Question bank difficulty adjustment method and device based on adaptive prop management and storage medium

Abstract

This invention discloses a method, device, and storage medium for adjusting the difficulty of a question bank based on adaptive tool management, belonging to the field of digital education technology. The method includes: acquiring user grade information and comparing it with a preset grade in the question bank to identify younger, advanced users; automatically activating difficulty reduction tools in response to the identification results, reducing the immediate difficulty of answering questions by modifying the question presentation format; collecting user answering behavior data in real time to construct ability assessment parameters; and dynamically adjusting the tool usage strategy in a step-by-step manner based on the comparison results between the ability assessment parameters and preset progressive thresholds, gradually transitioning from unlimited use initially to a daily limit, ultimately guiding users to answer questions independently. This invention effectively solves the problem of frustration caused by excessively difficult questions when younger users are learning ahead of schedule, systematically cultivating users' independent problem-solving abilities while protecting their learning interest, and achieving an adaptive learning transition.

Description

Technical Field

[0001] This invention relates to the field of digital education technology, and in particular to a method, device and storage medium for adjusting the difficulty of a question bank based on adaptive prop management. Background Technology

[0002] In current digital education platforms, question banks, as core teaching resources, are typically categorized according to textbook grade levels, such as junior high school textbooks corresponding to junior high school exercises. However, in practice, there are many scenarios where younger users (such as upper elementary school students) are using question banks designed for higher grades. Because these users' cognitive levels have not yet reached the corresponding grade level, directly facing highly difficult exercises can easily lead to frustration, affecting their learning interest and effectiveness.

[0003] Most existing question bank systems lack dynamic difficulty adjustment mechanisms tailored to individual user differences. While some systems offer features such as "hints" or "skip," these features are typically statically set and cannot be adaptively adjusted based on the user's learning progress, making it difficult to strike a balance between protecting learning interest and promoting skill development.

[0004] Therefore, there is an urgent need for a technical solution that can dynamically adjust the difficulty of the question bank and the assistance strategies based on the user's age, grade, and real-time answer performance, so as to support young users to achieve a smooth transition in the process of advanced learning and gradually improve their self-learning ability. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a method, device, and storage medium for adjusting the difficulty of a question bank based on adaptive tool management. It accurately identifies precocious young users through user profiling and activates a dynamic difficulty decay mechanism for them. Furthermore, based on real-time analysis of their answering behavior, it constructs a competency model, which drives a tiered adjustment of auxiliary strategies, ultimately achieving intelligent exit from educational intervention. The aim is to solve the technical problem of how to dynamically and adaptively adjust the difficulty of the question bank to systematically cultivate and transition precocious young users' independent problem-solving abilities while protecting their learning interest.

[0006] The technical solution of the present invention is as follows: On the one hand, this invention provides a method for adjusting the difficulty of a question bank based on adaptive prop management, characterized by the following steps: Step S100: Obtain the user's basic grade information; Step S200: Compare the basic grade information with the preset grade information of the current question bank, and generate a user type identifier based on the comparison result. When the basic grade information is lower than the preset grade information, the user type identifier is marked as a precocious user. Step S300: In response to the user type identifier of the precocious young user, activate a preset difficulty reduction tool for the user and configure an initial usage strategy; the difficulty reduction tool is configured to dynamically reduce the real-time difficulty of answering questions by modifying the presentation of the questions during the answering process. Step S400: Collect the user's answering behavior data in the question bank in real time; Step S500: Based on the answer behavior data, construct an ability assessment parameter; Step S600: The ability assessment parameters are compared with a number of preset progressive thresholds, and the use strategy of the difficulty reduction props is dynamically and stepwise adjusted according to the comparison results to achieve a smooth transition from assisted learning to autonomous learning.

[0007] Furthermore, the difficulty reduction item in step S300 is an option removal item; The modification of the question presentation format includes: when displaying the questions, identifying and hiding at least one incorrect option from the original number, so that the number of remaining options is less than the original number.

[0008] Furthermore, the construction of capability assessment parameters in step S500 specifically includes: The cumulative number of questions answered, the number of consecutive correct answers, and the statistical accuracy rate in the question-answering behavior data are weighted and calculated to generate a one-dimensional numerical ability value.

[0009] Furthermore, the dynamic adjustment in step S600 specifically includes: When the capability assessment parameter is lower than the first threshold, the first usage strategy is activated, which is a strategy with no limit on the number of uses. When the capability assessment parameter reaches the first threshold but is lower than the second threshold, the second usage strategy is activated. The second usage strategy is the daily first-time quota strategy. When the capability assessment parameter reaches the second threshold, a third usage strategy is activated. The third usage strategy is a daily second usage limit strategy, wherein the second usage limit is lower than the first usage limit.

[0010] Furthermore, after enabling the third usage strategy, it also includes: When it is detected that a user answers questions within a preset time period without using the difficulty reduction item, and the user's statistical accuracy rate remains above the set level, the fourth usage strategy is activated. The fourth usage strategy is either a periodic quota strategy or an item expiration strategy.

[0011] Second, 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, characterized in that the processor implements the method described above when executing the program.

[0012] Third, a computer-readable storage medium having a computer program stored thereon, characterized in that the program, when executed by a processor, implements the method described above.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: 1) By using the immediate intervention of difficulty reduction tools, the frustration experienced by younger users when first encountering challenging content was precisely eliminated, effectively protecting their learning interest. Simultaneously, through the tiered adjustment of strategies, the system systematically guided and compelled skill advancement, achieving an organic unity between interest protection and ability development.

[0014] 2) It enables each user to obtain a learning support path precisely matched to their current ability, providing a highly personalized learning experience and improving learning efficiency. It can understand the user's state, assess their level, and provide adaptive teaching feedback, enhancing the software's teaching effectiveness and technological added value. Attached Figure Description

[0015] Figure 1 This is a flowchart of the question bank difficulty adjustment method based on adaptive prop management according to the present invention; Figure 2 These are examples of 10 questions from the game interface and the question bank. Detailed Implementation

[0016] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments, but this should not limit the scope of protection of the present invention.

[0017] This invention achieves dynamic adjustment of the difficulty of the question bank through a system combining hardware and software. Figure 1 The diagram illustrates a system architecture of an embodiment of the present invention. This system is typically deployed on a cloud server, and users access the interactive puzzle game application through terminal devices (such as tablets or personal computers). The system mainly includes a user management module, a question bank management module, an item logic module, a behavior analysis module, and a strategy scheduling module. These modules work together to achieve the technical effects of the present invention.

[0018] 1. User information collection and type identification When a user registers for the first time or completes their personal information, the system collects their basic grade information (e.g., "sixth grade of primary school") through the user interface and stores it persistently in the user database to form an initial user profile.

[0019] When a user selects to enter a question bank (e.g., "Junior High School Grade 1 History Question Bank"), the strategy scheduling module retrieves the preset grade information for that question bank (i.e., "Junior High School Grade 1"). The system executes comparison logic: comparing the user's "Elementary School Grade 6" with the question bank's "Junior High School Grade 1". Since "Elementary School Grade 6" is lower than "Junior High School Grade 1", the system generates and binds a "Premature Advanced User" type identifier to that user's session. This identifier is the key switch that triggers all subsequent adaptive logic.

[0020] 2. Activation and initial configuration of difficulty reduction items Once a user is identified as a "prematurely advanced user," the strategy scheduling module sends an instruction to the item logic module. The item logic module then activates a difficulty decay item called "Eagle Eyes" (a specific implementation name of the "Error Option Removal" item) for the user account and sets its initial usage strategy to "unlimited uses."

[0021] In the actual answer interface, such as Figure 2 As shown, this tool will be displayed as a prominent icon on the side of the screen. When a user encounters a multiple-choice question with four options, clicking the tool icon will immediately interact with the question bank management module to obtain a list of correct and incorrect answers for the current question. Subsequently, the system will randomly remove two options from the list of incorrect answers, leaving only one incorrect answer and one correct answer for the user to choose from on the interface. This essentially reduces the absolute difficulty of the question from "four options" to "two options".

[0022] 3. Collection of answer behavior data and ability assessment All user actions related to answering questions, including but not limited to question ID, user answer, whether it is correct, answering time, and whether props are used, are captured in real time by the behavior analysis module and recorded in the log database.

[0023] The behavior analysis module periodically (e.g., after every 5 questions or once a day) aggregates and calculates this raw data to construct ability assessment parameters. In a preferred embodiment, these parameters are generated by a weighted formula: Ability score = (Total number of questions answered × W1 + Number of consecutive correct answers × W2 + Overall accuracy rate × W3) W1, W2, and W3 are preset weighting coefficients (for example, they can be set to 0.2, 0.5, and 0.3 respectively). This formula aims to more sensitively reflect the user's recent progress trend, especially the "number of consecutive correct answers" which has a higher weighting and can quickly capture the leap in the user's learning status.

[0024] 4. Dynamic, tiered strategy adjustments The strategy scheduling module pre-sets multiple progressive thresholds and their corresponding item usage strategies. The system compares the calculated ability values ​​with these thresholds and automatically switches strategies. The following is a specific adjustment example: Phase One (Intensive Support Period): When the user's ability value is less than 50, keep the "Eagle Eyes" item usable indefinitely. The goal of this phase is to help the user build confidence and become familiar with higher-level knowledge points.

[0025] Phase Two (Auxiliary Decrease Period): When the ability value is ≥ 50 and < 80, the strategy is adjusted to allow 15 uses per day. The system will notify the user of the strategy change through the interface, guiding them to use items more cautiously.

[0026] Phase Three (Self-Guided Learning Period): When the ability value is ≥ 80, the strategy is further tightened to allow 5 uses per day. At this point, the user has a good grasp of most knowledge points, and the system encourages them to answer questions more independently.

[0027] Phase Four (Quasi-Autonomy Period / Graduation): When the system detects that a user's correct answer rate without using props is ≥ 70% for three consecutive days, and the average number of questions answered per day is ≥ 10, the strategy scheduling module will execute the final strategy adjustment, setting the prop usage permission to twice per week. This signifies that the user has basically adapted to the question bank of this difficulty level, and the system has successfully assisted in the "gradualization."

[0028] Example Taking user A, a sixth-grade elementary school student, as an example, their parents purchased a junior high school question bank for them. When user A registered, the system recorded their grade as "sixth grade." Upon first entering the junior high school question bank level, the system automatically activated the "Incorrect Option Removal" tool, allowing unlimited use. During the quiz, user A gradually familiarized themselves with junior high school knowledge points with the tool's assistance. After accumulating 30 correct answers with a 75% accuracy rate, the system adjusted the tool's usage to 15 times per day. Continuing practice until 60 correct answers with an 85% accuracy rate, the usage was adjusted to 5 times per day. Finally, when user A could maintain an accuracy rate of over 70% without the tool's assistance, the tool's usage was limited to 2 times per week, guiding them to complete the exercises independently and achieving a smooth transition to advanced learning.

Claims

1. A method for adjusting the difficulty of a question bank based on adaptive prop management, characterized in that, Includes the following steps: Step S100: Obtain the user's basic grade information; Step S200: Compare the basic grade information with the preset grade information of the current question bank, and generate a user type identifier based on the comparison result. When the basic grade information is lower than the preset grade information, the user type identifier is marked as a precocious user. Step S300: In response to the user type identifier of the precocious young user, activate a preset difficulty reduction tool for the user and configure an initial usage strategy; the difficulty reduction tool is configured to dynamically reduce the real-time difficulty of answering questions by modifying the presentation of the questions during the answering process. Step S400: Collect the user's answering behavior data in the question bank in real time; Step S500: Based on the answer behavior data, construct an ability assessment parameter; Step S600: The ability assessment parameters are compared with multiple preset progressive thresholds, and the usage strategy of the difficulty reduction props is dynamically and stepwise adjusted according to the comparison results to achieve a smooth transition from assisted learning to autonomous learning.

2. The method according to claim 1, characterized in that, The difficulty reduction tool in step S300 is the option removal tool; The modification of the question presentation format includes: when displaying the questions, identifying and hiding at least one incorrect option from the original number, so that the number of remaining options is less than the original number.

3. The method according to claim 1, characterized in that, The construction of capability assessment parameters in step S500 is specifically as follows: The cumulative number of questions answered, the number of consecutive correct answers, and the statistical accuracy rate in the question-answering behavior data are weighted and calculated to generate a one-dimensional numerical ability value.

4. The method according to claim 1, characterized in that, The dynamic adjustment in step S600 specifically includes: When the capability assessment parameter is lower than the first threshold, the first usage strategy is activated, which is a strategy with no limit on the number of uses. When the capability assessment parameter reaches the first threshold but is lower than the second threshold, the second usage strategy is activated. The second usage strategy is the daily first-time quota strategy. When the capability assessment parameter reaches the second threshold, a third usage strategy is activated. The third usage strategy is a daily second usage limit strategy, wherein the second usage limit is lower than the first usage limit.

5. The method according to claim 4, characterized in that, After enabling the third usage strategy, the following is also included: When it is detected that a user answers questions within a preset time period without using the difficulty reduction item, and the user's statistical accuracy rate remains above the set level, the fourth usage strategy is activated. The fourth usage strategy is either a periodic quota strategy or an item expiration strategy.

6. 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 program, it implements the method as described in any one of claims 1 to 5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 5.

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