Evaluation index value push method, system, device and medium

Abstract

The present invention provides a method and system, device and medium for pushing evaluation index values, the pushing method comprising the following steps: obtaining the evaluation index value corresponding to the first user; collecting the historical vital sign parameters of the second user with respect to the first user; pushing the evaluation index value to the second user based on the historical vital sign parameters; wherein the historical vital sign parameters include the vital sign parameters collected from the second user within a first preset time period after the second user receives the historical evaluation index value of the first user. The present invention realizes accurate and differentiated pushing of the evaluation index value corresponding to the first user to the second user through intelligent analysis of the historical vital sign parameters of the second user with respect to the first user, and can build a smart digital education ecosystem in the application scenario of student education, realize close connection and interaction between families, schools and students, and break through the limitation of lack of differentiated evaluation in the traditional digital education model.

Description

Technical Field

[0001] The present invention relates to the field of digital education technology, and in particular to a method and system, equipment and medium for pushing evaluation index values. Background Art

[0002] In the current information society, digital education has become an important part and trend of modern education and teaching. The teaching activities involved in this field cover three core roles, namely students, parents and teachers. In this ecological system, the synergy between family and school is particularly critical. Especially in the family education link, the role of parents is not only a companion, but also a guide and understander. Their understanding of students' learning process and learning outcomes directly affects the effectiveness of education and the quality of children's growth. The existing digital education platform already has powerful data collection and analysis functions, which can track and record various behavioral indicators of students' online learning in real time, such as learning time, task completion efficiency, knowledge mastery, etc. These rich data make it possible to form a comprehensive learning evaluation report, and can provide timely feedback through the parent-side application, so that parents can intuitively understand their children's independent learning status and their true learning ability performance inside and outside the school.

[0003] However, a significant problem in the existing digital education system is that the system cannot display differentiated competence models according to different user roles. The competence model here can be understood as an evaluation indicator constructed for students. This also leads to the inability to meet the personalized needs of each role. Take student personality traits as an example. For example, according to the definition of the Big Five personality trait model, children with good conscientiousness will have more regular time, be willing to act as organizers, usually do things in an orderly manner, have clear goals, abide by the rules, complete homework and tasks on time, and have a certain sense of planning for the future. Children with higher neuroticism may be more sensitive. When they are frustrated, they are more likely to feel anxious, depressed or angry, and may show stronger negative reactions when encountering difficulties. In Baumrind's family education style theory, the types of parents can be divided into neglectful, permissive, authoritative, democratic, etc. At present, some parents often put too much pressure on their children's education and growth because of their high expectations for their children and their concerns about educational competition. This situation is often exacerbated by parents' lack of understanding of their children's learning situation in school and their lack of overall grasp of their children's ability development. In addition, due to the differences in the types of traits of parents and children, not all ability evaluation indicators are suitable for display to different types of parents and children. A solution is needed that can selectively display the ability model based on the user's type traits. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the above-mentioned defects in the prior art and provide a method for pushing evaluation index values, comprising the following steps:

[0005] Obtaining an evaluation index value corresponding to the first user;

[0006] Collecting historical vital sign parameters of the second user about the first user;

[0007] Pushing the evaluation index value to the second user based on the historical vital sign parameter;

[0008] The historical vital sign parameters include vital sign parameters collected from the second user within a first preset time period after the second user receives the historical evaluation index value of the first user.

[0009] Preferably, the historical vital sign parameters also include vital sign parameters collected from the first user within a second preset time period after the second user receives the historical evaluation index value of the first user.

[0010] Preferably, the evaluation index value is set at several levels; and the step of pushing the evaluation index value to the second user based on the historical vital sign parameter comprises:

[0011] According to the historical vital sign parameters and the historical evaluation index values, the evaluation index values ​​that meet the preset level are pushed to the second user.

[0012] Preferably, the evaluation index value includes a plurality of single evaluation index values ​​and an overall evaluation index value, and the overall evaluation index value is generated based on the plurality of single evaluation index values; the overall evaluation index value and the plurality of single evaluation index values ​​are respectively provided with the plurality of levels; and the step of pushing the evaluation index value to the second user based on the historical vital sign parameter comprises:

[0013] According to the historical vital sign parameters and the historical evaluation index values, an overall evaluation index value or a single evaluation index value that meets a preset level is pushed to the second user.

[0014] Preferably, the push method further includes:

[0015] Based on the historical physical sign parameters and the evaluation index values, generating at least one of preset speech information, case information, and cognitive development research reports corresponding to the first user and the second user;

[0016] Among them, the preset speech information is used to be sent to the third user; the case information and cognitive development research report are used to be sent to the first user, the second user and the third user.

[0017] Preferably, the historical vital sign parameters include at least one of a heart rate parameter, a blood pressure parameter, and a sleep duration parameter.

[0018] Preferably, the first user is a target student, the second user is a parent of the target student, and the third user is a teacher of the target student;

[0019] and / or,

[0020] The individual evaluation index values ​​include self-discipline evaluation index value, plan execution ability evaluation index value, learning performance evaluation index value, and learning effect evaluation index value;

[0021] The overall evaluation index value is generated based on the self-discipline evaluation index value, the plan execution ability evaluation index value, the learning performance evaluation index value and the learning effect evaluation index value;

[0022] The overall evaluation index value, the self-discipline evaluation index value, the plan execution ability evaluation index value, the learning performance evaluation index value and the learning effect evaluation index value are respectively set to four levels: need to be improved, qualified, good and excellent;

[0023] and / or,

[0024] The preset level is determined based on at least one of the target student's age, the target student's gender, the target student's study time, the target student's practice accuracy, the target student's personality assessment information, the target student's parents' personality assessment information, the target student's family environment information, the target student's school environment information, and the target student's teacher recommendation information.

[0025] The present invention also provides a push system for evaluation index values, including:

[0026] An evaluation module, used to obtain an evaluation index value corresponding to the first user;

[0027] A collection module, used for collecting historical vital sign parameters of the second user about the first user;

[0028] A push module, configured to push the evaluation index value to the second user based on the historical vital sign parameter;

[0029] The historical vital sign parameters include vital sign parameters collected from the second user within a first preset time period after the second user receives the historical evaluation index value of the first user.

[0030] Preferably, the historical vital sign parameters also include vital sign parameters collected from the first user within a second preset time period after the second user receives the historical evaluation index value of the first user.

[0031] Preferably, the evaluation index value is set to several levels; the push module is also used for:

[0032] According to the historical vital sign parameters and the historical evaluation index values, the evaluation index values ​​that meet the preset level are pushed to the second user.

[0033] Preferably, the evaluation index value includes several single evaluation index values ​​and an overall evaluation index value, and the overall evaluation index value is generated based on the several single evaluation index values; the overall evaluation index value and the several single evaluation index values ​​are respectively provided with the several levels; the push module is further used for:

[0034] According to the historical vital sign parameters and the historical evaluation index values, an overall evaluation index value or a single evaluation index value that meets a preset level is pushed to the second user.

[0035] Preferably, the push module is also used for:

[0036] Based on the historical physical sign parameters and the evaluation index values, generating at least one of preset speech information, case information, and cognitive development research reports corresponding to the first user and the second user;

[0037] Among them, the preset speech information is used to be sent to the third user; the case information and cognitive development research report are used to be sent to the first user, the second user and the third user.

[0038] Preferably, the historical vital sign parameters include at least one of a heart rate parameter, a blood pressure parameter, and a sleep duration parameter.

[0039] Preferably, the first user is a target student, the second user is a parent of the target student, and the third user is a teacher of the target student;

[0040] and / or,

[0041] The individual evaluation index values ​​include self-discipline evaluation index value, plan execution ability evaluation index value, learning performance evaluation index value, and learning effect evaluation index value;

[0042] The overall evaluation index value is generated based on the self-discipline evaluation index value, the plan execution ability evaluation index value, the learning performance evaluation index value and the learning effect evaluation index value;

[0043] The overall evaluation index value, the self-discipline evaluation index value, the plan execution ability evaluation index value, the learning performance evaluation index value and the learning effect evaluation index value are respectively set to four levels: need to be improved, qualified, good and excellent;

[0044] and / or,

[0045] The preset level is determined based on at least one of the target student's age, the target student's gender, the target student's study time, the target student's practice accuracy, the target student's personality assessment information, the target student's parents' personality assessment information, the target student's family environment information, the target student's school environment information, and the target student's teacher recommendation information.

[0046] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for pushing evaluation index values ​​when executing the computer program.

[0047] 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 method for pushing the evaluation index value is implemented.

[0048] The positive and progressive effects of the present invention are: the present invention provides a method and system, device and medium for pushing evaluation index values, and realizes accurate and differentiated pushing of the evaluation index values ​​corresponding to the first user to the second user through intelligent analysis of the historical physical sign parameters of the second user about the first user. Especially in the application scenario of student education, the technical solution of the present invention can build an intelligent digital education ecosystem, realize close connection and interaction between families, schools and students, and effectively solve the problem that traditional digital education ignores individual differences and the limitations of students' ability development. By incorporating parent types into the scope of education data analysis, the optimal matching of family education methods and parent type characteristics is achieved, thereby alleviating the negative impact of parents' blind intervention to a certain extent, and effectively realizing the coordinated cooperation between teachers and parents in combination with the actual situation of the children, forming a more rational and effective education model. Based on the differentiated ability evaluation index display mechanism, it emphasizes object-oriented personalized services, reflecting the respect for students' physical and mental health and the support for the concept of holistic education. The introduction of the mental development path assessment tool helps teachers to deeply understand the students' internal growth laws, formulate more targeted teaching plans and improvement measures, and truly implement the principle of teaching students in accordance with their aptitude. Specific effects include:

[0049] 1. Differentiated display and communication: Flexibly display different dimensions of information in the student ability model based on the different role characteristics, emotional changes and type traits of parents, students and teachers, display appropriate ability indicators for different types of parents, reduce the impact of excessive parental intervention, and alleviate the pressure of parents on their children's education; display ability models that match students with different characteristics, which is conducive to stimulating students' potential and maintaining their mental health.

[0050] 2. Precise guidance and interaction: Provide customized information output to help parents establish scientific parenting concepts and promote more efficient and targeted communication between teachers and parents. Improve the quality of home-school cooperation by providing communication skills and successful cases with parents, as well as professional advice and support materials for ability indicators at all levels.

[0051] 3. Mental development assessment and support: It includes the function of recommending student cognitive development research reports, helping teachers and parents to deeply understand the laws of students' mental growth, so as to formulate teaching plans and improvement measures that are more in line with students' characteristics, and ensure that educational practice follows the principle of teaching students in accordance with their aptitude.

[0052] 4. Psychological quality training and care: not only pay attention to students' explicit academic performance, but also attach importance to the development of their implicit psychological qualities. By analyzing students' psychological characteristics such as emotional stability and ability to withstand pressure, ensure that they are given sufficient attention and reasonable training strategies in the education process.

[0053] The present invention comprehensively uses big data, psychology-related information technology and technical means to overcome the current educational pain points, better adapt to students' individual differences, support students' all-round development, and further enhance the efficiency of home-school collaboration; it enhances the close connection and interaction between families, schools and students, effectively solves the problem of traditional digital education ignoring individual differences, and strongly promotes the development of the education model towards a more rational and efficient personalized direction, which is conducive to the overall improvement of students' comprehensive quality and the realization of practical attention and protection for students' physical and mental health. By performing differentiated evaluation and display according to user roles and characteristics, the personalized level of education is improved, the synergy between home and school is strengthened, and it is helpful to achieve a more rational and effective education model and the teaching principle of teaching students in accordance with their aptitude. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a flowchart of a method for pushing evaluation index values ​​according to Embodiment 1 of the present invention.

[0055] Figure 2 This is a module diagram of a system for pushing evaluation index values ​​according to Example 2 of the present invention.

[0056] Figure 3 This is a structural block diagram of an electronic product according to Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0057] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0058] The push method of the evaluation index value provided in this embodiment can be executed in an intelligent terminal, a computer terminal, a network device, a chip, a chip module or a similar computing device. Mentioning "embodiment" in this application means that the specific features, structures or characteristics described in conjunction with the embodiment may be included in at least one embodiment of the present application. The appearance of this phrase in various positions in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described in this application can be combined with other embodiments.

[0059] It should be understood that the "system", "device", "unit" and / or "module" used herein are a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0060] As shown in this specification, unless the context clearly indicates an exception, the words "a", "an", "a kind" and / or "the" do not refer to the singular, but also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0061] Example 1

[0062] See also Figure 1 As shown, this embodiment specifically provides a method for pushing evaluation index values, including the following steps:

[0063] S1. Obtain the evaluation index value corresponding to the first user;

[0064] S2. Collecting historical vital signs parameters of the second user about the first user;

[0065] S3. Pushing evaluation index values ​​to the second user based on historical vital signs parameters;

[0066] The historical vital sign parameters include the vital sign parameters collected from the second user within a first preset time period after the second user receives the historical evaluation index value of the first user.

[0067] Step S1 obtains the evaluation index value corresponding to the first user, including but not limited to the ability evaluation index value, performance evaluation index value, etc.; preferably, the type of historical vital sign parameters includes at least one of heart rate parameters, blood pressure parameters, and sleep duration parameters, and the historical vital sign parameters are collected from the second user within a first preset time period after receiving the historical evaluation index value of the first user. For example, for the heart rate parameter, it can be collected within ten minutes, one hour, or twenty-four hours after the second user receives the historical evaluation index value of the first user. Based on the concept of the present invention, the historical vital sign parameters of the second user can reflect the second user's emotional changes, psychological fluctuations and other biological sign changes to the historical evaluation index value of the first user, and then be used as a reference for pushing the evaluation index value of the first user to the second user later.

[0068] As a preferred embodiment, the historical vital sign parameters also include the vital sign parameters collected from the first user within a second preset time period after the second user receives the historical evaluation index value of the first user. In this embodiment, the differentiated push method is further analyzed. It can be imagined that in some scenarios, the first user knows his historical evaluation index value; for example, the second user informs or communicates with the first user about the historical evaluation index value of the first user after learning about it; all of the above may have an impact on the biological signs of the first user; then this embodiment uses the previous historical vital sign parameters of the first user and the historical vital sign parameters of the second user as a reference for this recommendation based on this situation, which has better directionality and accuracy. It can be understood that the specific push logic, that is, what kind of historical vital sign parameters combined with the current evaluation index value will point to what kind of differentiated push results, can be determined according to dynamic preset rules, and the preset rules do not impose any restrictions on the concept of the present invention.

[0069] As a preferred implementation, the evaluation index value is set to several levels; the step of pushing the evaluation index value to the second user based on the historical vital sign parameter includes: pushing the evaluation index value that meets the preset level to the second user according to the historical vital sign parameter and the historical evaluation index value. This implementation embodies differentiated push in different treatments of each level of the evaluation index value, so that the push has better differentiation and refinement.

[0070] Preferably, the evaluation index value includes several single evaluation index values ​​and an overall evaluation index value, and the overall evaluation index value is generated based on the several single evaluation index values; the overall evaluation index value and the several single evaluation index values ​​are respectively set with several levels; the step of pushing the evaluation index value to the second user based on the historical vital sign parameters includes: according to the historical vital sign parameters and the historical evaluation index values, pushing the overall evaluation index value or the single evaluation index value that meets the preset level to the second user.

[0071] As a preferred implementation, the push method further includes:

[0072] Based on the historical physical sign parameters and the evaluation index values, generating at least one of preset speech information, case information, and cognitive development research reports corresponding to the first user and the second user;

[0073] Among them, the preset speech information is used to be sent to the third user; the case information and cognitive development research report are used to be sent to the first user, the second user and the third user.

[0074] This implementation method constructs a third user in addition to the evaluation object, i.e., the first user, and the evaluation recipient, i.e., the second user. It can be understood that in a digital teaching model, the third user can appear as an educational institution or teacher; this implementation method is that the teacher can provide the second user, i.e., the parent, with words and cases for communicating with the evaluation indicators of each level, such as cases of students changing for the better. It can be understood that in order to improve the communication efficiency between teachers and parents, the third user, i.e., the teacher, can also be pushed what evaluation indicator values ​​the first user, the student, and the second user, the parent, can know, so as to conduct more targeted communication processing.

[0075] As a preferred implementation, the first user is the target student, the second user is the target student's parent, and the third user is the target student's teacher; the single evaluation index value includes the self-discipline evaluation index value, the plan execution ability evaluation index value, the learning performance evaluation index value, and the learning effect evaluation index value; among them, the self-discipline evaluation index value can be quantitatively measured by comparing the degree of consistency between the actual learning time and the scheduled plan time, such as calculating the punctuality rate of completing tasks or the average delay time. The plan execution ability evaluation index value is based on the set learning goals and the achievement of the situation. For example, a daily / weekly task list is set up, and a scoring system is constructed based on factors such as the completion ratio and the number of consecutive days of meeting the target. The learning effect evaluation index value can use regression or classification algorithms in machine learning, such as logistic regression algorithms, decision tree algorithms, etc., combined with multiple factors such as the correct answer rate, the difficulty of the questions, and the time spent on answering questions to comprehensively predict the learning performance or skill mastery level.

[0076] The overall evaluation index value is generated based on the self-discipline evaluation index value, the plan execution ability evaluation index value, the academic performance evaluation index value and the learning effect evaluation index value; the overall evaluation index value, the self-discipline evaluation index value, the plan execution ability evaluation index value, the academic performance evaluation index value and the learning effect evaluation index value are respectively divided into four levels: need to be improved, qualified, good and excellent; the preset level is determined based on at least one of the target student's age, the target student's gender, the target student's study time, the target student's practice accuracy, the target student's personality assessment information, the target student's parents' personality assessment information, the target student's family environment information, the target student's school environment information, and the target student's teacher suggestion information.

[0077] As an example of this embodiment, based on the personality type traits of parents, the overall or sub-item evaluation index values ​​of their children, i.e., students, are displayed to them. The personality type traits of parents can be obtained based on the heart rate data when they learned the historical evaluation index values ​​of students before, and then the evaluation index values ​​are pushed to them in a targeted manner. Heart rate data can be obtained through the wearable device of parents. If the heart rate is higher than the preset value, only the ability model of the two level indicators of good and excellent in the student evaluation index value is displayed, otherwise the evaluation index values ​​of all levels are displayed. Democratic parents can show them the overall evaluation index value of students; anxious parents only show them the evaluation index values ​​of the three level indicators of qualified, good, and excellent. Optionally, the dimension selection of the evaluation index value is performed according to the personality type of the parents, for example, only the evaluation index values ​​related to learning habits are displayed, and the evaluation index values ​​related to academic performance are not displayed. Optionally, only the learning ability indicators with good and excellent grades in the ability model are displayed to students; optionally, the overall evaluation index of students is displayed to teachers; optionally, teachers can adjust the level range of the evaluation index values ​​displayed to students, such as only showing the ability indicators of good and excellent grades. Optionally, if no relevant data from parents is collected, the differentiated capability model display module displays evaluation index values ​​of three levels, namely qualified, good and excellent, to parents by default.

[0078] The method for pushing evaluation index values ​​in this embodiment realizes accurate and differentiated pushing of the evaluation index values ​​corresponding to the first user to the second user through intelligent analysis of the second user's historical vital sign parameters regarding the first user. In the application scenario of student education, it is possible to build a smart digital education ecosystem, realize close connection and interaction between families, schools and students, and break through the limitations of differentiated evaluation in the traditional digital education model.

[0079] Example 2

[0080] See also Figure 2 This embodiment also provides a system for pushing evaluation index values, including:

[0081] Evaluation module 1, used to obtain the evaluation index value corresponding to the first user;

[0082] Collection module 2, used for collecting historical vital sign parameters of the second user about the first user;

[0083] Push module 3, used for pushing the evaluation index value to the second user based on the historical vital sign parameters;

[0084] The historical vital sign parameters include the vital sign parameters collected from the second user within a first preset time period after the second user receives the historical evaluation index value of the first user.

[0085] The evaluation module 1 obtains the evaluation index value corresponding to the first user, including but not limited to the ability evaluation index value, the performance evaluation index value, etc.; preferably, the types of historical vital sign parameters collected by the collection module 2 include at least one of heart rate parameters, blood pressure parameters, and sleep duration parameters. The historical vital sign parameters are collected within the first preset time period after the second user receives the historical evaluation index value of the first user. For example, for the heart rate parameter, it can be collected within ten minutes, one hour, or twenty-four hours after the second user receives the historical evaluation index value of the first user. Based on the concept of the present invention, the historical vital sign parameters of the second user can reflect the second user's emotional changes, psychological fluctuations and other biological sign changes in response to the historical evaluation index value of the first user, and can be used as a reference for pushing the evaluation index value of the first user to the second user later.

[0086] As a preferred implementation, the historical vital sign parameters also include vital sign parameters collected from the first user within a second preset time period after the second user receives the historical evaluation index value of the first user.

[0087] In this embodiment, the differentiated push method is further analyzed. It can be imagined that in some scenarios, the first user knows his historical evaluation index value; for example, after the second user learns the historical evaluation index value of the first user, he informs or communicates with the first user about this matter; all of the above may have an impact on the biological signs of the first user; then this embodiment uses the previous physical sign parameters of the first user and the historical physical sign parameters of the second user as a reference for this recommendation based on this situation, which has better directionality and accuracy. It can be understood that the specific push logic, that is, what kind of historical physical sign parameters combined with the current evaluation index value will point to what kind of differentiated push results, can be determined according to dynamic preset rules, and the preset rules do not form any restrictions on the concept of the present invention.

[0088] As a preferred implementation, the evaluation index value is set to several levels; the push module 3 is also used for:

[0089] According to the historical vital sign parameters and the historical evaluation index values, the evaluation index values ​​that meet the preset level are pushed to the second user. The evaluation index values ​​are set to several levels; the step of pushing the evaluation index values ​​to the second user based on the historical vital sign parameters includes: according to the historical vital sign parameters and the historical evaluation index values, the evaluation index values ​​that meet the preset level are pushed to the second user. This implementation mode embodies differentiated push in different processing of each level of the evaluation index value, so that the push has better differentiation and refinement.

[0090] As a preferred implementation, the evaluation index value includes several single evaluation index values ​​and an overall evaluation index value, and the overall evaluation index value is generated based on several single evaluation index values; the overall evaluation index value and several single evaluation index values ​​are respectively set to several levels; the push module 3 is also used to push the overall evaluation index value or the single evaluation index value that meets the preset level to the second user according to the historical vital sign parameters and the historical evaluation index values. The evaluation index value includes several single evaluation index values ​​and an overall evaluation index value, and the overall evaluation index value is generated based on several single evaluation index values; the overall evaluation index value and several single evaluation index values ​​are respectively set to several levels; the step of pushing the evaluation index value to the second user based on the historical vital sign parameters includes: according to the historical vital sign parameters and the historical evaluation index values, pushing the overall evaluation index value or the single evaluation index value that meets the preset level to the second user.

[0091] As a preferred implementation, the push module 3 is also used to generate at least one of preset speech information, case information, and cognitive development research reports corresponding to the first user and the second user based on historical vital sign parameters and evaluation index values; wherein the preset speech information is used to be sent to the third user; and the case information and cognitive development research report are used to be sent to the first user, the second user, and the third user.

[0092] This implementation method constructs a third user in addition to the evaluation object, i.e., the first user, and the evaluation recipient, i.e., the second user. It can be understood that in a digital teaching model, the third user can appear as an educational institution or teacher; this implementation method is that the teacher can provide the second user, i.e., the parent, with words and cases for communicating with the evaluation indicators of each level, such as cases of students changing for the better. It can be understood that in order to improve the communication efficiency between teachers and parents, the third user, i.e., the teacher, can also be pushed what evaluation indicator values ​​the first user, the student, and the second user, the parent, can know, so as to conduct more targeted communication processing.

[0093] As a preferred implementation, the first user is the target student, the second user is the target student's parent, and the third user is the target student's teacher; the single evaluation index value includes the self-discipline evaluation index value, the plan execution ability evaluation index value, the learning performance evaluation index value, and the learning effect evaluation index value; among them, the self-discipline evaluation index value can be quantitatively measured by comparing the degree of consistency between the actual learning time and the scheduled plan time, such as calculating the punctuality rate of completing tasks or the average delay time. The plan execution ability evaluation index value is based on the set learning goals and the achievement of the situation. For example, a daily / weekly task list is set up, and a scoring system is constructed based on factors such as the completion ratio and the number of consecutive days of meeting the target. The learning effect evaluation index value can use regression or classification algorithms in machine learning, such as logistic regression algorithms, decision tree algorithms, etc., combined with multiple factors such as the correct answer rate, the difficulty of the questions, and the time spent on answering questions to comprehensively predict the learning performance or skill mastery level.

[0094] The overall evaluation index value is generated based on the self-discipline evaluation index value, the plan execution ability evaluation index value, the academic performance evaluation index value and the learning effect evaluation index value; the overall evaluation index value, the self-discipline evaluation index value, the plan execution ability evaluation index value, the academic performance evaluation index value and the learning effect evaluation index value are respectively divided into four levels: need to be improved, qualified, good and excellent; the preset level is determined based on at least one of the target student's age, the target student's gender, the target student's study time, the target student's practice accuracy, the target student's personality assessment information, the target student's parents' personality assessment information, the target student's family environment information, the target student's school environment information, and the target student's teacher suggestion information.

[0095] The evaluation index value push system of this embodiment realizes accurate and differentiated push of the evaluation index value corresponding to the first user to the second user through intelligent analysis of the second user's historical vital sign parameters of the first user. In the application scenario of student education, it can build a smart digital education ecosystem, realize close connection and interaction between families, schools and students, and break through the limitations of differentiated evaluation in traditional digital education models.

[0096] Example 3

[0097] Figure 3 This is a structural block diagram of an electronic device provided in this embodiment. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the method for pushing the evaluation index value in the above embodiment is implemented when the processor executes the program. Figure 3 The electronic device 30 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0098] like Figure 3As shown, the electronic device 30 may be in the form of a general-purpose computing device, for example, it may be a server device. The components of the electronic device 30 may include, but are not limited to: at least one processor 31, at least one memory 32, and a bus 33 connecting different system components (including the memory 32 and the processor 31).

[0099] The bus 33 includes a data bus, an address bus, and a control bus.

[0100] The memory 32 may include a volatile memory, such as a RAM 321 and / or a cache memory 322 , and may further include a ROM 323 .

[0101] The memory 32 may also include a program tool 325 having a set (at least one) of program modules 324, such program modules 324 including but not limited to: an operating system, one or more application programs, other program modules and program data, each of which or some combination may include the implementation of a network environment.

[0102] The processor 31 executes various functional applications and data processing by running the computer programs stored in the memory 32, such as the method for pushing the evaluation index value described above in the present invention.

[0103] The electronic device 30 may also communicate with one or more external devices 34 (e.g., keyboards, pointing devices, etc.). Such communication may be performed via an I / O interface 35. Furthermore, the model generating electronic device 30 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 36. Figure 3 As shown, the network adapter 36 communicates with other modules of the model-generated electronic device 30 via the bus 33. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the model-generated electronic device 30, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (disk array) systems, tape drives, and data backup storage systems, etc.

[0104] It should be noted that although several units / modules or sub-units / modules of the electronic device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided into multiple units / modules to be embodied.

[0105] Example 4

[0106] This embodiment also provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps in the method for pushing the evaluation index value in the above embodiment are implemented. The readable storage medium may be more specifically, but not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0107] In a possible implementation, the present invention may also be implemented in the form of a program product, which includes a program code, and when the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps in the method for pushing the evaluation index value as described above. The program code for executing the present invention may be written in any combination of one or more programming languages, and the program code may be executed completely on the user device, partially on the user device, as an independent software package, partially on the user device, partially on the remote device, or completely on the remote device.

[0108] Although the specific embodiments of the present invention are described above, it should be understood by those skilled in the art that this is only for illustration and the protection scope of the present invention is defined by the appended claims. Those skilled in the art may make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but these changes and modifications all fall within the protection scope of the present invention.

Claims

1. A method for pushing evaluation index values, characterized in that: The method is used for intelligently analyzing the historical vital sign parameters of the second user with respect to the first user, so as to push the current evaluation index value of the first user to the second user in a more accurate and differentiated manner, including the following steps: Obtaining an evaluation index value corresponding to the first user; Collecting historical vital sign parameters of the second user with respect to the first user; Pushing the evaluation index value to the second user based on the historical vital sign parameter; The historical vital sign parameters include the vital sign parameters collected from the second user within a first preset period of time after the second user receives the historical evaluation index value of the first user; The historical vital sign parameters also include vital sign parameters collected from the first user within a second preset period of time after the second user receives the historical evaluation index value of the first user; The evaluation index value is set to several levels; the step of pushing the evaluation index value to the second user based on the historical vital sign parameter includes: According to the historical vital sign parameters and the historical evaluation index values, the evaluation index values ​​that meet the preset level are pushed to the second user.

2. The method for pushing evaluation index values ​​according to claim 1, characterized in that: The evaluation index value includes a plurality of single evaluation index values ​​and an overall evaluation index value, and the overall evaluation index value is generated based on the plurality of single evaluation index values; the overall evaluation index value and the plurality of single evaluation index values ​​are respectively provided with the plurality of grades; The step of pushing the evaluation index value to the second user based on the historical vital sign parameter includes: According to the historical vital sign parameters and the historical evaluation index values, an overall evaluation index value or a single evaluation index value that meets a preset level is pushed to the second user.

3. The method for pushing evaluation index values ​​according to claim 2, characterized in that: The push method also includes: Based on the historical physical sign parameters and the evaluation index values, generating at least one of preset speech information, case information, and cognitive development research reports corresponding to the first user and the second user; Among them, the preset speech information is used to be sent to the third user; the case information and cognitive development research report are used to be sent to the first user, the second user and the third user.

4. The method for pushing evaluation index values ​​according to claim 3, characterized in that: The historical vital sign parameters include at least one of a heart rate parameter, a blood pressure parameter, and a sleep duration parameter.

5. The method for pushing evaluation index values ​​according to claim 4, characterized in that: The first user is a target student, the second user is a parent of the target student, and the third user is a teacher of the target student; and / or, The individual evaluation index values ​​include self-discipline evaluation index value, plan execution ability evaluation index value, learning performance evaluation index value, and learning effect evaluation index value; The overall evaluation index value is generated based on the self-discipline evaluation index value, the plan execution ability evaluation index value, the learning performance evaluation index value and the learning effect evaluation index value; The overall evaluation index value, the self-discipline evaluation index value, the plan execution ability evaluation index value, the learning performance evaluation index value and the learning effect evaluation index value are respectively set to four levels: need to be improved, qualified, good and excellent; and / or, The preset level is determined based on at least one of the target student's age, the target student's gender, the target student's study time, the target student's practice accuracy, the target student's personality assessment information, the target student's parents' personality assessment information, the target student's family environment information, the target student's school environment information, and the target student's teacher recommendation information.

6. A push system for evaluation index values, characterized in that: The method for pushing the evaluation index value according to any one of claims 1 to 5 comprises: An evaluation module, used to obtain an evaluation index value corresponding to the first user; A collection module, used for collecting historical vital sign parameters of the second user about the first user; A push module, configured to push the evaluation index value to the second user based on the historical vital sign parameter; The historical vital sign parameters include vital sign parameters collected from the second user within a first preset time period after the second user receives the historical evaluation index value of the first user.

7. An electronic 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 method for pushing the evaluation index value according to any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for pushing evaluation index values ​​according to any one of claims 1 to 5 is implemented.

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