Learning effect evaluation method and device, equipment and medium
Through real-time evaluation of student facial data and screen display content, learning effect scores are calculated and teaching content is adjusted according to the scores, the problem of inability to adjust teaching in real time in the existing technology is solved, and teaching effect and learning efficiency are improved.
Patent Information
- Application Number
- CN202411432363.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-14
- Publication Date
- 2025-01-14
AI Technical Summary
The existing technology lacks methods to evaluate students' learning effects in real time, which leads to the inability to adjust the focus of teaching according to students' learning situation during teaching, which reduces learning efficiency.
Through students' facial data and screen display content, learning effect scores are generated in real time, scores are calculated using the field of vision and reading ability, and teaching content is adjusted according to the scores to achieve personalized teaching.
It has achieved personalized adjustments to the teaching content based on the real-time learning situation of different students, which has improved the teaching effect and improved the learning efficiency.
Smart Images
Figure CN119313218A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of computer technology, and in particular to a learning effect evaluation method, device, equipment and medium. Background Art
[0002] At present, the evaluation of students' learning effects is mainly completed through examinations, homework correction, etc. Since the above methods are all carried out after class, it is impossible to adjust the teaching focus according to the students' learning situation during teaching, thereby reducing students' learning efficiency. With the further development of AI technology, personalized teaching plans have become possible, but the existing technology lacks a method that can evaluate students' learning effects in real time.
[0003] To address the above problems, no effective solution has been proposed yet. Summary of the invention
[0004] Based on this, in order to solve the above problems, this paper proposes a learning effect evaluation method, device, equipment and medium. The present invention can generate students' learning effect scores in real time through students' facial data and screen display content, so that subsequent teaching content can be personalized according to the real-time learning situation of different students, which can greatly improve the teaching effect.
[0005] According to a first aspect of the present invention, there is provided a learning effect evaluation method, comprising:
[0006] Acquisition step, acquiring the student's facial data and screen display content;
[0007] Processing step, processing the student's facial data to obtain the student's field of view on the screen;
[0008] Reading ability acquisition steps, acquire students' reading ability;
[0009] The learning effect evaluation step is to obtain the student's learning effect score according to the screen display content, the student's visual field on the screen and the student's reading ability.
[0010] In some embodiments, it also includes a learning content adjustment step, determining the knowledge points that the students have not fully mastered based on the learning effect score, adjusting the subsequent screen display content in real time, and adding the content of the part of the knowledge points that the students have not fully mastered. The corresponding knowledge points with learning effect scores lower than the set threshold are identified as knowledge points that the students have not fully mastered, and the corresponding content is adjusted and added in the subsequent teaching. In some embodiments, this real-time adjustment is achieved through AI automatic adjustment.
[0011] In some embodiments, obtaining the student's learning effect score according to the screen display content, the student's field of view on the screen, and the student's reading ability includes:
[0012] The student's reading range on the screen is obtained through the student's field of vision on the screen and the student's reading ability, and the reading range is used as the student's learning range. The time the student stays in the reading range is used as the range learning time. The required learning time of the knowledge points in the learning range is obtained through the student's learning range. The student's learning effect score for the knowledge points in the learning range is calculated based on the range learning time and the required learning time for the knowledge points in the learning range.
[0013] In some embodiments, the calculation formula for the learning effect score is:
[0014]
[0015] Among them, s is the learning effect score of the knowledge points within the learning scope of the students, t1 is the learning time within the scope, t2 is the required learning time of the knowledge points within the learning scope, and α i is the correction coefficient of student i.
[0016] In some embodiments, the α i The method for obtaining is: obtaining the learning ability score of student i for the knowledge points within the learning scope, and normalizing the learning ability score to obtain the correction coefficient α of student i i .
[0017] In some embodiments, the learning ability score of the student i on the knowledge points within the learning scope includes: the student's test scores in the subject area to which the knowledge points belong.
[0018] In some embodiments, the method for acquiring the student's reading ability includes: testing the area that the student can see without eye movement, and generating the corresponding student's reading ability according to the area.
[0019] According to a second aspect of the present invention, there is provided a learning effect evaluation device, comprising:
[0020] An acquisition module is used to obtain students' facial data and screen display content;
[0021] A processing module is used to process the student's facial data and obtain the student's field of view on the screen;
[0022] A reading ability acquisition module is used to acquire students' reading ability;
[0023] The learning effect evaluation module is used to obtain the student's learning effect score based on the screen display content, the student's visual field on the screen and the student's reading ability.
[0024] According to a third aspect of the present invention, there is provided a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any of the above-mentioned method embodiments when executing the computer program.
[0025] According to a fourth aspect of the present invention, there is provided a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned embodiments of the method are implemented.
[0026] Beneficial effects of the present invention:
[0027] 1. Generate students’ learning effect scores in real time through students’ facial data and screen display content, so that subsequent teaching content can be personalized according to the real-time learning situation of different students to improve teaching effectiveness.
[0028] 2. Based on the focus range test, the reading ability of students can be obtained, which can better identify the differences in reading ranges of different students, thereby obtaining more accurate learning effect scores. BRIEF DESCRIPTION OF THE DRAWINGS
[0029] Figure 1 are flow charts of some embodiments of the learning effect evaluation method of the present invention;
[0030] Figure 2 is a schematic diagram of six key points of the eye in the present invention;
[0031] Figure 3 It is a multi-color concentric circle test chart in the present invention;
[0032] Figure 4 It is the color horizontal bar test chart of the present invention;
[0033] Figure 5 is a schematic diagram of the structure of some embodiments of the learning effect evaluation device of the present invention;
[0034] Figure 6 It is a diagram of the internal structure of a computer device used to implement some embodiments of the present invention. DETAILED DESCRIPTION
[0035] Embodiments of the present invention will be described more fully below with reference to the accompanying drawings, in which embodiments of the present invention are shown. However, the present invention can be embodied in many different forms and should not be construed as limited to the embodiments set forth herein.
[0036] The terms used herein are used only for the purpose of describing specific embodiments and are not intended to limit the present disclosure. As used herein, the singular forms "a", "an", "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that when used herein, the term "comprising" specifies the presence of the claimed features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups thereof.
[0037] Unless otherwise defined, the terms (including technical and scientific terms) used herein have the same meanings as commonly understood by those of ordinary skill in the art to which the present disclosure belongs. The terms used herein should be interpreted as having the meanings consistent with their meanings in the context of this specification and in the relevant field, and should not be interpreted in an idealized or overly formal sense, unless specifically defined as such herein.
[0038] Reading ability: that is, the ability of each person to read screen information when reading the screen, or the size of the area that each person can read when their line of sight is fixed.
[0039] 68 facial key points: The specific locations include 5 key points for one eyebrow, 6 key points for the eye, and other key points. This annotation scheme was first proposed in the Xm2vtsdb dataset in 1999, and has been widely used in the subsequent 300W dataset and XM2VTS dataset. The Dlib algorithm is a well-known algorithm that uses this 68-point annotation. It can accurately locate the positions of these 68 key points by analyzing facial images.
[0040] 6 eye key points: that is, 6 eye key points among the 68 facial key points.
[0041] Learning effect score: used to indicate the degree of students' mastery of different knowledge points. The student's reading range on the screen is obtained through the student's field of vision on the screen and the student's reading ability. The reading range is used as the student's learning range, and the time the student stays in the reading range is used as the learning time. The learning effect score of the student's knowledge point in the learning range is calculated through the learning range, learning time, and the required learning time of the knowledge point in the learning range.
[0042] The required learning time for the knowledge points within the learning scope: the shortest learning time for students to learn this knowledge point. The shortest learning time among all students to master this knowledge point can be used as the shortest learning time.
[0043] The student's reading range on the screen: the area on the screen that the student can read without moving his eyes. According to the student's reading ability, the corresponding area extending outward from the center of the student's field of view on the screen (the size of the area is consistent with the student's reading ability) is selected as the reading range.
[0044] Figure 1 The flowcharts show some embodiments of the learning effect evaluation method of the present invention.
[0045] like Figure 1 As shown, the method includes:
[0046] Acquisition step S102, acquiring the student's facial data and screen display content;
[0047] Processing step S104, processing the student's facial data to obtain the student's field of view on the screen;
[0048] In some embodiments, the specific steps include:
[0049] (1) Based on the student's facial data, use the dlib machine learning framework to specify parameters and locate the 68 key points of the face in dlib. Import the dlib library and import the parameters.
[0050] (2) Set the parameters and the corresponding ROI area. Detect the position of a region where the face is located, and then detect the position of the nose relative to the face frame, such as: the left eye of a person is at the face frame of 0.2w and 0.2h.
[0051] (3) The positions of the key points relative to the face frame, which correspond to the mouth, left eye, right eye, left eyebrow, right eyebrow, nose, and chin.
[0052] (4) Load face detection and key point location. Then return the coordinates of the four points of the face detection rectangle through the passed parameters. Take a certain area of the image as input and output a series of points to represent the posture in this image.
[0053] (5) Process the data and convert it into a grayscale image. Call the face frame detector, use the grayscale image for detection, and traverse the detection frame. Traverse the area and draw a circle around it. Extract the ROI area and display it. Detect the face and locate it based on the key points. After locating, apply the positioning information to the student's line of sight angle detection.
[0054] (6) Determine the sight angle through the six key points of the glasses. Import the Euclidean distance toolkit and locate the 68 key points. Figure 2As shown, among the 6 key points of the eye, when the sight angle changes, the Euclidean distance between P2 and P6 and P3 and P5 will change, and the distance between P1 and P4 will also change slightly. A formula is set based on the relationship between the 6 key points of the eye, that is, subtract P2 from P6, subtract P3 from P5, and then take the absolute value of the difference between P1 and P4 times the previous value. When the sight angle changes, the value will change accordingly, and the sight angle of the human eye can be judged based on this value. The calculation steps are as follows:
[0055] Calculate the Euclidean distance between points P2 and P6:
[0056]
[0057] Calculate the Euclidean distance between points P3 and P5:
[0058]
[0059] Calculate the Euclidean distance between points P1 and P4:
[0060]
[0061] Substitute into the formula to calculate:
[0062]
[0063] Through this formula, we can calculate a value s, which will change with the change of the viewing angle, and can be used to determine the viewing angle of the human eye.
[0064] (7) Locate the chin ROI area. The key points of the chin are marked at points 0-17.
[0065] (8) Solve the Euler angles based on the rotation matrix. The posture of an object relative to the camera can be represented by a rotation matrix and a translation matrix.
[0066] (9) Using rectangles and rectangular connecting frames, the key points are located and the world coordinate system is converted into 2D coordinates. Finally, the Euler angle is calculated through CV2 to grasp the three-dimensional sight angle of the face.
[0067] (10) Set face data. Import the 68 key point data of the face to set the face size. Determine the distance between the face and the screen based on the changes in the values of the 68 key points.
[0068] (11) Import the Euclidean distance toolkit. Import the face 3D sight angle numerical tool. According to the 3D sight angle range and screen distance, select a 25-degree range of focused attention on the screen as the student's field of vision on the screen.
[0069] Reading ability acquisition step S106, acquiring the student's reading ability;
[0070] In some embodiments, the area that the student can see without eye movement is tested, and the reading ability of the corresponding student is generated according to the area, including: directly using the area as the reading ability of the corresponding student.
[0071] Test method:
[0072] Use multi-colored concentric circles to test students' focus range, such as Figure 3 As shown, when a student can see a sphere of one color clearly without moving his eyes, the circular screen area of that color is regarded as the focusing range of the student, and the focusing range is regarded as the reading ability of the student.
[0073] The colored bars are used to test the students’ focus range and determine the effective reading length of the text. Figure 4 As shown, say the color order of the colored bars from left to right. When the eyeball moves (to the right), it means that it has exceeded the range of the visual focus point. The previous range is taken as the effective reading length, and the effective reading length is taken as the student's reading ability.
[0074] The learning effect evaluation step S108 is to obtain the student's learning effect score according to the screen display content, the student's visual field on the screen and the student's reading ability.
[0075] In some embodiments, the method for obtaining the learning effect score includes:
[0076] The student's reading range on the screen is obtained through the student's field of vision on the screen and the student's reading ability, and the reading range is used as the student's learning range. The time the student stays in the reading range is used as the range learning time. The required learning time of the knowledge points in the learning range is obtained through the student's learning range. The student's learning effect score for the knowledge points in the learning range is calculated based on the range learning time and the required learning time for the knowledge points in the learning range.
[0077] In some embodiments, a corresponding area extending outward from the center of the student's field of view on the screen (the size of the area is consistent with the student's reading ability) is selected as the reading range (i.e., the area on the screen that the student can see without moving his or her eyeballs) based on the student's reading ability.
[0078] In other embodiments, the student's field of view on the screen may be directly identified as the student's reading range on the screen.
[0079] The calculation formula for learning effect score is:
[0080]
[0081] Among them, s is the learning effect score of the knowledge points within the learning scope of the students, t1 is the learning time within the scope, t2 is the required learning time of the knowledge points within the learning scope, and α i is the correction coefficient of student i. i The method for obtaining is: obtaining the learning ability score of student i for the knowledge points within the learning scope (such as the test scores of students in the subject field to which the knowledge points belong, and the test scores include classroom tests, unit exercises, etc.), and normalizing the learning ability score to obtain the correction coefficient α of student i i .
[0082] In some embodiments, it also includes a learning content adjustment step, according to the learning effect score, determining the knowledge points that the students have not fully mastered, adjusting the subsequent screen display content in real time, and adding the content of the part of the knowledge points that the students have not fully mastered. When the learning effect score is lower than the set threshold, it is determined that the relevant knowledge points have not been mastered by the students, and the subsequent teaching content is adjusted in real time, and the teaching of the relevant knowledge points is automatically added. The above method can reduce or avoid students from learning subsequent knowledge points when the previous knowledge points are not mastered, thereby improving the teaching effect. In particular, it can play a good improvement role in the teaching of subjects such as mathematics and physics, which are prone to cause the subsequent teaching content to be incomprehensible when the previous knowledge points are not mastered.
[0083] The present invention generates a learning effect score of a student in real time through the student's facial data and the screen display content, thereby being able to provide timely feedback on the student's learning effect, providing assistance for the personalized customization of the classroom, and improving the teaching effect.
[0084] Figure 5 The following is a schematic diagram showing the structures of some embodiments of the learning effect evaluation device of the present invention.
[0085] like Figure 5 As shown, including:
[0086] An acquisition module 100 is used to acquire the student's facial data and screen display content;
[0087] The processing module 200 is used to process the facial data of the student and obtain the visual field of the student on the screen;
[0088] The reading ability acquisition module 300 is used to acquire the reading ability of the student;
[0089] The learning effect evaluation module 400 is used to obtain the student's learning effect score according to the screen display content, the student's visual field on the screen and the student's reading ability.
[0090] For the specific definition of a learning effect evaluation device, please refer to the definition of a learning effect evaluation method above, which will not be repeated here. Each module in the above-mentioned learning effect evaluation device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.
[0091] The present invention also provides a computer device, which may be a terminal, and its internal structure diagram may be as follows: Figure 6 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the above-mentioned learning effect evaluation method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc. Those skilled in the art can understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.
[0092] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned learning effect evaluation method is implemented.
[0093] Those skilled in the art can understand that all or part of the processes in the above method embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus), direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
[0094] So far, the embodiments of the present invention have been described in detail. In order to avoid obscuring the concept of the present invention, some details known in the art are not described. Based on the above description, those skilled in the art can fully understand how to implement the technical solutions disclosed herein.
[0095] Although some specific embodiments of the present invention have been described in detail by way of examples, it should be understood by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present invention. It should be understood by those skilled in the art that the above embodiments may be modified or some technical features may be replaced by equivalents without departing from the scope and spirit of the present invention. The scope of the present invention is defined by the appended claims.
Claims
1. A learning effect evaluation method, characterized in that: The following steps are involved: Acquisition step, acquiring the student's facial data and screen display content; Processing step, processing the student's facial data to obtain the student's field of view on the screen; Reading ability acquisition steps, acquire students' reading ability; The learning effect evaluation step is to obtain the student's learning effect score according to the screen display content, the student's visual field on the screen and the student's reading ability.
2. The learning effect evaluation method according to claim 1, characterized in that: Also includes, The learning content adjustment step determines the knowledge points that the students have not fully mastered based on the learning effect score, and adjusts the subsequent screen display content in real time to add the content of the knowledge points that the students have not fully mastered.
3. The learning effect evaluation method according to claim 1, characterized in that: The obtaining of the learning effect score of the student according to the screen display content, the student's field of vision on the screen and the student's reading ability includes: The student's reading range on the screen is obtained through the student's field of vision on the screen and the student's reading ability, and the reading range is used as the student's learning range. The time the student stays in the reading range is used as the range learning time. The required learning time of the knowledge points in the learning range is obtained through the student's learning range. The student's learning effect score for the knowledge points in the learning range is calculated based on the range learning time and the required learning time for the knowledge points in the learning range.
4. The learning effect evaluation method according to claim 3, characterized in that: The calculation formula for the learning effect score is: Among them, s is the learning effect score of the knowledge points within the learning scope of the students, t1 is the learning time within the scope, t2 is the required learning time of the knowledge points within the learning scope, and α i is the correction coefficient of student i.
5. The learning effect evaluation method according to claim 4, characterized in that: The α i The method for obtaining is: obtaining the learning ability score of student i for the knowledge points within the learning scope, and normalizing the learning ability score to obtain the correction coefficient α of student i i .
6. The learning effect evaluation method according to claim 5, characterized in that: The learning ability score of the student i for the knowledge points within the learning scope includes: the test scores of the student in the subject field to which the knowledge points belong.
7. The learning effect evaluation method according to claim 1, characterized in that: The method for acquiring the student's reading ability includes: testing the area that the student can see without eyeball rotation, and generating the corresponding student's reading ability according to the area.
8. A learning effect evaluation device, characterized in that: include: An acquisition module is used to obtain students' facial data and screen display content; A processing module is used to process the facial data of the students and obtain the visual field of the students on the screen; A reading ability acquisition module is used to acquire students' reading ability; The learning effect evaluation module is used to obtain the student's learning effect score based on the screen display content, the student's visual field on the screen and the student's reading ability.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.
10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.