Method for achieving user ability prediction through man-machine interaction

A human-computer interaction and user-friendly technology, applied in the field of machine learning, can solve problems such as loss of accuracy, low evaluation, and unbalanced student abilities, and achieve the effects of eliminating interference, accurately expressing ability, and increasing the accuracy of information acquisition

Active Publication Date: 2018-11-30
北京悉之智能科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, since only the final options of the students can be obtained, this method can only treat all the abilities associated with a topic as a whole, ignoring the fact that students often have uneven abilities
When students are doing a question, the prob

Method used

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  • Method for achieving user ability prediction through man-machine interaction
  • Method for achieving user ability prediction through man-machine interaction
  • Method for achieving user ability prediction through man-machine interaction

Examples

Experimental program
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Embodiment 1

[0061] Such as figure 1 As shown, the method for predicting user capabilities through human-computer interaction provided in this embodiment includes the following steps.

[0062] S100. Pre-store knowledge point basic data, user current ability data, and test question basic data for answering test questions in the database, wherein the knowledge point basic data includes a first topological order for expressing the prior relationship of all knowledge points, and the The user's current ability data includes the user's current ability value at each knowledge point, and the basic data of the test question includes the standard answer with at least two answer steps, the second topological sequence used to express the prior relationship of all answer steps, and the corresponding The knowledge point, the difficulty value of the knowledge point and the discrimination value of the knowledge point of the step.

[0063] In the step S100, the prior relationship of knowledge points means...

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Abstract

The invention relates to the technical field of machine learning, and discloses a method for achieving user ability prediction through man-machine interaction. According to the method, participation of any human teacher is not needed in other steps except data preparation and parameter setting in the first step, and therefore occupation to the manpower resource and particularly the education resource is reduced maximally; meanwhile, due to the fact that the method is achieved on the basis of the question step structure and the single step-level doing right accuracy rate, the performance abilities when a user answers various parts of a question can be more precisely estimated, and the purpose of improving the prediction precision by introducing step-level information of the question is achieved; and in addition, in the man-machine interaction process, the step-level right and wrong information of the user can be obtained on the condition that the teaching process is not influenced by means of the ingenious interaction design.

Description

technical field [0001] The invention belongs to the technical field of machine learning, and in particular relates to a method that can be applied to the education industry and complete user ability prediction through human-computer interaction. Background technique [0002] In the education industry, accurate prediction of students' performance on the topic has great reference significance for topic recommendation, explanation and practice, and even the formulation of the entire learning plan. [0003] In traditional teaching, this process is often carried out by teachers. However, first of all, teachers' cognition of students is very perceptual and cannot be quantified. They can only simply identify "easy to make mistakes" or "not easy to make mistakes", and cannot give an accurate quantitative value. Naturally, it is impossible to compare steps and questions A comparison between them provides enough information. At the same time, human memory also determines that teache...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q10/04
CPCG06Q10/04G06Q10/06393
Inventor 孙一乔
Owner 北京悉之智能科技有限公司
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