Knowledge tracking method and system based on knowledge state evolution representation of learner

A technology of knowledge status and learners, applied in the field of knowledge tracking, can solve problems such as difficult modeling of learners, failure to restore learning scenes, etc., and achieve the effect of assisting teaching practice

Active Publication Date: 2021-09-07
HUAZHONG NORMAL UNIV
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

However, the common deficiency is that it is difficult to model the process of the gradual evolution of the learner's knowledge state, and it is impossible to restore the real learning scene

Method used

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  • Knowledge tracking method and system based on knowledge state evolution representation of learner
  • Knowledge tracking method and system based on knowledge state evolution representation of learner
  • Knowledge tracking method and system based on knowledge state evolution representation of learner

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Embodiment Construction

[0053] In order to make the object, technical solution and advantages of the present invention clearer, the following in conjunction with the attached Figure 1-2 , the present invention will be described in further detail. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0054] In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other. The present invention will be further described in detail below in combination with specific embodiments.

[0055] figure 1 is a schematic diagram of a knowledge tracking method based on the evolution representation of the learner's knowledge state in the present invention. Such as figure 1 As shown, the method includes the following steps:

[0056] S1. Obtain statistical cognitive datasets...

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Abstract

The invention provides a knowledge tracking method and system based on knowledge state evolution representation of learners. The method comprises the following steps: acquiring a statistical cognitive data set of a plurality of learners for a plurality of knowledge point samples; generating knowledge state representation of the learner, and building a knowledge tracking model; generating a predicted value of future answering performance of the learner and in the established knowledge tracking model, wherein the input of the Bayesian knowledge tracking algorithm is the state matrix, and the output of the Bayesian knowledge tracking algorithm is the predicted value of future answering performance of the learner; generating an evolution term; incorporating an evolutionary term and optimizing into a loss function, wherein the training goal of the knowledge tracking model is to generate an accurate predicted value of future answer performance of the learner and to accurately model a gentle change in the knowledge state, the goal being accomplished by defining the loss function.

Description

technical field [0001] The invention belongs to the field of knowledge tracking, and in particular relates to a knowledge tracking method and system based on evolution representation of learners' knowledge status. Background technique [0002] Knowledge tracking is an important learner modeling method. It models the learner's historical answer sequence, tracks the learner's knowledge state, and then predicts the learner's future answering performance. Specifically, the learner's knowledge status refers to the learner's mastery of knowledge points, which will continue to change with the answering situation. Generally speaking, in the process of answering adjacent questions, the state of knowledge should gradually transition and evolve smoothly. How to restore the process of gently changing the knowledge state is a key issue in the knowledge tracking task. [0003] Existing knowledge tracking models mainly include two categories. The first type is the probabilistic knowledg...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/04G06N3/08G06N7/00G06F17/18G06F17/16G06Q10/04G06Q50/20
CPCG06N3/049G06N3/084G06F17/18G06F17/16G06Q10/04G06Q50/20G06N3/047G06N7/01G06N3/044G06N3/045
Inventor 孙建文刘三女牙蒋路路张凯邹睿
Owner HUAZHONG NORMAL UNIV
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