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Student score prediction method and device based on fuzzy cloud cognitive diagnosis model

A diagnostic model and prediction method technology, applied in fuzzy logic-based systems, specific mathematical models, predictions, etc., can solve the problems of insufficient score prediction accuracy and low calculation efficiency, and improve prediction accuracy and calculation efficiency. The effect of simplifying the estimation process and shortening the execution time

Pending Publication Date: 2021-11-19
HUNAN NORMAL UNIVERSITY
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Problems solved by technology

[0027] However, due to the above-mentioned limitations of the existing cognitive diagnostic models, the score prediction methods based on the existing cognitive diagnostic models still have the problems of insufficient score prediction accuracy and low computational efficiency in the online learning scenario of massive data.

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  • Student score prediction method and device based on fuzzy cloud cognitive diagnosis model
  • Student score prediction method and device based on fuzzy cloud cognitive diagnosis model
  • Student score prediction method and device based on fuzzy cloud cognitive diagnosis model

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Embodiment Construction

[0085] In order to make the purpose, technical solutions and advantages of the present disclosure clearer, the present disclosure will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0086] Such as figure 1 As shown, a method for predicting student scores based on a fuzzy cloud cognitive diagnosis model provided by an embodiment of the present invention specifically includes the following steps:

[0087] Step S10, establishing a student cognitive cloud model.

[0088] In this embodiment, the "student cognitive cloud" is defined by introducing the cloud model theory, and the student cognitive cloud model is obtained by mathematically describing the student cognitive cloud model. The student cognitive state can be comprehensively and objectively described by using the student cognitive cloud model uncertainty and volatility.

[0089] Preferably, step S10 includes the following steps:

[0090] Ste...

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Abstract

The invention discloses a student score prediction method and device based on a fuzzy cloud cognitive diagnosis model. The method comprises the following steps: establishing a student cognitive cloud model; according to a solving result of the student cognitive cloud model, obtaining a mastery degree interval number of students on knowledge points; according to the mastering degree interval number of the knowledge points, obtaining the mastering degree interval number of the students on test questions; and obtaining a prediction score of the test questions according to a target model parameter obtained by iterative training and the mastering degree interval number of the students on the test questions. According to the fuzzy cloud cognitive diagnosis model, fuzzy interval numbers obtained through student cognitive cloud conversion are used for depicting fuzziness and uncertainty of knowledge point mastering degrees of students, and more comprehensive representation of student cognitive states is achieved; besides, the fuzzy cloud cognitive diagnosis model simplifies model parameters, shortens model execution time, and effectively improves the prediction accuracy and calculation efficiency of student scores in a large-scale online learning scene under the support of the model.

Description

technical field [0001] The invention relates to the technical field of educational data mining, in particular to a method and device for predicting student scores based on a fuzzy cloud cognitive diagnosis model. Background technique [0002] Currently there are some cognitive diagnosis models (Cognitive Diagnosis Model, CDM) and student score prediction methods (Predicting Examinee Performance, PEP). [0003] (1) Cognitive diagnostic model [0004] Cognitive diagnostic models can be roughly divided into two types: discrete and continuous. The most representative of these two types of cognitive diagnostic models are Item Response Theory (IRT) and DINA (Deterministic Inputs, Noisy And-gate Model). [0005] IRT assumes that each student has a unique potential trait, and combines the student's performance on the test questions with characteristics such as discrimination and difficulty, and models the student as a one-dimensional continuous ability value, which represents the ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q50/20G06Q10/04G06N7/00G06N7/02
CPCG06Q50/205G06Q10/04G06N7/02G06N7/01
Inventor 马华黄卓轩李京泽唐文胜张栩翔
Owner HUNAN NORMAL UNIVERSITY
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