Test question difficulty prediction method
A prediction method and difficulty technology, applied in prediction, word processing, instruments, etc., can solve problems such as deviation of actual difficulty of test questions, inaccurate prediction results, and relevance considerations
Pending Publication Date: 2021-08-10
HEFEI UNIV OF TECH
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[0004] The embodiment of the present application provides a method for predicting the difficulty of test questions to at least solve the inaccurate prediction results caused by considering each knowledge point as independent discrete data in the related art and not taking into account the correlation between each knowledge point , technical problems that deviate greatly from the actual difficulty of the test questions
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[0025] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiment of the application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiment of the application. Obviously, the described embodiment is only It is an embodiment of a part of the application, but not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.
[0026] It should be noted that the terms "first" and "second" in the description and claims of the present application and the above drawings are used to distinguish similar objects, but not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used are interchangeable under appropriate circumstances such...
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The invention discloses a test question difficulty prediction method. The method comprises the following steps: performing text analysis on a target test question to obtain a target knowledge point investigated in the target test question; setting the target knowledge point as a father node, and determining a tree structure formed by sub knowledge points corresponding to the target knowledge point; obtaining the hierarchy of the target knowledge point in the tree structure and a first correlation coefficient corresponding to the hierarchy; determining a second correlation coefficient between the sub-knowledge points and the target knowledge point; determining a first difficulty value corresponding to the target knowledge point and a second difficulty value corresponding to the sub knowledge point; and determining a target difficulty value of the target test question at least according to the first correlation coefficient, the second correlation coefficient, the first difficulty value and the second difficulty value. According to the method and the device, the technical problems that the prediction result is inaccurate and has a relatively large deviation from the actual difficulty of the test question due to the fact that each knowledge point is taken as independent discrete data and the relevance between the knowledge points is not considered in the related technology are solved.
Description
technical field [0001] This application relates to the field of difficulty prediction of exercise questions, in particular, to a method for predicting the difficulty of test questions. Background technique [0002] There are many methods for predicting the difficulty of exercises. For example, the method for predicting the difficulty of exercises based on neural networks builds different network models for different types of questions, but there are many attributes of the questions. We also need to find some of the most important attributes as parameters for training. , which obviously requires a large workload, and in many traditional methods for predicting the difficulty of test questions, each knowledge point is regarded as a separate discrete data, and the correlation between each knowledge point is not taken into account. Therefore, in related technologies, when predicting the difficulty of test questions, each knowledge point is regarded as independent discrete data, a...
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IPC IPC(8): G06F40/14G06F40/205G06F16/335G06Q10/04G06Q50/20
CPCG06F40/14G06F40/205G06F16/335G06Q10/04G06Q50/205
Inventor 卜晨阳郝浩刘菲李磊胡学钢
Owner HEFEI UNIV OF TECH