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CN-121996839-A - Personalized adjustment method, device, equipment and medium based on growth type task

CN121996839ACN 121996839 ACN121996839 ACN 121996839ACN-121996839-A

Abstract

The application relates to a personalized adjustment method, device and equipment based on a growth type task and a storage medium. The method comprises the steps of synchronously collecting behavior and emotion information of a user in a growth task to obtain a user behavior data set and a user emotion data set, analyzing and processing early-stage test data of the user and past difficulty adjustment records to obtain individual characteristic correction values of the user, carrying out weighted calculation according to the user behavior data set, the user emotion data set and the individual characteristic correction values to obtain difficulty adjustment coefficients, matching the difficulty adjustment coefficients with difficulty rules corresponding to a user cognition theory to obtain adjustment parameters, and adjusting the growth task according to the adjustment parameters. The task difficulty control method and the task difficulty control system realize more accurate task difficulty control which is more fit with the personalized demands of the users, not only comprehensively reflect the comprehensive state of the users in the task, but also give consideration to individual differences of the users, meet the unique demands of different users, and improve the accuracy of task adjustment.

Inventors

  • Request for anonymity

Assignees

  • 深圳市深科创产业发展有限公司

Dates

Publication Date
20260508
Application Date
20251211

Claims (10)

  1. 1. A personalized adjustment method based on growing-type tasks, the method comprising: Synchronously collecting behavior and emotion information of a user in a growth type task to obtain a user behavior data set and a user emotion data set; analyzing and processing the early-stage test data and the past difficulty adjustment record of the user to obtain an individual characteristic correction value of the user; Performing weighted calculation according to the user behavior data set, the user emotion data set and the individual characteristic correction value to obtain a difficulty adjustment coefficient; And matching the difficulty adjustment coefficient with a difficulty rule corresponding to a user cognitive theory to obtain an adjustment parameter, and adjusting the growth task according to the adjustment parameter.
  2. 2. The personalized adjustment method according to claim 1, wherein the step of synchronously collecting behavior and emotion information of the user in the growing task to obtain a user behavior data set and a user emotion data set comprises: Determining a task acquisition reference, wherein the acquisition reference comprises a task type, a task unit and an acquisition frequency; Acquiring behavior information of a user in a task process in real time according to the acquisition standard to obtain a user behavior data set; Based on facial features of the user during the task, a user emotion data set is identified.
  3. 3. The method for personalizing a growing-based task of claim 2, wherein identifying the set of user emotion data based on facial features of the user during the task comprises: Extracting facial features of a user in the task process by using ViT models; identifying initial emotion data of the user according to the facial features of the user; and verifying the initial emotion data based on the physiological signals of the user to obtain a user emotion data set.
  4. 4. The personalized adjustment method based on growing task of claim 1, wherein analyzing the user early test data and the past difficulty adjustment record to obtain the individual characteristic correction value of the user comprises: acquiring individual characteristic data of a user; Based on the individual characteristic data, carrying out amplitude and summation according to a first rule to obtain a basic characteristic correction value of the user; acquiring emotion feedback records corresponding to the past difficulty adjustment records of the user; Based on the emotion feedback records, performing assignment and summation according to a second rule to obtain past adjustment record correction scores of the users; and calculating the sum of the basic characteristic correction value and the past adjustment record correction value as an individual characteristic correction value of the user.
  5. 5. The method for personalized adjustment based on growing task according to claim 1, wherein the obtaining the difficulty adjustment coefficient by performing weighted calculation according to the user behavior data set, the user emotion data set and the individual feature correction value comprises: scoring each behavior parameter in the user behavior data set, and then carrying out weighted summation to obtain a behavior dimension total score; Scoring the emotion type and the emotion duration in the user emotion data set, and then carrying out weighted summation to obtain an emotion dimension total score; substituting the behavior dimension total score, the emotion dimension total score and the individual characteristic correction value into a preset formula to obtain a difficulty adjustment coefficient.
  6. 6. The personalized adjustment method based on growing task of claim 1, wherein the matching the difficulty adjustment coefficient with the difficulty rule corresponding to the user cognitive theory to obtain the adjustment parameter comprises: determining a difficulty adjustment direction according to the difficulty adjustment coefficient; Matching according to the adjustment direction and a difficulty rule corresponding to a user cognition theory, and determining a difficulty adjustment amplitude; and determining an adjustment parameter based on the difficulty adjustment direction and the difficulty adjustment amplitude.
  7. 7. The method for personalizing adjustment of a growing task according to claim 1, wherein when obtaining adjustment parameters and adjusting the growing task according to the adjustment parameters, the method further comprises: optimizing according to the adjustment parameters and the adjusted feedback data to obtain target adjustment parameters; And storing the target adjustment parameters into a user personalized parameter library.
  8. 8. A personalized adjustment device based on growing-type tasks, the device comprising: The acquisition unit is used for synchronously acquiring the behavior and emotion information of the user in the growing task to obtain a user behavior data set and a user emotion data set; The analysis unit is used for analyzing and processing the early-stage test data and the past difficulty adjustment record of the user to obtain an individual characteristic correction value of the user; The computing unit is used for carrying out weighted computation according to the user behavior data set, the user emotion data set and the individual characteristic correction value to obtain a difficulty adjustment coefficient; And the adjusting unit is used for matching the difficulty adjusting coefficient with a difficulty rule corresponding to the user cognitive theory to obtain an adjusting parameter and adjusting the growing task according to the adjusting parameter.
  9. 9. The electronic equipment is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory are communicated with each other through the communication bus; A memory for storing a computer program; a processor for implementing the growth-class task-based personalization adjustment method according to any one of claims 1 to 7 when executing a program stored on a memory.
  10. 10. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the growth-class task-based personalization adjustment method according to any one of claims 1 to 7.

Description

Personalized adjustment method, device, equipment and medium based on growth type task Technical Field The present application relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a storage medium for personalized adjustment based on a growing task. Background At present, in the adjustment scheme of the child growth type task, the prior art mainly relies on single data to adjust task difficulty, and lacks in-depth consideration of individual characteristics of children, and the adjustment mode of the prior art has a plurality of problems that on one hand, the adjustment of the single-dimension data can cause the unilateralness of adjustment and cannot fully reflect the real state of the children in the task, and on the other hand, the difference of individual information of the children is ignored, so that the task adjustment is difficult to fit with the unique requirements of each child. Therefore, how to perform personalized adjustment on the growing task to improve the accuracy of task adjustment has become a technical problem to be solved by those skilled in the art. It should be noted that the information disclosed in the above background section is only for enhancing understanding of the background of the present disclosure and thus may include information that does not constitute prior art known to those of ordinary skill in the art. Disclosure of Invention In view of the above, the present application provides a method, apparatus, device and storage medium for personalized adjustment based on growing task, which aims to solve the above technical problems. In a first aspect, the present application provides a method for personalized adjustment based on growing-type tasks, the method comprising: Synchronously collecting behavior and emotion information of a user in a growth type task to obtain a user behavior data set and a user emotion data set; analyzing and processing the early-stage test data and the past difficulty adjustment record of the user to obtain an individual characteristic correction value of the user; Performing weighted calculation according to the user behavior data set, the user emotion data set and the individual characteristic correction value to obtain a difficulty adjustment coefficient; And matching the difficulty adjustment coefficient with a difficulty rule corresponding to a user cognitive theory to obtain an adjustment parameter, and adjusting the growth task according to the adjustment parameter. In a second aspect, the present application provides a personalized adjustment device based on a growing task, including: The acquisition unit is used for synchronously acquiring the behavior and emotion information of the user in the growing task to obtain a user behavior data set and a user emotion data set; The analysis unit is used for analyzing and processing the early-stage test data and the past difficulty adjustment record of the user to obtain an individual characteristic correction value of the user; The computing unit is used for carrying out weighted computation according to the user behavior data set, the user emotion data set and the individual characteristic correction value to obtain a difficulty adjustment coefficient; And the adjusting unit is used for matching the difficulty adjusting coefficient with a difficulty rule corresponding to the user cognitive theory to obtain an adjusting parameter and adjusting the growing task according to the adjusting parameter. In a third aspect, the present application provides an electronic device, including a processor, a communication interface, a memory, and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus; A memory for storing a computer program; and the processor is used for realizing the steps of the personalized adjustment method based on the growing task according to any one of the embodiments of the first aspect when executing the program stored in the memory. In a fourth aspect, a computer readable storage medium is provided, on which a computer program is stored, which when being executed by a processor implements the steps of the growth-class task based personalization tuning method according to any of the embodiments of the first aspect. Compared with the prior art, the technical scheme provided by the embodiment of the application has the following advantages: According to the application, through synchronously collecting user behavior and emotion information and combining early-stage test data with past adjustment records, comprehensive analysis is performed to calculate the individual characteristic correction value, and the task difficulty is adjusted accordingly, so that more accurate task difficulty control which is more fit with individual demands of users is realized, the comprehensive state of the users in the task is comprehensively reflected, the