attention to learning if the visual angles of the students deviate from the display area of the learning contents.
12. The method of claim 7, further comprising:
and determining the test scores of the tests in the teaching process, adjusting the teaching effect to one level upwards if the average score of the test scores is greater than or equal to 80, and adjusting the teaching effect to one level downwards if the average score of the test scores is less than or equal to 60.
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| CN202010121867.8A CN111260517A (en) | 2020-02-23 | 2020-02-23 | Intelligent teaching and management platform system and method for mobile phone |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114049669A (en) * | 2021-11-15 | 2022-02-15 | 海信集团控股股份有限公司 | Method and device for determining learning effect |
| CN114399827A (en) * | 2022-03-14 | 2022-04-26 | 潍坊护理职业学院 | College graduate career personality testing method and system based on facial micro-expression |
-
2020
- 2020-02-23 CN CN202010121867.8A patent/CN111260517A/en not_active Withdrawn
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114049669A (en) * | 2021-11-15 | 2022-02-15 | 海信集团控股股份有限公司 | Method and device for determining learning effect |
| CN114399827A (en) * | 2022-03-14 | 2022-04-26 | 潍坊护理职业学院 | College graduate career personality testing method and system based on facial micro-expression |
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