CN111539588A - Method for predicting learning result by correcting short answer question score - Google Patents

Method for predicting learning result by correcting short answer question score Download PDF

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CN111539588A
CN111539588A CN202010653451.0A CN202010653451A CN111539588A CN 111539588 A CN111539588 A CN 111539588A CN 202010653451 A CN202010653451 A CN 202010653451A CN 111539588 A CN111539588 A CN 111539588A
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question
answer
score
test
knowledge point
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兰新华
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NANCHANG CAMPUS OF JIANGXI UNIVERSITY OF SCIENCE AND TECHNOLOGY
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06395—Quality analysis or management
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/20—Education
    • G06Q50/205—Education administration or guidance

Abstract

The invention discloses a method for predicting learning achievement by correcting simple answer scores. The method determines an answer set according to a score list, calls a first profile in a first question bank, calls a second profile in a second question bank, and determines a test question adjusting coefficient of each test question and a correction score of each question-answer identification. And finally, determining the learning result of each knowledge point code according to the question-answer score and the correction score. The invention determines the mastery degree of each question and answer knowledge point by the answerers through the corrected test paper scores, and can more accurately predict the learning achievement. The learning results of a plurality of students in a unified class or the same specialty are collected, and the teaching quality can be evaluated.

Description

Method for predicting learning result by correcting short answer question score
Technical Field
The invention relates to a method for predicting learning achievement by correcting simple answer question scores, belonging to the technology of processing and predicting subject achievement data.
Background
CN110929020A discloses a knowledge point mastery analysis method based on test results. The method systematically disperses different knowledge points into different test questions, and combines the error checking of different test questions of students to form a knowledge point mastering database for each student. In the specific test, the test content is generated into a question number, a knowledge point number is generated for each knowledge point, and the knowledge point mastery degree of the test result of one student in each list is analyzed. The knowledge point mastery degree calculation formula in the case considers the difficulty coefficient and student capability of the knowledge point, but does not consider the time length factor influencing the test score.
Some applicants have identified the impact of the time duration factor on performance, such as the performance prediction method of CN 110826796A. However, in this case, the duration is used as a preset parameter and not as an adjustment item. The related art related to the present application also discloses a method for processing result data disclosed in CN108710602A, which is a method for converting and processing result data by using various data tables such as a result data table and a result analysis table, and can be referred to in the present application. The method of knowledge point set recommendation of CN108573628A discloses a solution for creating question bank according to knowledge point category. CN104809677A discloses an automatic scoring method based on statistics and analysis of knowledge point grasping conditions, which mainly relates to scoring steps, and does not disclose how to analyze knowledge point grasping conditions.
In addition, the question type structure of the short answer questions is more complicated than the blank filling questions and the selection questions. Documents CN101587513A and CN110175585A only disclose examination paper marking methods for simple answers, and few inventors propose analytical prediction models for simple answers.
Therefore, the prior art lacks a method for determining learning outcome by correcting the question-answer score of a short-response question.
Disclosure of Invention
The invention provides a method for predicting learning achievement by correcting the score of a short answer question, which determines the mastery degree of each question and answer knowledge point of an answerer by correcting the score of a test paper and can more accurately predict the learning achievement.
A method for predicting learning outcome by correcting short-answer question score is characterized in that,
determining total length of test
Figure 289440DEST_PATH_IMAGE001
；
The first question bank stores a plurality of first profiles, and the first profiles comprise question identifications and question stem duration
Figure 472160DEST_PATH_IMAGE002
And multiple question-answer identifiers corresponding to the question stem identifier
Figure 455159DEST_PATH_IMAGE003
；
The second question bank stores a plurality of second profiles, and the second profiles comprise question and answer identifiers, knowledge point codes and question and answer scores
Figure 115948DEST_PATH_IMAGE004
Length of question and answer
Figure 258216DEST_PATH_IMAGE005
；
The score database stores score lists of multiple answerers, each score list has multiple question-answer identifiers and question-answer scores uniquely corresponding to the question-answer identifiers
Figure 346258DEST_PATH_IMAGE006
；
Determining a set of answers based on the score list
Figure 816554DEST_PATH_IMAGE007
The answer set comprises any question-answer mark with a non-zero question-answer score,
Figure 281033DEST_PATH_IMAGE008
for any
Figure 22681DEST_PATH_IMAGE009
All satisfy
Figure 484886DEST_PATH_IMAGE010
，
Figure 504795DEST_PATH_IMAGE011
；
According to the answer set, calling the first profile with the question-answer identification in the first question bank to determine the question amount regulating coefficient
Figure 569703DEST_PATH_IMAGE012
，
Figure 358667DEST_PATH_IMAGE013
。
Calling a second profile with the question-answer identifier in a second question bank according to the answer set to determine the test question adjustment coefficient of each test question
Figure 991774DEST_PATH_IMAGE014
，
Figure 498979DEST_PATH_IMAGE015
；
Determining a revised score for each question and answer identifier
Figure 852731DEST_PATH_IMAGE016
，
Figure 761781DEST_PATH_IMAGE017
；
According to question-answer score
Figure 300210DEST_PATH_IMAGE018
And the correction score
Figure 294710DEST_PATH_IMAGE016
Determining learning outcome for each knowledge point code
Figure 701421DEST_PATH_IMAGE019
，
Figure 464978DEST_PATH_IMAGE020
。
In the present invention, each knowledge point code contains one or more knowledge points.
In the invention, the learning result of the knowledge point code corresponding to the question-answer identification with any question-answer score not equal to zero is output.
In the present invention, in the case of the present invention,
Figure 439887DEST_PATH_IMAGE021
as the total number of questions that have been answered,
Figure 656105DEST_PATH_IMAGE022
the total number of questions and answers that have been answered in the test question.
In the invention, the learning achievement of a plurality of answerers for coding any knowledge point is predicted, the average learning achievement is obtained, and the teaching quality is determined.
In the present invention, in the case of the present invention,
Figure 617239DEST_PATH_IMAGE023
。
in the invention, each test question has more than one question and answer, and each test question mark corresponds to a plurality of question and answer marks.
The method for predicting the learning result by correcting the simple answer score distributes the answer time of each question and determines the correction coefficient according to the time distribution. And adjusting the score of each question and answer by using the correction coefficient, and finally summarizing to determine the test paper score. And determining the mastery degree of the answerer on each question and answer knowledge point according to the corrected test paper scores, so that the learning result can be predicted more accurately. The learning results of a plurality of students in a unified class or the same specialty are collected, and the teaching quality can be evaluated.
Drawings
Fig. 1 is a flowchart of a method for predicting learning outcome by correcting the score of a simple response question according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention.
The method for predicting learning outcome by modifying the score of a simple response question according to the present invention as shown in fig. 1 is used for predicting learning outcome according to the score of a test paper containing a plurality of simple response questions. Such test papers are, for example, the subjective questions of judicial examinations. The method mainly comprises the following steps:
determining total length of test
Figure 235302DEST_PATH_IMAGE001
. The total test duration refers to the total test duration of the test paper and represents the longest allowable answer of all the simple answersThe subject time is, for example, 2 hours or 3 hours. Before the examination, the operator assigns the total length of the examination to each short-response question to generate the length of the examination question. Meanwhile, the test question time length is divided into the time length for reading the question stem and the time length for completing each question and answer. If the answerer completes all the simple answers, the influence of time factors on answer quality can be not considered. If the answerer only completes partial simple answers, the actual answering efficiency of the partial simple answers is lower than the preset answering efficiency, and the proficiency of the answerer on the question-answering knowledge point is evaluated. It is necessary to have a reasonable allocation duration impact.
The first question bank stores a plurality of first profiles. The first profile comprises test question identification, test question duration and question stem duration
Figure 381112DEST_PATH_IMAGE002
And multiple question-answer identifiers corresponding to the question stem identifier
Figure 84626DEST_PATH_IMAGE003
. The question stem duration refers to the basic duration of reading the question stem by the answering machine. Each test question has more than one question and answer, so each test question mark corresponds to a plurality of question and answer marks. Based on the question and answer identification, a unique stem identification and stem duration may be determined from the first profile of the first question bank. For example, a first profile of a test paper for a subjective question of a judicial examination is shown in the following table.
Figure 833139DEST_PATH_IMAGE024
The second question bank stores a plurality of second profiles. The second profile comprises question-answer identification, knowledge point code and question-answer score
Figure 571288DEST_PATH_IMAGE025
Length of question and answer
Figure 888000DEST_PATH_IMAGE026
. The question-and-answer time length is a time length expected to be assigned to the corresponding question and answer. When a question-answer relates to multiple knowledge points, the corresponding knowledge point code may contain multiple knowledge pointsAnd (6) recognizing points. The second profile of the test paper is as follows.
Question-answering mark Question and answer score Duration of question and answer Knowledge point coding
11 5 5 113
12 5 10 117
21 5 10 256
22 10 10 259
31 5 5 365
32 10 5 371
33 10 10 377/241
41 5 5 119
42 10 5 633
43 10 10 671
44 15 15 678/114
The score database stores score lists of multiple answerers, each score list has multiple question-answer identifiers and question-answer scores uniquely corresponding to the question-answer identifiers
Figure 78810DEST_PATH_IMAGE027
. And after the examination paper is read, generating a score list according to the score condition of each question and answer of each simple answer of the answerer. The coaching performance of a student is shown in the table below.
Question-answering mark Question and answer score
11 5
12 3
21 5
22 8
31 0
32 0
33 0
41 5
42 6
43 3
44 0
Determining a set of answers based on the score list
Figure 381746DEST_PATH_IMAGE028
The answer set includes any question-answer identifiers with a non-zero question-answer score. Or, extracting the scored question-answer identifiers from all question-answer identifiers. In general, the question-answer identification is not zero, so that the answering machine can determine that the answering machine tries to answer the test questions, and the actual score can be regarded as the learning result of the answering machine. Answering set
Figure 708822DEST_PATH_IMAGE029
For any
Figure 462015DEST_PATH_IMAGE030
All satisfy
Figure 202438DEST_PATH_IMAGE031
. The preset test questions are always n, and each test question comprises the number of questions and answers of m.
Figure 496016DEST_PATH_IMAGE032
，
Figure 880861DEST_PATH_IMAGE033
。
Figure 414741DEST_PATH_IMAGE034
As the total number of questions that have been answered,
Figure 580144DEST_PATH_IMAGE035
the number of questions and answers that have been answered in the test questions.
According to the answer set, calling the first profile with the question-answer identification in the first question bank to determine the question amount regulating coefficient
Figure 349516DEST_PATH_IMAGE036
. Because partial answerers only answer partial test questions, the time actually consumed for the answered test questions exceeds the preset time length, and the answering person does not scoreCan be used as the actual learning result of the test question. The question volume adjusting coefficient is the degree that the answering time of the answerer exceeds the preset total answering time.
Figure 916764DEST_PATH_IMAGE037
。
Calling a second profile with the question-answer identifier in a second question bank according to the answer set to determine the test question adjustment coefficient of each test question
Figure 605234DEST_PATH_IMAGE038
. For partial respondents, the same test question only answers partial questions. Since the question stem duration is a lead time, the smaller the number of completed questions, the longer the time allocated for the questions is.
Figure 257932DEST_PATH_IMAGE039
。
Determining a revised score for each question and answer identifier
Figure 830996DEST_PATH_IMAGE040
，
Figure 987171DEST_PATH_IMAGE041
. According to question-answer score
Figure 862854DEST_PATH_IMAGE042
And the correction score
Figure 737269DEST_PATH_IMAGE040
Determining learning outcome for each knowledge point code
Figure 114024DEST_PATH_IMAGE043
，
Figure 718181DEST_PATH_IMAGE044
. S =120min was determined from the previous table as in the following table. Length of examination paper basic answer
Figure 951716DEST_PATH_IMAGE045
5+10+15+（5+10）+（10+10）+（5+5+10）=85 min. For the test question 10, the basic answer duration is long
Figure 251110DEST_PATH_IMAGE046
=5+5+10=20, basic answer time length of all questions and answers
Figure 228294DEST_PATH_IMAGE047
=5+10= 15. For the test question 20, the basic answer duration is long
Figure 172110DEST_PATH_IMAGE048
=10+10+10=30, basic answer time length of all questions and answers
Figure 576547DEST_PATH_IMAGE049
=10+10= 20. For the test question 40, the basic answering duration is long
Figure 363237DEST_PATH_IMAGE050
=15+5+5+10=35, basic answer time length of all questions and answers
Figure 878532DEST_PATH_IMAGE051
=5+5+10= 20. The following table is specific.
Figure 191702DEST_PATH_IMAGE052
Generally, the test questions which are not answered cannot predict whether the time is short or the test questions which are not answered, so that the system only outputs the learning result of the knowledge point codes corresponding to the question and answer identifications with any question and answer score which is not zero with the cautious purpose. For large-scale examinations of multiple students in the same specialty, the learning results of multiple respondents coding any knowledge points can be predicted, and the average learning results can be determined. The average learning outcome can be regarded as the teaching outcome of the teacher to the knowledge point. It should be noted that since the actual number of questions to be answered by the answerer cannot exceed the total number of questions, the total answering time cannot exceed the total examination time, and therefore
Figure 767039DEST_PATH_IMAGE053
。
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (7)

1. A method for predicting learning outcome by correcting short-answer question score is characterized in that,
determining total length of test
Figure DEST_PATH_IMAGE002
；
The first question bank stores a plurality of first profiles, and the first profiles comprise question identifications and question stem duration
Figure DEST_PATH_IMAGE004
And multiple question-answer identifiers corresponding to the question stem identifier
Figure DEST_PATH_IMAGE006
；
The second question bank stores a plurality of second profiles, and the second profiles comprise question and answer identifiers, knowledge point codes and question and answer scores
Figure DEST_PATH_IMAGE008
Length of question and answer
Figure DEST_PATH_IMAGE010
；
The score database stores score lists of multiple answerers, each score list has multiple question-answer identifiers and question-answer scores uniquely corresponding to the question-answer identifiers
Figure DEST_PATH_IMAGE012
；
Determining a set of answers based on the score list
Figure DEST_PATH_IMAGE014
The answer set includes any questions and answersThe question-answer labels with the scores not equal to zero,
Figure DEST_PATH_IMAGE016
for any
Figure DEST_PATH_IMAGE018
All satisfy
Figure DEST_PATH_IMAGE020
，
Figure DEST_PATH_IMAGE022
；
According to the answer set, calling the first profile with the question-answer identification in the first question bank to determine the question amount regulating coefficient
Figure DEST_PATH_IMAGE024
，
Figure DEST_PATH_IMAGE026
；
Calling a second profile with the question-answer identifier in a second question bank according to the answer set to determine the test question adjustment coefficient of each test question
Figure DEST_PATH_IMAGE028
，
Figure DEST_PATH_IMAGE030
；
Determining a revised score for each question and answer identifier
Figure DEST_PATH_IMAGE032
，
Figure DEST_PATH_IMAGE034
；
According to question-answer score
Figure DEST_PATH_IMAGE036
And the correction score
Figure 166577DEST_PATH_IMAGE032
Determining learning outcome for each knowledge point code
Figure DEST_PATH_IMAGE038
，
Figure DEST_PATH_IMAGE040
。
2. The method of claim 1, wherein each knowledge point code comprises one or more knowledge points.
3. The method for predicting learning outcome by modifying the simple answer score as claimed in claim 1, wherein the learning outcome of the knowledge point code corresponding to the question mark with any score not equal to zero is outputted.
4. The method of predicting learning outcome by modifying the short response question score according to claim 3,
Figure DEST_PATH_IMAGE042
as the total number of questions that have been answered,
Figure DEST_PATH_IMAGE044
the total number of questions and answers that have been answered in the test question.
5. The method of claim 1, wherein the learning outcome of any knowledge point coding of a plurality of respondents is predicted, an average learning outcome is obtained, and the teaching quality is determined.
6. The method for predicting learning outcome by modifying the short response question score according to claim 1,
Figure DEST_PATH_IMAGE046
。
7. the method of claim 1, wherein each test question has more than one question and answer, and each test question mark corresponds to multiple question and answer marks.
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