Knowledge point analysis method and device, electronic equipment and storage medium

Abstract

Embodiments of the invention relate to a knowledge point analysis method and apparatus, an electronic device and a storage medium. The method comprises the steps of obtaining a test question identifier list corresponding to each knowledge point in a target test paper; selecting an examinee from all the examinees as a target examinee, and determining a first score rate of all the examinees including the target examinee at each knowledge point based on the test question identifier list corresponding to each knowledge point; determining a first evaluation level of the target examinee at each knowledge point by comparing the first score rates of the target examinee and all the examinees at each knowledge point; determining the knowledge points of which the first evaluation levels are preset levels as weak knowledge points of the target examinee; according to the method, the answering condition in the test paper of the students can be automatically analyzed, and the mastering degree of each student on each knowledge point can be identified, so that the students or teachers can formulate effective personalized learning plans and teaching strategies.

Description

Technical Field

[0001] The present invention relates to the field of computer-assisted education technology, and in particular to a knowledge point analysis method, device, electronic equipment and storage medium. Background Art

[0002] In modern education, examinations are an important means of evaluating students' learning outcomes and learning abilities. With the popularity of online education and electronic examinations, how to efficiently analyze examination results in order to provide students with personalized learning feedback has become an important research direction in the field of educational technology.

[0003] Traditional test analysis systems usually focus on basic statistical data, such as average scores, pass rates, score distribution, difficulty, discrimination, etc. They lack in-depth analysis of each candidate's mastery of knowledge points and provide insufficient support for personalized feedback, resulting in students being unable to obtain targeted learning suggestions. Summary of the invention

[0004] The present invention provides a knowledge point analysis method, device, electronic device and storage medium to solve the technical problem that the prior art lacks personalized analysis of students' knowledge point mastery.

[0005] In a first aspect, the present invention provides a knowledge point analysis method, including: obtaining a list of test question identifiers corresponding to each knowledge point in a target test paper; selecting a candidate from all candidates as a target candidate, and based on the list of test question identifiers corresponding to each knowledge point, determining a first score rate of all candidates including the target candidate at each knowledge point; determining a first evaluation level of the target candidate at each knowledge point by comparing the first score rate of the target candidate with that of all candidates at each knowledge point; and determining the knowledge points whose first evaluation level is a preset level as weak knowledge points of the target candidate.

[0006] In some embodiments, obtaining a list of question identifications corresponding to each knowledge point in a target test paper includes: obtaining test questions in the target test paper, and determining the question identifications corresponding to the test questions based on a preset question table; determining the knowledge point identifications corresponding to each question identification based on a preset question-knowledge point relationship table; determining the knowledge point corresponding to each knowledge point identification based on a preset knowledge point table; determining a list of question identifications corresponding to each knowledge point based on the knowledge point identifications corresponding to each question identification and the knowledge points corresponding to each knowledge point identification.

[0007] In some embodiments, the method of determining the first score rate of all candidates including the target candidate at each knowledge point based on the list of test question identifications corresponding to each knowledge point includes: determining the total number of questions corresponding to each knowledge point according to the list of test question identifications corresponding to each knowledge point; determining the number of correct answers or incorrect answers to each candidate at each knowledge point; determining the first score rate of each candidate at each knowledge point according to the ratio of the number of correct answers to the total number of questions or the ratio of the number of incorrect answers to the total number of questions.

[0008] In some embodiments, the first evaluation level of the target candidate at each knowledge point is determined by comparing the first score rate of the target candidate with that of all candidates at each knowledge point, including: for each knowledge point, determining the number of candidates whose first score rate does not exceed that of the target candidate; and determining the first evaluation level of the target candidate at the corresponding knowledge point based on the ratio of the number of candidates to the total number of candidates.

[0009] In some embodiments, after determining that the knowledge point with the first evaluation level as a preset level is a weak knowledge point of the target candidate, it also includes at least one of the following: when it is determined that a weak knowledge point exists, outputting the test questions in the target test paper corresponding to the weak knowledge point of the target candidate; when it is determined that a weak knowledge point exists, determining the overall score rate based on the average first score rate of all candidates on the weak knowledge points.

[0010] In some embodiments, the method also includes: obtaining test question types in the target test paper; determining the second score rate of all candidates including the target candidate on each test question type; and determining the second evaluation level of the target candidate on each test question type by comparing the second score rate of the target candidate with that of all candidates on each test question type.

[0011] In some embodiments, the method further includes: outputting a personalized analysis report for the target examinee, the personalized analysis report including a first evaluation level for each knowledge point and a second evaluation level for each test question type.

[0012] In a second aspect, the present invention provides a knowledge point analysis device, comprising: an acquisition module for acquiring a list of test question identifications corresponding to each knowledge point in a target test paper; a processing module for selecting a candidate from all candidates as a target candidate, and determining a first score rate of all candidates including the target candidate at each knowledge point based on the list of test question identifications corresponding to each knowledge point; an evaluation module for determining a first evaluation level of the target candidate at each knowledge point by comparing the first score rate of the target candidate with that of all candidates at each knowledge point; a determination module for determining a knowledge point whose first evaluation level is a preset level as a weak knowledge point of the target candidate.

[0013] In a third aspect, the present invention provides an electronic device comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; the memory is used to store computer programs; and the processor is used to implement the steps of the knowledge point analysis method described in any one of the first aspects when executing the program stored in the memory.

[0014] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the knowledge point analysis method described in any one of the first aspects.

[0015] The knowledge point analysis method, device, electronic device and storage medium provided in the embodiments of the present invention can automatically analyze the answers in students' test papers and identify the degree of mastery of each student on each knowledge point, so that students or teachers can formulate effective personalized learning plans and teaching strategies. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0018] Figure 1 A schematic diagram of a flow chart of a knowledge point analysis method provided by an embodiment of the present invention;

[0019] Figure 2 A schematic diagram of a test question table, a knowledge point table, and a test question and knowledge point relationship table provided in an embodiment of the present invention;

[0020] Figure 3 A schematic diagram of a flow chart of another knowledge point analysis method provided by an embodiment of the present invention;

[0021] Figure 4 A schematic diagram of a flow chart of another knowledge point analysis method provided by an embodiment of the present invention;

[0022] Figure 5a is a detailed flow chart of step S402;

[0023] Figure 5b A detailed flow chart summarizing the knowledge points in step S403;

[0024] Figure 5cA detailed flow chart of the knowledge point analysis in step S403;

[0025] Figure 5d is a detailed flow chart of step S404;

[0026] Figure 6 A schematic diagram of the structure of a knowledge point analysis device provided by an embodiment of the present invention;

[0027] Figure 7 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] Traditional test analysis systems lack in-depth knowledge point analysis and personalized feedback on individual student answers. Specifically, existing systems can only provide macroscopic statistical data, but cannot accurately understand the mastery of specific knowledge points of each student, which makes it difficult for teachers and students to accurately understand the strengths and weaknesses of students in various knowledge points, and thus it is impossible to formulate effective personalized learning plans and teaching strategies.

[0030] In response to the above technical problems, the technical concept of the present invention is to automatically analyze the answers in students' test papers and identify each student's mastery of each knowledge point. This not only helps students to self-assess and adjust their learning strategies, but also provides teachers with targeted teaching feedback, thereby effectively improving teaching effectiveness and students' academic performance.

[0031] Figure 1 A schematic diagram of a knowledge point analysis method provided by an embodiment of the present invention. Figure 1 As shown, the method includes:

[0032] Step S101, obtaining a list of test question identifiers corresponding to each knowledge point in the target test paper.

[0033] Specifically, the target test paper can be regarded as a test paper to be analyzed, and the question identifier can be understood as a unique identifier of the question, such as a question ID; a test paper usually covers multiple knowledge points, and each knowledge point corresponds to at least one question; the purpose of this step is to summarize the knowledge points involved in the target test paper and the questions corresponding to each knowledge point.

[0034] In some embodiments, step S101 includes: obtaining test questions in the target test paper, and determining the test question identifiers corresponding to the test questions based on a preset test question table; determining the knowledge point identifiers corresponding to each test question identifier based on a preset test question and knowledge point relationship table; determining the knowledge points corresponding to each knowledge point identifier based on a preset knowledge point table; and determining a list of test question identifiers corresponding to each knowledge point based on the knowledge point identifiers corresponding to each test question identifier and the knowledge points corresponding to each knowledge point identifier.

[0035] Specifically, the question table (qb_question), knowledge point table (qb_knowledge) and question and knowledge point relationship table (qb_question_knowledge) are predefined. The question table stores all the questions (string content), and each question has a unique question ID (int id). The knowledge point table stores all the knowledge points (string name), and each knowledge point also has a unique knowledge point ID (int id). The question and knowledge point relationship table stores the question ID (int question_id) and the knowledge point ID (int knowledge_id), reflecting the relationship between the question and the knowledge point. Figure 2 A schematic diagram of a test question table, a knowledge point table, and a test question and knowledge point relationship table provided in an embodiment of the present invention. In this embodiment, the above three tables are used to summarize the knowledge points involved in the target test paper and the test questions corresponding to each knowledge point. The specific process is as follows:

[0036] First, obtain the test paper information, that is, obtain the test questions used by the candidates in this test, query the test question table (qb_question), and extract all the test question IDs in this test paper; then, according to each test question ID, query the test question and knowledge point relationship table (qb_question_knowledge) to determine the knowledge point ID corresponding to each test question ID; then query the knowledge point table (qb_knowledge) through the knowledge point ID to obtain the specific information of each knowledge point; in this way, you can find the corresponding knowledge point for each question in the test paper, and summarize the knowledge points of all the questions to obtain all the knowledge points covered by the entire test paper, and then sort out the test question ID list corresponding to each knowledge point.

[0037] Step S102: Select one examinee from all examinees as a target examinee, and determine the first score rate of all examinees including the target examinee at each knowledge point based on the list of test question identifiers corresponding to each knowledge point.

[0038] Specifically, for target candidates who need personalized analysis, the score of the target candidate on each knowledge point is determined based on the target candidate's answer record, and at the same time, the answer records of all candidates except the target candidate are obtained to determine the score of each of the other candidates on each knowledge point.

[0039] In some embodiments, the step S102 determines the first score rate of all candidates including the target candidate at each knowledge point based on the list of test question identifications corresponding to each knowledge point, including: determining the total number of questions corresponding to each knowledge point according to the list of test question identifications corresponding to each knowledge point; determining the number of correct answers or incorrect answers to each candidate at each knowledge point; determining the first score rate of each candidate at each knowledge point according to the ratio of the number of correct answers to the total number of questions or the ratio of the number of incorrect answers to the total number of questions.

[0040] Specifically, based on the list of test question IDs corresponding to each knowledge point, the total number of questions for each knowledge point can be determined; for each candidate, including the target candidate, the number of correct answers or incorrect answers at the corresponding knowledge point (the total number of questions minus the number of correct answers) is obtained, and the score rate of each candidate at each knowledge point is determined based on the ratio of the number of correct answers to the total number of questions, or the ratio of the number of incorrect answers to the total number of questions.

[0041] Step S103: Determine the first evaluation level of the target candidate at each knowledge point by comparing the first score rate of the target candidate with that of all candidates at each knowledge point.

[0042] Specifically, by comparing the target candidate's score rate with that of each other candidate on each knowledge point, the target candidate's mastery level on each knowledge point is evaluated.

[0043] In some embodiments, step S103 includes: for each knowledge point, determining the number of candidates among all candidates whose first score rate does not exceed that of the target candidate; and determining the first evaluation level of the target candidate at the corresponding knowledge point based on the ratio of the number of candidates to the total number of candidates.

[0044] Specifically, the target examinee's score rate for each knowledge point is traversed, and the number of times the score rate exceeds the score rate of the current knowledge point in the test is calculated. The number of times the score rate exceeds the total number is divided by the evaluation level. For example, if the evaluation level is 85%, it can be considered that the target examinee has mastered the knowledge point more than 85% of the people. For example, an evaluation level division is shown in Table 1:

[0045] Table 1

[0046] excellent More than 85% good 75％～85％ generally 60％～75％ Need to be strengthened 50％～60％ Urgent need to strengthen 0～50％

[0047] Step S104: Determine that the knowledge points whose first evaluation level is a preset level are weak knowledge points of the target examinee.

[0048] Specifically, the knowledge points with evaluation levels of "need to be strengthened" or "urgently need to be strengthened" are regarded as the weak knowledge points of the target examinees. Preferably, an analysis report on the mastery of each knowledge point for the target examinees can be output, so that the target examinees themselves or teachers can formulate targeted learning strategies for the target examinees.

[0049] In some embodiments, after step S104, at least one of the following items is also included: when it is determined that weak knowledge points exist, the test questions in the target test paper corresponding to the weak knowledge points of the target examinees are output; when it is determined that weak knowledge points exist, the overall score rate is determined based on the average first score rate of all examinees in the weak knowledge points.

[0050] Specifically, after screening out all knowledge points marked as "needs to be strengthened" or "urgently needs to be strengthened" from the knowledge point analysis results and marking these knowledge points as weak knowledge points, it is necessary to further check the existence of weak knowledge points, that is, to determine whether there are weak knowledge points (for example, all candidates including the target candidate have a good grasp of a certain knowledge point, then there is a situation where the target candidate's evaluation grade is rated as a lower grade, but the target candidate actually has a good grasp of the knowledge point). If there are no weak knowledge points, then this embodiment is terminated; if it is determined that there are weak knowledge points, then the test questions related to the weak knowledge points are identified, that is, for each weak knowledge point, all the test question IDs involved in this exam are found, and the test questions corresponding to these test question IDs are recorded for subsequent analysis. Furthermore, teachers can also calculate the overall score rate of all candidates. The specific process is as follows: for each test question ID related to a weak knowledge point, find all candidates who answered the test in this test, calculate and record the number of people who answered each test question, and the number of people who answered the test is the total number of people who participated in the test; then calculate the overall score rate, that is, for each candidate who participated in the test, calculate their score rate on the current weak knowledge point, and determine the overall score rate by summarizing the average score rate of all candidates on this knowledge point. If the overall score rate is low, teachers can carry out knowledge point teaching for all students. If the overall score rate is high, teachers can carry out knowledge point teaching only for individual students.

[0051] The knowledge point analysis method provided in this embodiment can automatically analyze the answers in the student test papers and identify the degree of mastery of each student on each knowledge point. That is, by introducing evaluation grades, students or teachers can clearly understand their own degree of mastery of the knowledge point relative to the level of all candidates in this exam, so that students or teachers can formulate effective personalized learning plans and teaching strategies.

[0052] Based on the above embodiments, Figure 3FIG. 1 is a flow chart of another knowledge point analysis method provided by an embodiment of the present invention. Figure 3 As shown, the method further comprises the following steps:

[0053] Step S301, obtaining the test question types in the target test paper.

[0054] Specifically, in the design of the question bank, the test questions are divided into two categories: subjective questions and objective questions. Subjective questions include fill-in-the-blank questions, definition of terms, short-answer questions, and essay questions. The characteristic of subjective questions is that they need to be manually graded; objective questions include A1-type questions, A2-type questions, A3-type questions, A4-type questions, B1-type questions, multiple-choice questions, true-or-false questions, etc. The characteristic of objective questions is that the answers are fixed and the program can automatically grade them. The test question type in this step refers to the question type of objective questions. For each question type, an analysis object is created and basic attributes (such as candidate ID, question type ID, and question type name) are set.

[0055] Step S302: Determine the second score rate of all examinees including the target examinee in each test question type.

[0056] Specifically, the test paper information of each candidate is obtained, that is, the test paper ID and candidate ID are extracted from the candidate's answer record, and the detailed information of the test paper and all test questions are obtained according to the test paper ID, and then the correct answer is determined, that is, the candidate's answer is compared with the correct answer in the test paper, and the set of test question IDs answered correctly by the candidate is identified; then, each question type is analyzed one by one, that is, for each question type, all test questions of this question type are identified, the total number of questions of this question type is calculated, and the number of questions answered correctly by the candidate in this question type is determined (how many of the test question IDs of the question type are in the set of test question IDs answered correctly by the candidate); the number of errors in this question type is calculated (the total number of questions minus the number of correct answers), and finally the accuracy rate is calculated (the number of correct answers divided by the total number of questions) to obtain the score rate of the candidate in each test question type.

[0057] Step S303: Determine the second evaluation level of the target candidate on each test question type by comparing the second score rate of the target candidate with that of all candidates on each test question type.

[0058] Specifically, the question type analysis results of each candidate are traversed, and for each question type, the candidate's score rate is obtained, and it is calculated how many other candidates the candidate's score rate in this question type exceeds, the number of excess numbers is converted into a percentage, the candidate's performance level in this question type is evaluated, and the results are recorded.

[0059] In some embodiments, the method further includes: outputting a personalized analysis report for the target examinee, the personalized analysis report including a first evaluation grade for each knowledge point and a second evaluation grade for each test question type. Specifically, a function of generating a personalized analysis report for each examinee can be provided.

[0060] Based on the above-mentioned embodiment, in addition to conducting an in-depth analysis of each candidate's mastery of knowledge points, this embodiment also conducts a personalized analysis of each candidate's answer to each question type, providing students or teachers with more comprehensive personalized learning report feedback.

[0061] Figure 4 A flow chart of another knowledge point analysis method provided by an embodiment of the present invention is as follows: Figure 4 As shown, the following steps are included:

[0062] Step S401, basic information analysis: total number of candidates, average score, highest score and ranking of the target candidate among all candidates.

[0063] Step S402, question type analysis: find all objective question types on the target test paper, and analyze the total number of questions of each question type and the score rate and evaluation level of all candidates including the target candidate on each question type.

[0064] Step S403, knowledge point analysis: Find all knowledge points on the target test paper, and analyze the total number of questions for each knowledge point and the score rate and evaluation level of all candidates including the target candidate on each knowledge point.

[0065] Step S404, weak knowledge point analysis: a more detailed analysis is performed on the knowledge points whose evaluation levels are "need to be strengthened" or "urgently need to be strengthened".

[0066] Step S405: store the analysis results of the target examinee into the database.

[0067] Step S406: download a personalized analysis report for the target candidate.

[0068] In this embodiment, routine basic information analysis is first performed, such as counting the number of all candidates, the test scores, average scores, and highest scores of each candidate, and determining the ranking of the target candidate and the gap between the target candidate's score and the average score and the highest score.

[0069] Then, question type analysis is performed. In some embodiments, step S402 includes the following steps:

[0070] (1) Collect answer data: Obtain the answer records of all candidates based on the test ID.

[0071] (2) Analyze the question type for each candidate: For each candidate, perform the following specific steps to analyze the question type:

[0072] ① Obtain test paper information: Extract the test paper ID and candidate ID from the candidate's answer record, and obtain the test paper's detailed information and all test questions based on the test paper ID.

[0073] ② Determine the correct answer: Compare the candidate's answer with the correct answer in the test paper, and identify the set of question IDs to which the candidate answered correctly.

[0074] ③Extract objective question types: extract all objective question types information from the test questions.

[0075] ④ Initialize the analysis result set: create an analysis object for each question type and set basic properties (such as candidate ID, question type ID and question type name).

[0076] ⑤ Analyze each question type one by one: For each question type, identify all test questions of that question type and calculate the total number of questions of that question type; determine the number of questions that the examinee answered correctly in that question type (how many of the question IDs of that question type are in the set of question IDs that the examinee answered correctly); calculate the number of errors in that question type (the total number of questions minus the number of correct answers); calculate the accuracy rate (the number of correct answers divided by the total number of questions) and record it in the analysis object.

[0077] (3) Evaluation grade calculation: Traverse the question type analysis results of each candidate. For each question type, obtain the candidate's correct rate, calculate how many other candidates the candidate's correct rate exceeds in this question type, convert the number of excess candidates into a percentage, evaluate the candidate's performance level in this question type, and record the result.

[0078] Figure 5a is a detailed flow chart of step S402, and the corresponding pseudo code example is as follows:

[0079]

[0080]

[0081]

[0082] Then, knowledge point analysis is performed. In some embodiments, step S403 includes the following steps:

[0083] (1) Knowledge point summary, including the following steps:

[0084] ① Get the test paper information: Get the test paper used by the examinee in this exam, and extract the IDs of all test questions in the test paper.

[0085] ② Find the knowledge point ID: According to the ID of each test question, query the "Test Question and Knowledge Point Relationship Table (qb_question_knowledge)" to determine the knowledge point ID corresponding to each test question.

[0086] ③ Get the details of knowledge points: query the knowledge point table (qb_knowledge) through the knowledge point ID to obtain the specific knowledge point information involved in each question.

[0087] ④ Summarize knowledge points: Find the corresponding knowledge point for each question in the test paper, and summarize the knowledge points of all questions to obtain all the knowledge points covered in the entire test paper.

[0088] Figure 5b A detailed flowchart summarizing the knowledge points in step S403, and the corresponding pseudo code example is as follows:

[0089] / / Get all the knowledge points of the candidate's test paper

[0090]

[0091]

[0092]

[0093] (2) Knowledge point analysis

[0094] ① Obtain the test paper information of the candidates: retrieve and obtain the test paper information of the candidates in this test.

[0095] ② Check whether the test paper exists: Determine whether the test paper exists. If the test paper does not exist, the program ends.

[0096] ③ Find all the knowledge points involved in this test paper: identify and extract all the knowledge points involved in the test paper.

[0097] ④ Calculate the test question IDs contained in each knowledge point: Determine the list of test question IDs contained in each knowledge point.

[0098] ⑤Summarize all the test question IDs answered correctly by the candidates: count all the test question IDs answered correctly by the candidates in the exam.

[0099] ⑥ Calculate the total number of questions for each knowledge point: calculate the total number of test questions corresponding to each knowledge point.

[0100] ⑦ Calculate the number of correct answers given by candidates for each knowledge point: Count the number of questions answered correctly by candidates in each knowledge point.

[0101] ⑧Calculate the number of wrong questions answered by candidates in each knowledge point: count the number of questions answered incorrectly by candidates in each knowledge point.

[0102] ⑨Calculate the score rate for each knowledge point: Calculate the score rate for each knowledge point based on the number of correct questions and the number of incorrect questions.

[0103] ⑩ Calculate the evaluation level of each knowledge point: After the knowledge point analysis of all candidates is completed, calculate the evaluation level of each candidate on each knowledge point. The calculation rule of the evaluation level is: based on the candidate's score rate on a certain knowledge point in the current exam, evaluate how many percent of other candidates he or she exceeds.

[0104] Figure 5c A detailed flowchart of the knowledge point analysis in step S403, and the corresponding pseudo code example is as follows:

[0105]

[0106]

[0107]

[0108]

[0109] Then, weak knowledge point analysis is performed. In some embodiments, step S404 includes the following steps:

[0110] (1) Mark weak knowledge points: Filter out all knowledge points marked as "needs to be strengthened" or "urgently needs to be strengthened" from the knowledge point analysis results, and mark these knowledge points as weak knowledge points.

[0111] (2) Check whether weak knowledge points exist: Determine whether weak knowledge points exist. If no weak knowledge points exist, end the analysis process.

[0112] (3) Identify test questions related to weak knowledge points: For each weak knowledge point, find all the test question IDs involved in this exam and record these test question IDs for subsequent analysis.

[0113] (4) Count the number of candidates who answered the questions: For each question ID related to a weak knowledge point, find all candidates who answered the questions in this exam, calculate and record the number of candidates who answered each question. The number of candidates who answered the questions is the total number of candidates who participated in the test.

[0114] (5) Calculate the overall score rate: For each candidate taking the exam, calculate his / her score rate on the current weak knowledge point. By summing up the scores of all candidates on this knowledge point, calculate the overall score rate, that is, the average score rate of all candidates.

[0115] Figure 5d is a detailed flow chart of step S404, and its corresponding pseudo code example is as follows:

[0116]

[0117]

[0118]

[0119] Then, the question type analysis results and knowledge point analysis results for each candidate are stored in the database.

[0120] Finally, each test analysis data that has not generated a download link in the database is obtained, and a PDF file is generated for it, which is uploaded to the file server to obtain a download link for the test analysis PDF; the examinee or teacher downloads the test analysis PDF by clicking on the link.

[0121] In summary, this embodiment consists of three parts: question type analysis, knowledge point analysis, and weak knowledge point analysis. It goes deeper layer by layer, provides an analysis perspective from breadth to depth, and provides a comprehensive assessment of the examinee's ability. It can not only go deep into the level of each knowledge point, and count the total number of questions and score rate of each knowledge point, but also introduces an evaluation level, so that students can clearly understand their mastery of this knowledge point relative to the level of all examinees in this exam. For example, "excellent" means that the mastery of this knowledge point exceeds that of more than 85% of the examinees. This embodiment provides students with clear and detailed test feedback, helps them identify weak links in learning, helps improve students' learning effects, provides reference information for teaching work, helps teachers quickly understand examinees' mastery of question types and knowledge points, and helps the implementation of personalized education.

[0122] Figure 6 Schematic diagram of the structure of a knowledge point analysis device provided by an embodiment of the present invention. Figure 6 As shown, the device comprises:

[0123] An acquisition module 601 is used to acquire a list of test question identifiers corresponding to each knowledge point in the target test paper;

[0124] Processing module 602, for selecting a candidate from all candidates as a target candidate, and determining the first score rate of all candidates including the target candidate on each knowledge point based on the list of test question identifiers corresponding to each knowledge point;

[0125] Evaluation module 603, used to determine the first evaluation level of the target candidate at each knowledge point by comparing the first score rate of the target candidate with that of all candidates at each knowledge point;

[0126] The determination module 604 is used to determine that the knowledge points whose first evaluation level is a preset level are weak knowledge points of the target examinee.

[0127] In some embodiments, the acquisition module 601 is specifically used to:

[0128] Obtaining test questions in the target test paper, and determining test question identifiers corresponding to the test questions based on a preset test question table;

[0129] Determine the knowledge point identifier corresponding to each test question identifier based on a preset test question and knowledge point relationship table;

[0130] Determine the knowledge point corresponding to each knowledge point identifier based on a preset knowledge point table;

[0131] According to the knowledge point identifier corresponding to each test question identifier and the knowledge point corresponding to each knowledge point identifier, a list of test question identifiers corresponding to each knowledge point is determined.

[0132] In some embodiments, the processing module 602 is specifically configured to:

[0133] According to the list of test question identifiers corresponding to each knowledge point, determine the total number of questions corresponding to each knowledge point;

[0134] Determine the number of correct answers or incorrect answers for each candidate at each knowledge point;

[0135] The first score rate of each candidate in each knowledge point is determined based on the total number of test questions and the correct answer rate or the incorrect answer rate.

[0136] In some embodiments, the evaluation module 603 is specifically used to:

[0137] For each knowledge point, determine the number of candidates who do not exceed the first score rate of the target candidates among all candidates;

[0138] Based on the ratio of the number of people to the total number of all candidates, the first evaluation level of the target candidates in the corresponding knowledge points is determined.

[0139] In some embodiments, the apparatus further includes an output module 605, wherein the output module 605 is configured to:

[0140] When it is determined that weak knowledge points exist, the test questions corresponding to the weak knowledge points of the target examinees in the target test paper are output;

[0141] When it is determined that weak knowledge points exist, the overall score rate is determined based on the average first score rate of all candidates in the weak knowledge points.

[0142] In some embodiments, the acquisition module 601 is further used to: acquire the question types in the target test paper;

[0143] The processing module 602 is also used to: determine the second score rate of all examinees including the target examinee in each test question type;

[0144] The evaluation module 603 is also used to determine the second evaluation level of the target candidate on each test question type by comparing the second score rate of the target candidate with that of all candidates on each test question type.

[0145] In some embodiments, the output module 605 is further used to: output a personalized analysis report for the target examinee, wherein the personalized analysis report includes a first evaluation level for each knowledge point and a second evaluation level for each test question type.

[0146] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process and corresponding beneficial effects of the knowledge point analysis device described above can refer to the corresponding process in the aforementioned method example, and will not be repeated here.

[0147] Figure 7 A schematic diagram of the hardware structure of an electronic device provided by an embodiment of the present invention is shown in FIG. Figure 7 As shown, the electronic device includes: a processor 701, a communication interface 702, a memory 703 and a communication bus 704, wherein the processor 701, the communication interface 702, and the memory 703 communicate with each other through the communication bus 704.

[0148] Memory 703, used for storing computer programs;

[0149] In one embodiment of the present application, the processor 701 is used to implement the steps of the knowledge point analysis method provided by any of the aforementioned method embodiments when executing the program stored in the memory 703.

[0150] The implementation principle and technical effects of the electronic device provided in the embodiment of the present application are similar to those of the above embodiment and will not be repeated here.

[0151] The above-mentioned memory 703 can be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read-only memory), an EPROM, a hard disk or a ROM. The memory 703 has a storage space for program codes for executing any method steps in the above-mentioned method. For example, the storage space for program codes may include various program codes for implementing the various steps in the above method respectively. These program codes can be read from or written into one or more computer program products. These computer program products include program code carriers such as hard disks, compact disks (CDs), memory cards or floppy disks. Such computer program products are usually portable or fixed storage units. The storage unit may have a storage segment or storage space arranged similarly to the memory 703 in the above-mentioned electronic device. The program code can be compressed, for example, in an appropriate form. Generally, the storage unit includes a program for executing the method steps according to the embodiment of the present application, that is, a code that can be read by a processor such as 701, which, when run by an electronic device, causes the electronic device to execute the various steps in the method described above.

[0152] The embodiment of the present application further provides a computer-readable storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the knowledge point analysis method described above are implemented.

[0153] The computer-readable storage medium may be included in the device / apparatus described in the above embodiment; or it may exist independently without being assembled into the device / apparatus. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present application is implemented.

[0154] According to an embodiment of the present application, the computer-readable storage medium may be a non-volatile computer-readable storage medium, for example, may include but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0155] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0156] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A knowledge point analysis method, characterized in that: include: Get the list of test question identifiers corresponding to each knowledge point in the target test paper; Selecting one examinee from all examinees as a target examinee, and determining the first score rate of all examinees including the target examinee on each knowledge point based on the list of test question identifiers corresponding to each knowledge point; By comparing the first score rate of the target examinee with that of all examinees in each knowledge point, the first evaluation level of the target examinee in each knowledge point is determined; The knowledge points whose first evaluation level is a preset level are determined to be weak knowledge points of the target examinees.

2. The method according to claim 1, characterized in that The step of obtaining a list of test question identifiers corresponding to each knowledge point in the target test paper includes: Obtaining test questions in the target test paper, and determining test question identifiers corresponding to the test questions based on a preset test question table; Determine the knowledge point identifier corresponding to each test question identifier based on a preset test question and knowledge point relationship table; Determine the knowledge point corresponding to each knowledge point identifier based on a preset knowledge point table; According to the knowledge point identifier corresponding to each test question identifier and the knowledge point corresponding to each knowledge point identifier, a list of test question identifiers corresponding to each knowledge point is determined.

3. The method according to claim 1, characterized in that The determining of the first score rate of each knowledge point for all examinees including the target examinee based on the list of test question identifiers corresponding to each knowledge point comprises: According to the list of test question identifiers corresponding to each knowledge point, determine the total number of questions corresponding to each knowledge point; Determine the number of correct answers or incorrect answers for each candidate at each knowledge point; The first score rate of each candidate in each knowledge point is determined based on the ratio of the number of correctly answered questions to the total number of questions, or the ratio of the number of incorrectly answered questions to the total number of questions.

4. The method according to claim 1, characterized in that: Determining the first evaluation level of the target candidate at each knowledge point by comparing the first score rate of the target candidate with that of all candidates at each knowledge point includes: For each knowledge point, determine the number of candidates who do not exceed the first score rate of the target candidates among all candidates; Based on the ratio of the number of people to the total number of all candidates, the first evaluation level of the target candidates in the corresponding knowledge points is determined.

5. The method according to any one of claims 1 to 4, characterized in that: After determining that the knowledge point with the first evaluation level being the preset level is a weak knowledge point of the target examinee, the method further includes at least one of the following: When it is determined that weak knowledge points exist, the test questions corresponding to the weak knowledge points of the target examinees in the target test paper are output; When it is determined that weak knowledge points exist, the overall score rate is determined based on the average first score rate of all candidates in the weak knowledge points.

6. The method according to any one of claims 1 to 4, characterized in that: The method further comprises: Obtain the question types in the target test paper; Determine the second score rate of all candidates, including the target candidates, for each test question type; By comparing the second score rate of the target candidate with that of all candidates on each test question type, the second evaluation level of the target candidate on each test question type is determined.

7. The method according to claim 6, characterized in that The method further comprises: A personalized analysis report for a target examinee is output, wherein the personalized analysis report includes a first evaluation grade for each knowledge point and a second evaluation grade for each test question type.

8. A knowledge point analysis device, characterized in that: include: An acquisition module is used to obtain a list of test question identifiers corresponding to each knowledge point in the target test paper; A processing module, for selecting a candidate from all candidates as a target candidate, and determining the first score rate of all candidates including the target candidate on each knowledge point based on the list of test question identifiers corresponding to each knowledge point; An evaluation module is used to determine the first evaluation level of the target candidate at each knowledge point by comparing the first score rate of the target candidate with that of all candidates at each knowledge point; The determination module is used to determine that the knowledge points whose first evaluation level is a preset level are weak knowledge points of the target examinee.

9. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; Memory, used to store computer programs; The processor is used to implement the steps of the knowledge point analysis method described in any one of claims 1 to 7 when executing the program stored in the memory.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the knowledge point analysis method according to any one of claims 1 to 7 are implemented.

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