TW201443667A - Artificial intelligent test paper item system and item method thereof - Google Patents

Abstract

The present invention discloses an artificial intelligent test paper item system, which comprises a database, an item difficulty discrimination module, an item sorting module, a exam result authentication module, and a level identification module for examinees. The database comprises multiple items. The item difficulty discrimination module is used for setting difficulty of each item. The item sorting module picks items with corresponding difficulty in accordance with selected discrimination. The exam result authentication module acquires solution of each item and validates them. The level identification module for examinees determines the level of students; items with corresponding difficulty are picked by analyzing the difficulty of each item of item pool through artificial intelligent analysis for composing a test paper. Exam and artificial intelligent training are carried out for achieving the highest discrimination to solve the problem of poor discrimination of test paper caused by artificial classification.

Description

Artificial intelligence test paper group title system and its group problem method

The invention relates to a test paper group question system, in particular to a test paper group question system which uses artificial intelligence to classify test questions according to the selected degree of discrimination.

In order to confirm whether the student understands the teacher's lecture content and to let the teacher understand the student's learning outcome after the lecture, the existing school or educational unit has multiple test evaluations in each semester, and according to the evaluation results for different students. The degree of learning is used for counseling. Because the degree of each student is different from the learning outcome, the teacher wants to select suitable test questions from the test question bank. As a student learning degree, it takes a lot of time to filter and classify the student degree and the test title. Among them, the question bank of the middle and the small country is the most large and complicated, and it is not easy to combine or select the examination papers suitable for each student level in the class.

Due to the limited professionalism, past teaching or experience of the lecturer, it is easy to subjectively judge the difficulty of the test, so the difficulty of the questions selected by different teachers is too large, and the discrimination is not good. The problem, as well as the gap between the student's test results and the test results are not worthy of reference.

As mentioned above, the existing examination questions are easily affected by the professional literacy and personal subjective factors of the students, and the differences in the difficulty of the examination questions are too large, and there are problems of poor discrimination. Therefore, the main purpose of the present invention is to provide an artificial wisdom test paper group. The system and its group method are mainly used to analyze the difficulty of the test questions by artificial intelligence. According to the selected degree of discrimination, the questions of the corresponding difficulty are selected from the question bank and the test papers are composed to solve the problem that the existing test papers are poorly discriminated by manual classification and screening.

The main technical means adopted to achieve the foregoing objectives is that the aforementioned artificial intelligence test paper group title system includes: a database storing a plurality of test questions; a difficult-to-discriminate degree module connected to the database for Set the difficulty level and scope of each test question; a topic screening module, which is linked with the database, is used to select the test questions corresponding to the difficulty in the database according to the selected degree of discrimination, and form a test paper with a majority of questions; The module is connected to the database for obtaining an external user's answer to each question; and a candidate degree discriminating module, which is respectively connected with the problem difficulty identification module and the test result verification module, for The difficulty of the test questions and the answers to the questions determine the degree of students.

The main technical means adopted to achieve the above objectives is the method of the aforementioned artificial wisdom test paper group, which includes: Set the discriminating degree of the test paper; determine whether the number of questions in the question bank meets the number of questions required for the discriminating degree of the test. If the number of questions in the question bank is sufficient, directly form the test questions and perform artificial intelligence verification training according to the set discrimination degree, if the test questions in the question bank If the number is insufficient, the questions will be randomly selected and the difficulty discrimination training will be carried out; and the artificial intelligence training will be carried out according to the test questions, the results of the questions and the degree of the candidates, so that the difficulty and discrimination of the group questions of the next test paper are in accordance with the degree of candidates.

The artificial intelligence test paper group question system consisting of the aforementioned components uses artificial intelligence to analyze the difficulty of each test question in the question bank, and according to the selected degree of discrimination, selects the test questions corresponding to the difficulty from the question bank with a large number of test questions and composes the test paper. The highest degree of discrimination can be achieved, so that all candidates' scores are normally distributed, and a test paper that effectively distinguishes the degree of each candidate is analyzed. After the test is completed, the scores and candidates are analyzed and artificial intelligence training is performed, so that the next test can be accurately determined according to the needs. Or the selected degree of discrimination is given to the appropriate difficulty topic, and the teacher's screening test time is reduced, and the problem of poor discrimination of the existing test paper by manual classification is solved.

"this invention"

10‧‧‧Server

10A‧‧‧Electronic devices

11‧‧‧Operator interface

20‧‧‧Database

30‧‧‧Difficult identification module

40‧‧‧Title screening module

50‧‧‧Exam results verification module

60‧‧‧ Candidate Level Discrimination Module

BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 is a block diagram of a circuit in accordance with a preferred embodiment of the present invention.

2 is a flow chart of a preferred embodiment of the present invention.

3 is a schematic diagram of an operation screen of an electronic device according to a preferred embodiment of the present invention.

4 is a schematic diagram showing the distribution of achievements in a preferred embodiment of the present invention.

Figure 5 is a schematic diagram showing the distribution of difficulty and discrimination in a preferred embodiment of the present invention.

For a preferred embodiment of the present invention, please refer to FIG. 1 to FIG. 3, which is provided with a database 20, a difficult identification module 30, a title screening module 40, and an examination result in a server 10. In the preferred embodiment, the server 10 is connected to one or more electronic devices 10A, and the electronic device 10A accesses the server 10 through a network connection. The electronic device 10A is a smart phone, a tablet computer, a notebook computer or a desktop computer, for displaying an operation screen, a test paper or a test item.

The database 20 stores a plurality of quiz questions and classifies the questions into different grades and subjects, such as first grade, second grade or sixth grade, and natural sciences, national liberal arts or mathematics.

The problem difficulty identification module 30 is linked to the database 20, which sets the difficulty of each test question in the database 20, for example, difficult, medium or easy.

The title screening module 40 is coupled to the database 20 for selecting test questions of the corresponding difficulty in the database 20 according to the selected degree of discrimination, and forming a test paper with a majority of questions. In the preferred embodiment, the title screening module 40 is a support vector machine with artificial intelligence, and performs machine learning training on the questions, and can select various training targets such as expected value, median, and mode. , variation, skewness, kurtosis, when A well-trained test bank can be selected according to the teacher's wishes to select the gifted students, backward students, or simply select questions in a high-discrimination manner to examine the class's ability. Among them, the degree of discrimination adjustment specifies the degree of discrimination of the test questions, so that the test scores are suitable for identifying gifted students, backward students or general normal distribution. The single student training system combines the questions suitable for the students according to the single student situation and sets the difficulty to make the students test. The score is close to the set score, the test results can be returned to the support vector machine, and the results will continue to be trained.

The test result verification module 50 is linked to the database 20 for obtaining an external user's answer to each question.

The candidate degree discriminating module 60 is respectively connected to the topic difficulty identification module 30 and the test result verification module 50 for judging the student degree according to the difficulty and the answer of the question.

As shown in FIG. 2 and FIG. 3, the user executes an application (APP) through the electronic device 10A to display an operation interface 11, which displays the data of the server 10 or sets parameters of each module, such as setting the test range. And the difficulty level, as shown in FIG. 3, the user sets the examination scope to the mathematics of the sixth grade to the next semester in the operation interface 11, the examination unit is the third chapter and the fourth chapter, the test number is 5 questions, and the question type is the automatic group. Question, and set the test time to be timed or not.

The operation process of the present invention can be divided into a user end (electronic device) and a database end (server), and the user end is provided for the user to operate by the operation interface 11 of the electronic device 10A, and the database end is set according to the setting. Parameter by servo The server 10 groups of questions, the following steps are carried out in sequence: the user sets the scope and discriminating degree of the test paper to be tested (101); and determines whether the number of questions in the question bank of the database 20 satisfies the number of questions required for the examination of the test (102) If the number of questions in the question bank is sufficient, the questions are directly grouped according to the degree of discrimination and the artificial intelligence verification training is performed (103). If the number of questions in the question bank is insufficient, the questions are randomly selected and the results are marked for difficulty identification training (104) The user conducts the test according to the questions generated by the group questions, and then sends the test results or answers back to the database (105); according to the group title questions, the results of the questions and the degree of the candidates, the artificial intelligence training is performed, so that the difficulty of the group questions of the next test paper is The degree of discrimination is in accordance with the degree of candidate (106).

Please refer to Figures 4 and 5, assuming that the degree of candidates and the exam questions are difficult. Degrees are normal distribution, which can be used to measure the degree of candidates. As shown in the figure, the number of students is S1, S2 to Sn, and the candidate class is Level1, Level2 to Leveln. The number of candidates and the candidate class are the original training of support vector machine. The data, using probability density function, standard deviation and variance as parameters, train the support vector machine and repeatedly verify the original data, adjust the parameters and the candidate class, so that the degree of candidate distribution is the normal distribution. For example, w * xb = 0, assuming that after training with the support vector machine, if b = 87.5 is found, then w * x - 87.5 = 0, that is, x = 87.5 (because of the one-dimensional space), therefore, it is assumed that the test score can be used to distinguish The degree of candidates is high and low, x=87.5 can be used to classify Level1 candidates. In the same way, manually distinguish the difficulty level, as the original data of the support vector machine training, and then classify the questions as described above (assuming that the difficulty of the test questions is also normal distribution, resulting in a low rate of training results is too low, can be used to other Distribution method), cross-validation of the difficulty of the test questions and the degree of candidates, to determine how high the training accuracy rate of the high-skilled class is under the high-level student class. Or average the questions of all kinds of difficulty, let all candidates take the test, check the training accuracy rate of the normal distribution, and repeatedly verify.

From the above, we can use artificial intelligence to analyze each test in the test bank. The difficulty of the question, according to the level of the selected degree of discrimination, the test questions of the corresponding difficulty are selected from a large number of test questions and composed of test papers, which can reach the highest degree of discrimination, so that the scores of all candidates are normally distributed, and the degree of each candidate is effectively distinguished. The test papers, after the test is completed, analyze the scores and the degree of candidates and carry out artificial intelligence training, so that the next test can accurately give appropriate difficulty questions according to the needs or the selected degree of discrimination, and reduce the teacher's screening test time, and solve the existing test papers generated by manual classification. The problem of poor discrimination.

10‧‧‧Server

20‧‧‧Database

30‧‧‧Difficult identification module

40‧‧‧Title screening module

50‧‧‧Exam results verification module

60‧‧‧ Candidate Level Discrimination Module

Claims (6)

An artificial wisdom test paper group question system comprises: a database storing a plurality of test questions; a difficult-to-discriminate degree module, which is linked with the database to set the difficulty level and the scope of each test question; The screening module is connected with the database, and is used for selecting the test questions corresponding to the difficulty in the database according to the selected degree of discrimination, and forming a test paper with a majority of questions; an test result verification module, which is linked with the database for obtaining An external user's answer to each question; and a candidate degree discriminating module, which is respectively linked with the problem difficulty identification module and the test result verification module, for judging the student degree according to the difficulty of the question and the answer of the test question. For example, the artificial intelligence test paper group questioning system described in claim 1 is a support vector machine with artificial intelligence to perform machine learning training on the test questions, and select various training targets such as expected values, Median, mode, variance, skewness, kurtosis to improve discrimination. The AI manual test group question system described in claim 1 or 2, the database, the title difficulty identification module, the title screening module, the test result verification module, and the candidate degree discrimination module are disposed in a server. . The AI manual test group system of claim 3 is an application executed by an electronic device to generate an operation interface for accessing the server data through the network connection to operate or set The difficulty and scope of the questions. The artificial intelligence test paper group question system of claim 4, wherein the electronic device is a smart phone, a tablet computer, a notebook computer or a desktop computer. An artificial wisdom test paper group question method includes: setting a discriminating degree of the test paper; determining whether the number of questions in the question bank satisfies the number of questions required for the degree of discrimination of the test, and if the number of test questions in the question bank is sufficient, directly forming the test questions according to the set degree of discrimination And carry out artificial intelligence verification training. If the number of questions in the question bank is insufficient, random questions will be given and difficult to identify and discriminate training; and artificial intelligence training will be carried out according to the composition test questions, the results of the questions and the degree of candidates, so that the difficulty and discrimination of the group questions of the next test paper Meet the candidate level.