Student score prediction method based on two-way attention mechanism

A prediction method and attention technology, applied in neural learning methods, prediction, computer parts and other directions, can solve the problems of students ignoring and ignoring individual differences of students, and achieve the effect of improving prediction performance and realizing the task of grade classification.

Pending Publication Date: 2020-07-28
HENAN NORMAL UNIV
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Existing research either only considers the impact of important factors on student achievement and ignores the impact of secondary factors
Either assume that key factors affect all students to the same extent, ignoring individual differences among students

Method used

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  • Student score prediction method based on two-way attention mechanism
  • Student score prediction method based on two-way attention mechanism
  • Student score prediction method based on two-way attention mechanism

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Embodiment Construction

[0038] The present invention will be described in detail below in conjunction with the accompanying drawings. Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0039] A method for predicting student performance based on a two-way attention mechanism, comprising the following steps:

[0040] Step 1: Obtain student attributes, historical grades in the first stage and historical grades in the second stage;

[0041] Step 2: Obtain the feature vector f of each of the student's attribute characteristics about the historical performance of the first stage 1 and the eigenvector f of each of the studen...

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Abstract

The invention provides a student score prediction method based on a two-way attention mechanism. The student score prediction method comprises the following steps of obtaining student attribute characteristics, first-stage historical scores and second-stage historical scores; obtaining a feature vector f1 of each student attribute feature with respect to a first-stage historical score and a feature vector f2 of each student attribute feature with respect to a second-stage historical score; fusing the feature vector f1 and the feature vector f2 to obtain a feature vector f; and calculating a student score prediction score p from the feature vector f through a three-layer full-connection neural network MLP. By introducing a double-path attention mechanism, the defects of a single-path attention mechanism can be overcome, information complementation is well performed, and the prediction performance of the model is further improved; and for a prediction result, a plurality of evaluation indexes are remarkably improved.

Description

technical field [0001] The invention relates to the technical field of grade prediction, in particular to a student grade prediction method based on a two-way attention mechanism. Background technique [0002] Student performance prediction, that is, to predict the future performance of students based on information such as student attributes and historical performance, is one of the important goals of learning analysis. As an important research branch in the field of educational data mining, student achievement prediction helps teachers to intervene and guide students in a timely and effective manner, such as identifying students at risk so that intervention measures can be provided in a timely manner. In addition, it can also be used for online assessment, cognitive diagnosis, student portrait construction and recommendation system. How to use data mining technology to discover the hidden internal connections and laws from massive educational data, and to accurately predi...

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Application Information

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IPC IPC(8): G06Q50/20G06Q10/04G06N3/04G06N3/08G06K9/62
CPCG06Q50/205G06Q10/04G06N3/084G06N3/045G06F18/253
Inventor 王晓东李梦莹陈恩红刘淇张琨阮书岚李淳
Owner HENAN NORMAL UNIV
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