Word mastering degree testing method and system

Abstract

The invention provides a word mastering degree testing method and system, and the method comprises the steps: constructing a memory palace which comprises a plurality of situation element regions closely related to a to-be-learned word in a learning target; in the memorizing stage, according to the navigation path in the memorizing palace, guiding the user to enter each area one by one to carry out interactive practice of word memorizing; a test sequence used for testing the word mastering degree of the user is generated, and all test questions in the test sequence are correspondingly associated with the situation elements in the memory palace; and in the test stage, guiding the user to test the test questions in sequence according to the test sequence, and displaying test scores in real time to evaluate the mastering degree of the user on all words in the learning target. According to the method, accurate testing is carried out through situational and guiding learning and test sequence generation, the user can be helped to master the words more efficiently, the learning effect is improved, and the master degree of the user on the whole words is accurately evaluated.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method and system for testing word mastery. Background Art

[0002] Electronic dictionaries and online learning platforms have gradually become new tools for many learners to memorize words. These platforms usually provide functions such as word definitions, examples and pronunciation, making it convenient for learners to check and learn at any time.

[0003] However, despite the rich vocabulary resources of these vocabulary learning platforms, there are still some problems in actual application: learners often rely on rote memorization and lack effective memory anchors and systems, which leads to poor memory effects and the formation of short-term memories. Frequent repetition is required to avoid forgetting, which is time-consuming and easy to discourage learners' independent enthusiasm, forming a vicious circle and increasing the difficulty of language self-study; and the test question banks of many platforms are not constructed scientifically enough, and the questions are disorganized, making it difficult to accurately measure learners' true level of mastery of vocabulary, which in turn hinders learners' accurate assessment of their own learning status. Summary of the invention

[0004] Based on this, the purpose of the present invention is to provide a method and system for testing the degree of word mastery to solve the above-mentioned problems.

[0005] A method for testing the degree of word mastery proposed by the present invention comprises:

[0006] Build a memory palace that contains multiple contextual elements that are closely related to the words to be learned in the learning objectives;

[0007] In the memorization stage, according to the navigation path in the memory palace, the user is guided to enter each area one by one to conduct interactive exercises on word memorization;

[0008] Generate a test sequence for testing the user's vocabulary mastery, wherein each test question in the test sequence is associated with a context element in the memory palace;

[0009] During the test phase, the user is guided to take the test questions in order according to the test sequence, and the test results are displayed in real time to evaluate the user's mastery of all the words in the learning objectives.

[0010] Furthermore, the construction of a memory palace includes:

[0011] Define a blank memory palace space object, where the memory palace object is a data structure used to represent space;

[0012] Generate multiple areas in the memory palace space and assign a unique identifier to each area, wherein each area corresponds to a learning topic;

[0013] For each area, formulate contextual elements closely related to the corresponding topic and all the words to be learned under the topic, and associate the words to be learned with the contextual elements;

[0014] Generate a navigation path to guide users through all areas to complete efficient memorization and learning of words.

[0015] Furthermore, generating a navigation path includes:

[0016] A navigation generation algorithm based on Q-learning is introduced to generate an optimal navigation path.

[0017] Furthermore, the introduction of a navigation generation algorithm based on Q-learning to generate an optimal navigation path includes:

[0018] Define a first state space, regard each area in the memory palace as a state, and the first state space includes all areas;

[0019] defining a first action space, the first action space comprising all actions of a user moving from one area to another area;

[0020] A first reward function is set based on the user's learning progress and the degree of mastery of each word;

[0021] Initialize a policy to decide what action the user should take in a given state;

[0022] Iteratively optimize the strategy through the Q-learning algorithm. In each iteration, guide the user to interact with the memory palace according to the current strategy and collect interaction data, which includes status, action and reward.

[0023] updating the strategy based on the interaction data so as to make better decisions in the next iteration;

[0024] When the strategy converges, an optimal navigation path is generated according to the optimized strategy, where the navigation path is a sequence of actions from the starting area to the target area.

[0025] Furthermore, the generating of a test sequence for testing the user's word mastery includes:

[0026] Based on the dynamic programming algorithm, a test sequence is generated to test the user's word mastery.

[0027] Furthermore, based on the dynamic programming algorithm, a test sequence for testing the user's word mastery is generated, including:

[0028] A second state space is defined, wherein each test sequence is regarded as a state, each test sequence is composed of a set of test questions in a specific order, and the second state space S contains all the test sequences;

[0029] A second action space is defined, wherein the second action space A represents the action of selecting test questions when generating a test sequence, each action a corresponds to selecting a test question from a test question library and adding it to the test sequence currently being constructed, and the action is selected based on the difficulty level, question type, words tested and related attributes of each test question;

[0030] The second reward function R(s, a) is set based on the user's mastery of the overall words in the learning goal, where s∈S represents the current state and a∈A represents the action taken;

[0031] Based on the defined second state space and second action space, the test questions are screened and sorted from a wide test question bank through a dynamic programming algorithm to generate an optimal test sequence for testing the user's mastery of words.

[0032] Furthermore, based on the defined second state space and second action space, the test questions are screened and sorted from a wide test question library by a dynamic programming algorithm to generate an optimal test sequence, including:

[0033] Create an empty test sequence as the starting state, and a table for storing the best test sequence and its corresponding reward value;

[0034] For the test sequence currently being constructed, traverse all test questions in the test question bank;

[0035] For each test question, calculate a new state formed after adding it to the current test sequence, and evaluate the reward value of the new state according to the second reward function, wherein the reward value is used to reflect the test effect of the test sequence on the degree of word mastery;

[0036] Filter out the state with the largest reward value from all potential new states as the next optimal state, and store the selected optimal state and reward value in a table;

[0037] When the test sequence reaches the preset length, the search stops and the stored optimal test sequence and its corresponding reward value are returned;

[0038] According to the optimal state and action recorded in the table, the optimal test sequence is generated in reverse order.

[0039] Furthermore, in the memorization stage, according to the navigation path in the memory palace, the user is guided to enter each area one by one to perform interactive exercises on word memorization, in the steps:

[0040] The interactive exercises include dragging the words to be learned onto the correct objects or selecting words in the context to fill in the blanks.

[0041] The present invention also proposes a test system for word mastery, the system comprising:

[0042] Memory Palace Module: used to build a memory palace, which contains multiple contextual element areas that are closely related to the words to be learned in the learning objectives;

[0043] Memory module: used to guide users to enter each area one by one for interactive practice of word memorization according to the navigation path in the memory palace during the memorization stage;

[0044] A test sequence module is used to generate a test sequence for testing the user's vocabulary mastery, wherein each test question in the test sequence is associated with a context element in the memory palace;

[0045] Test module: used to guide the user to take the test questions in order according to the test sequence during the test phase, and display the test results in real time to evaluate the user's mastery of all the words in the learning objectives.

[0046] In summary, according to the above-mentioned method for testing the degree of word mastery, a memory palace is constructed by combining the words to be learned with closely related contextual elements, so that users can connect the words with actual application scenarios during the memory process to deepen their memory and understanding, and the navigation path in the memory palace can guide users to traverse various areas in an orderly manner for learning. This orderly learning method avoids the blindness and fragmentation of learning, helps to improve memory efficiency, and thus ensures that users can master all words comprehensively and systematically; the generated test sequence is closely related to the contextual elements in the memory palace to ensure the pertinence and comprehensiveness of the test content, and the test is performed according to the generated test sequence, which can accurately evaluate the user's mastery of all words in the learning goal. The present invention can help users master words more efficiently, improve learning effects, and accurately evaluate their overall mastery of words through contextualized and guided learning and generation of test sequences for precise testing.

[0047] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description or will be learned through embodiments of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0049] Figure 1 A flowchart of a method for testing word mastery according to Embodiment 1 of the present invention;

[0050] Figure 2 The system block diagram of a system for testing the degree of word mastery according to the second embodiment of the present invention. DETAILED DESCRIPTION

[0051] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0052] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0054] Embodiment 1

[0055] See also Figure 1 The present invention proposes a method for testing the degree of word mastery, the method comprising steps S101 to S104:

[0056] S101, construct a memory palace, which includes multiple contextual element areas that are closely related to the words to be learned in the learning objectives.

[0057] Understandably, by constructing a memory palace that contains multiple contextual element areas that are closely related to the words to be learned in the learning objectives, a context-rich learning environment is provided for learners. The construction of the memory palace should be based on the learning objectives, ensuring that each contextual element area is related to the words to be learned, so as to form a strong associative memory in the learner's mind, thereby improving memory efficiency and deepening the impression of words through contextualized learning.

[0058] Situational elements can be scene stories, historical events, and game interactions. They can be customized according to the corresponding themes in the area and associated with multiple or all words to be learned under the same theme. For example, by creating a short story or plot related to the theme, the words under the theme are integrated into the context. In this way, while memorizing the words, learners also build a storyline associated with the words in their minds, which is convenient for subsequent recall, thereby improving the memory effect and realizing the associated memory of multiple words under the same theme, making memory efficient.

[0059] S102, in the memorization stage, according to the navigation path in the memory palace, guide the user to enter each area one by one to perform interactive exercises on word memorization.

[0060] Understandably, in the memorization stage, according to the navigation path in the memory palace, the user is guided to enter each area one by one to conduct interactive exercises on word memorization, ensuring the orderliness and systematicness of learning. The optimized navigation path can better guarantee the memory effect and learning efficiency. At the same time, the exercise results are fed back instantly, the correct answers and explanations are given, and the pronunciation, meaning, examples and usage tips of the words in the context are provided. Interactive exercises can be carried out by dragging the words to be learned to the correct objects or selecting words in the context to fill in the blanks, which enhances the interactivity of learning.

[0061] S103, generating a test sequence for testing the user's word mastery, wherein each test question in the test sequence is associated with a contextual element in the memory palace.

[0062] Understandably, in order to test the user's mastery of words, a test sequence needs to be generated first. Each test question in the test sequence corresponds to the situational elements in the memory palace, ensuring the pertinence and comprehensiveness of the test content. Through the test sequence, the user's mastery of all the words in the learning objectives can be accurately evaluated.

[0063] S104, in the test phase, the user is guided to take the test questions in order according to the test sequence, and the test results are displayed in real time to evaluate the user's mastery of all the words in the learning objectives.

[0064] Understandably, during the test phase, users are guided to take tests of each test question in sequence according to the test sequence, and the test results are displayed in real time so that learners can keep abreast of their learning progress and mastery. The test results include accuracy, error types, and the distribution of each wrong question in the subject area of ​​the memory palace, which is convenient for users to review in a targeted manner, and focus on strengthening the study of the corresponding topics in areas with more wrong questions to improve review efficiency.

[0065] Based on step S101 to step S104, a memory palace is constructed by combining the words to be learned with closely related contextual elements, so that the user can connect the words with actual application scenarios during the memory process to deepen memory and understanding, and the navigation path in the memory palace can guide the user to traverse various areas in an orderly manner for learning. This orderly learning method avoids the blindness and fragmentation of learning, helps to improve memory efficiency, and thus ensures that the user can master all words comprehensively and systematically; the generated test sequence is closely related to the contextual elements in the memory palace, ensuring the pertinence and comprehensiveness of the test content, and testing according to the generated test sequence can accurately evaluate the user's mastery of all words in the learning goal. The present invention can help users master words more efficiently, improve learning effects, and accurately evaluate their overall mastery of words through contextualized and guided learning and generation of test sequences for precise testing.

[0066] The following is a further detailed introduction to a method for testing the degree of word mastery in an embodiment of the present invention:

[0067] Further optionally, in step S101, constructing a memory palace includes:

[0068] Define a blank memory palace space object, where the memory palace object is a data structure used to represent space;

[0069] Generate multiple areas in the memory palace space and assign a unique identifier to each area, wherein each area corresponds to a learning topic;

[0070] For each area, formulate contextual elements closely related to the corresponding topic and all the words to be learned under the topic, and associate the words to be learned with the contextual elements;

[0071] Generate a navigation path to guide users through all areas to complete efficient memorization and learning of words.

[0072] Understandably, define a blank space object, which is a virtual, customizable data structure space; generate multiple areas in the memory palace space, each area corresponds to a learning topic, and by dividing multiple topic areas, you can classify and organize words, so as to customize the context elements under the topic, so as to achieve the same batch of associative memory of multiple words under the same topic, which not only greatly improves the memory efficiency, but also deepens the memory impression, and assigns a unique identifier to each topic area to ensure the uniqueness and accessibility of each area in the memory palace; for each area, set the context elements closely related to the corresponding topic and all the words to be learned under it, and associate the words with the context elements; generate a navigation path to guide users to traverse all areas in the memory palace in an orderly manner, and systematically complete the efficient memory learning of all words.

[0073] Further optionally, generating a navigation path includes:

[0074] A navigation generation algorithm based on Q-learning is introduced to generate an optimal navigation path.

[0075] The Q-learning algorithm of this embodiment can maximize the long-term cumulative reward by learning the optimal strategy of state-action pairs, and its reward is closely related to the improvement of the user's learning progress and the increase in the mastery of words. The navigation generation algorithm based on Q-learning reinforcement learning is optimized with the goal of improving the learner's learning progress and the mastery of each word, and generates an optimal navigation path to guide users to efficiently learn the words in the memory palace.

[0076] Further optionally, the introducing of a navigation generation algorithm based on Q-learning to generate an optimal navigation path includes:

[0077] Define a first state space, regard each area in the memory palace as a state, and the first state space includes all possible areas;

[0078] defining a first action space, the first action space containing all possible actions of a user moving from one area to another area;

[0079] A first reward function is set based on the user's learning progress and the degree of mastery of each word. When the user's learning progress is accelerated or the user has a better grasp of the words during the learning process, a positive reward will be given;

[0080] Initialize a policy to decide what action the user should take in a given state;

[0081] Iteratively optimize the strategy through the Q-learning algorithm. In each iteration, guide the user to interact with the memory palace according to the current strategy and collect interaction data, which includes status, action and reward.

[0082] According to the interactive data updating strategy, the algorithm can make more intelligent decisions in the next iteration, thereby more effectively improving the user's learning progress and mastery of words;

[0083] When the strategy converges, that is, the algorithm finds a set of actions that can maximize the long-term cumulative reward under a given state, it generates an optimal navigation path based on this set of optimized strategies. The navigation path is a sequence of actions from the starting area to the target area, which is used to guide users to learn words in the memory palace in the most efficient way.

[0084] Further optionally, in step S103, generating a test sequence for testing the user's word mastery includes:

[0085] Based on the dynamic programming algorithm, a test sequence is generated to test the user's word mastery.

[0086] Further optionally, the method of generating a test sequence for testing the user's word mastery based on a dynamic programming algorithm includes:

[0087] Define a second state space, wherein each test sequence is regarded as a state, each test sequence consists of a set of test questions in a specific order, and the second state space S contains all possible test sequences, so that the algorithm can consider all possible test sequence combinations;

[0088] A second action space is defined, wherein the second action space A represents the action of selecting test questions when generating a test sequence, each action a corresponds to selecting a test question from a test question library and adding it to the test sequence currently being constructed, and the action selection is based on the difficulty level, question type, words tested and their related attributes of the test questions to ensure the comprehensiveness and effectiveness of the test sequence;

[0089] The second reward function R(s, a) is set based on the user's mastery of the overall words in the learning goal, where s∈S represents the current state and a∈A represents the action taken. For each test question, rewards can be given based on the correctness of the user's answer. At the same time, additional rewards are given based on the difficulty level of the test question, thereby ensuring that the algorithm will give priority to those test questions that are most beneficial to the user's learning when generating the test sequence;

[0090] Based on the defined second state space and second action space, the dynamic programming algorithm is used to filter and sort test questions from a wide range of test questions to generate an optimal test sequence to test the user's mastery of words. The algorithm will consider the current state, actions that can be taken, and possible future states and rewards to make the best decision.

[0091] It is understandable that by introducing a test sequence generation method based on a dynamic programming algorithm, test questions can be screened and sorted from a wide range of test question banks to generate an optimal test sequence. This test sequence not only takes into account the difficulty level, question type, and words tested in the test questions, but also optimizes the user's overall mastery of the words in the learning objectives. Therefore, by generating a test sequence based on a dynamic programming algorithm, it is possible to more accurately evaluate and indirectly promote the user's overall mastery of the words, providing strong support for word learning.

[0092] Further optionally, the method of screening and sorting test questions from a wide test question library based on the defined second state space and second action space by a dynamic programming algorithm to generate an optimal test sequence includes:

[0093] Create an empty test sequence as the starting state, and a table for storing the best test sequence and its corresponding reward value;

[0094] For the test sequence currently being constructed, traverse all test questions in the test question bank;

[0095] For each test question, calculate a new state formed after adding it to the current test sequence, and evaluate the reward value of the new state according to the second reward function, wherein the reward value is used to reflect the test effect of the test sequence on the degree of word mastery;

[0096] Filter out the state with the largest reward value from all possible new states as the next optimal state, and store the selected optimal state and reward value in a table;

[0097] When the test sequence reaches the preset length, the search stops and the stored optimal test sequence and its corresponding reward value are returned;

[0098] According to the optimal state and action recorded in the table, the optimal test sequence is generated in reverse order.

[0099] Embodiment 2

[0100] See also Figure 2 The present invention provides a system for testing the degree of word mastery, the system comprising:

[0101] Memory Palace Module: used to build a memory palace, which contains multiple contextual element areas that are closely related to the words to be learned in the learning objectives;

[0102] Memory module: used to guide users to enter each area one by one for interactive practice of word memorization according to the navigation path in the memory palace during the memorization stage;

[0103] A test sequence module is used to generate a test sequence for testing the user's vocabulary mastery, wherein each test question in the test sequence is associated with a context element in the memory palace;

[0104] Test module: used to guide the user to take the test questions in order according to the test sequence during the test phase, and display the test results in real time to evaluate the user's mastery of all the words in the learning objectives.

[0105] Further optionally, the above-mentioned memory palace module is also used for:

[0106] Define a blank memory palace space object, where the memory palace object is a data structure used to represent space;

[0107] Generate multiple areas in the memory palace space and assign a unique identifier to each area, wherein each area corresponds to a learning topic;

[0108] For each area, formulate contextual elements closely related to the corresponding topic and all the words to be learned under the topic, and associate the words to be learned with the contextual elements;

[0109] Generate a navigation path to guide users through all areas to complete efficient memorization and learning of words.

[0110] Further optionally, the above-mentioned memory palace module is also used for:

[0111] A navigation generation algorithm based on Q-learning is introduced to generate an optimal navigation path.

[0112] Further optionally, the above-mentioned memory palace module is also used for:

[0113] Define a first state space, regard each area in the memory palace as a state, and the first state space includes all areas;

[0114] defining a first action space, the first action space comprising all actions of a user moving from one area to another area;

[0115] A first reward function is set based on the user's learning progress and the degree of mastery of each word;

[0116] Initialize a policy to decide what action the user should take in a given state;

[0117] Iteratively optimize the strategy through the Q-learning algorithm. In each iteration, guide the user to interact with the memory palace according to the current strategy and collect interaction data, which includes status, action and reward.

[0118] updating a strategy according to the interaction data;

[0119] When the strategy converges, an optimal navigation path is generated according to the optimized strategy, where the navigation path is a sequence of actions from the starting area to the target area.

[0120] Further optionally, the test sequence module is also used for:

[0121] Based on the dynamic programming algorithm, a test sequence is generated to test the user's word mastery.

[0122] Further optionally, the test sequence module is also used for:

[0123] A second state space is defined, wherein each test sequence is regarded as a state, each test sequence is composed of a set of test questions in a specific order, and the second state space S contains all the test sequences;

[0124] A second action space is defined, wherein the second action space A represents the action of selecting test questions when generating a test sequence, each action a corresponds to selecting a test question from a test question library and adding it to the test sequence currently being constructed, and the action is selected based on the difficulty level, question type, words tested and related attributes of each test question;

[0125] The second reward function R(s, a) is set based on the user's mastery of the overall words in the learning goal, where s∈S represents the current state and a∈A represents the action taken;

[0126] Based on the defined second state space and second action space, the test questions are screened and sorted from a wide test question bank through a dynamic programming algorithm to generate an optimal test sequence for testing the user's mastery of words.

[0127] Further optionally, the test sequence module is also used for:

[0128] Create an empty test sequence as the starting state, and a table for storing the best test sequence and its corresponding reward value;

[0129] For the test sequence currently being constructed, traverse all test questions in the test question bank;

[0130] For each test question, calculate a new state formed after adding it to the current test sequence, and evaluate the reward value of the new state according to the second reward function, wherein the reward value is used to reflect the test effect of the test sequence on the degree of word mastery;

[0131] Filter out the state with the largest reward value from all potential new states as the next optimal state, and store the selected optimal state and reward value in a table;

[0132] When the test sequence reaches the preset length, the search stops and the stored optimal test sequence and its corresponding reward value are returned;

[0133] According to the optimal state and action recorded in the table, the optimal test sequence is generated in reverse order.

[0134] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for testing the degree of word mastery, characterized in that: The method comprises: Build a memory palace that contains multiple contextual elements that are closely related to the words to be learned in the learning objectives; In the memorization stage, according to the navigation path in the memory palace, the user is guided to enter each area one by one to conduct interactive exercises on word memorization; Generate a test sequence for testing the user's vocabulary mastery, wherein each test question in the test sequence is associated with a context element in the memory palace; During the test phase, the user is guided to take the test questions in order according to the test sequence, and the test results are displayed in real time to evaluate the user's mastery of all the words in the learning objectives.

2. The method for testing the degree of word mastery according to claim 1, characterized in that: The construction of a memory palace includes: Define a blank memory palace space object, where the memory palace object is a data structure used to represent space; Generate multiple areas in the memory palace space and assign a unique identifier to each area, wherein each area corresponds to a learning topic; For each area, formulate contextual elements closely related to the corresponding topic and all the words to be learned under the topic, and associate the words to be learned with the contextual elements; Generate a navigation path to guide users through all areas to complete efficient memorization and learning of words.

3. The method for testing the degree of word mastery according to claim 2, characterized in that: The generating of a navigation path comprises: A navigation generation algorithm based on Q-learning is introduced to generate an optimal navigation path.

4. The method for testing the degree of word mastery according to claim 3, characterized in that: The introduction of the Q-learning-based navigation generation algorithm to generate an optimal navigation path includes: Define a first state space, regard each area in the memory palace as a state, and the first state space includes all areas; defining a first action space, the first action space comprising all actions of a user moving from one area to another area; A first reward function is set based on the user's learning progress and the degree of mastery of each word; Initialize a policy to decide what action the user should take in a given state; Iteratively optimize the strategy through the Q-learning algorithm. In each iteration, guide the user to interact with the memory palace according to the current strategy and collect interaction data, which includes status, action and reward. updating a strategy according to the interaction data; When the strategy converges, an optimal navigation path is generated according to the optimized strategy, where the navigation path is a sequence of actions from the starting area to the target area.

5. The method for testing the degree of word mastery according to claim 1, characterized in that: The generating of a test sequence for testing the user's word mastery comprises: Based on the dynamic programming algorithm, a test sequence is generated to test the user's word mastery.

6. The method for testing the degree of word mastery according to claim 5, characterized in that: The method generates a test sequence for testing the user's word mastery based on a dynamic programming algorithm, including: A second state space is defined, wherein each test sequence is regarded as a state, each test sequence is composed of a set of test questions in a specific order, and the second state space S contains all the test sequences; A second action space is defined, wherein the second action space A represents the action of selecting test questions when generating a test sequence, each action a corresponds to selecting a test question from a test question library and adding it to the test sequence currently being constructed, and the action is selected based on the difficulty level, question type, words tested and related attributes of each test question; The second reward function R(s, a) is set based on the user's mastery of the overall words in the learning goal, where s∈S represents the current state and a∈A represents the action taken; Based on the defined second state space and second action space, the test questions are screened and sorted from a wide test question bank through a dynamic programming algorithm to generate an optimal test sequence for testing the user's mastery of words.

7. The method for testing the degree of word mastery according to claim 6, characterized in that: The method of screening and sorting test questions from a wide test question bank based on the defined second state space and second action space by a dynamic programming algorithm to generate an optimal test sequence includes: Create an empty test sequence as the starting state, and a table for storing the best test sequence and its corresponding reward value; For the test sequence currently being constructed, traverse all test questions in the test question bank; For each test question, calculate a new state formed after adding it to the current test sequence, and evaluate the reward value of the new state according to the second reward function, wherein the reward value is used to reflect the test effect of the test sequence on the degree of word mastery; Filter out the state with the largest reward value from all potential new states as the next optimal state, and store the selected optimal state and reward value in a table; When the test sequence reaches the preset length, the search stops and the stored optimal test sequence and its corresponding reward value are returned; According to the optimal state and action recorded in the table, the optimal test sequence is generated in reverse order.

8. The method for testing the degree of word mastery according to claim 2, characterized in that: In the memorization stage, according to the navigation path in the memory palace, the user is guided to enter each area one by one to perform interactive exercises on word memorization, in the steps: The interactive exercises include dragging the words to be learned onto the correct objects or selecting words in the context to fill in the blanks.

9. A system for testing the degree of word mastery, characterized in that: The system comprises: Memory Palace Module: used to build a memory palace, which contains multiple contextual element areas that are closely related to the words to be learned in the learning objectives; Memory module: used to guide users to enter each area one by one for interactive practice of word memorization according to the navigation path in the memory palace during the memorization stage; A test sequence module is used to generate a test sequence for testing the user's vocabulary mastery, wherein each test question in the test sequence is associated with a context element in the memory palace; Test module: used to guide the user to take the test questions in order according to the test sequence during the test phase, and display the test results in real time to evaluate the user's mastery of all the words in the learning objectives.

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