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Subjective question self-adaptive examination paper marking method based on answer implication and dependency relationship

A technology of dependency and subjective questions, applied in data processing applications, special data processing applications, instruments, etc., can solve problems such as misjudgment

Active Publication Date: 2017-12-15
深圳市致远优学教育科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But in fact, when different students answer this subjective question, they will give answers in the following forms according to the context of the answer: "In the computer, the hard disk is installed in the main box", "The hard disk is installed in the main box", "Installed in the main box", "in the main box", and "in the main box", although the last three answers are also correct, but because these three answers have omitted some sentence components, if you still use calculation at this time Misjudgment will occur if the answer is graded according to the similarity of the sentence in the answer sheet

Method used

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  • Subjective question self-adaptive examination paper marking method based on answer implication and dependency relationship
  • Subjective question self-adaptive examination paper marking method based on answer implication and dependency relationship
  • Subjective question self-adaptive examination paper marking method based on answer implication and dependency relationship

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Embodiment 1

[0092] An adaptive marking method for subjective questions based on answer implication and dependence. The marking process is as follows: figure 1 shown, including the following steps:

[0093] 1. Classification and analysis of subjective questions

[0094] The invention divides the subjective questions into two categories: the subjective questions with interrogative words and the subjective questions with interrogative imperative words, and performs corresponding analysis and processing on their questions respectively.

[0095] (1) Subjective questions with interrogative words

[0096] Subjective questions with interrogative words refer to subjective questions in which interrogative words appear in the title but no interrogative imperative words appear, and questions are asked through interrogative words. For this type of subjective question, the present invention collects all interrogative words that may appear in the subjective question title in advance, and fo...

Embodiment 2

[0161] The self-adaptive marking method for subjective questions based on the answer implication and dependence relationship. The automatic marking process of the subjective question titled "What are the main types of network topology?":

[0162] Let the topic of the subjective question be "What are the main types of network topology?", the score is 10 points, and the corresponding standard answer for maximizing semantics is "The main types of network topology are star, ring, bus and hierarchical "; and set "hierarchical" and "tree" as synonyms in the ontology of the computer network field, in "Synonym Cilin", calculated by formulas (3) and (4), the verb "has" and "includes" The similarity between is 0.5; and in formula (11), set α=0.5, λ=β=0.25, try to review the following students' answers:

[0163] (1) Student answer 1: ring, tree, star

[0164] (2) Student answer 2: Network topologies include star, bus and hierarchical

[0165] according to figure 1 , the sco...

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Abstract

The invention discloses a subjective question self-adaptive examination paper marking method based on answer implication and a dependency relationship. The subjective question self-adaptive examination paper marking method comprises the following steps of 1, analyzing a question; 2, analyzing a standard answer; 3, analyzing student answers; 4, judging whether head words are verbs of the student answers or not; 5, marking the head words which are not the verbs of the student answers; 6, marking the head words which are the verbs of the student answers. Firstly, through the dependency relationship, sentence components of an interrogative in a subjective question and the dependency relationship constituted by the sentence components and the head words are determined; then, according to the sentence components of the interrogative, core semantics of the standard answer and the student answers is determined; finally, through the adoption of a method based on the answer implication, the dependency relationship and the term similarity, omission of the student answers for all the components is subjected to self-adaption, self-adaptive examination paper marking of the same standard answer in different answering modes is achieved, and the accuracy and practicability of a subjective question examination paper marking system are further improved. Therefore, the subjective question self-adaptive examination paper marking method based on the answer implication and the dependency relationship has a wide application prospect in the field.

Description

technical field [0001] The invention relates to the automation of examination paper marking in the field of educational technology and computer application technology, specifically an adaptive marking scheme for subjective questions based on answer implication and dependence. The automatic marking of subjective questions that adapts to students' answering methods can be widely used in computer automatic marking systems for subjective questions in various fields. Background technique [0002] The test questions in the test paper are generally divided into two categories: objective questions and subjective questions in terms of the form of answer composition. Test questions such as multiple-choice questions, multiple-choice questions, and judgment questions whose answers are expressed in option numbers are called objective questions, while short-answer questions, noun explanations, and essay questions whose answers are expressed in natural language are called subjective questi...

Claims

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Application Information

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IPC IPC(8): G06F17/27G06Q50/20
CPCG06F40/30G06Q50/20
Inventor 朱新华吴田俊杨雪晨
Owner 深圳市致远优学教育科技有限公司
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