A self-adaptive learning method based on student capability level positioning and a computer system

A self-adaptive learning and computer system technology, applied in the field of self-adaptive learning methods and computer systems for students' ability level positioning, can solve problems such as discrete and single distribution of ability values, and achieve improved accuracy, improved learning efficiency, and high accuracy. Effect

Active Publication Date: 2019-06-28
SHANGHAI SQUIRREL CLASSROOM ARTIFICIAL INTELLIGENCE TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The existing method can roughly locate the general level of students, but the main problem is: the dimension of ability value is relatively single, and the current distribution of ability value is relatively discrete

Method used

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  • A self-adaptive learning method based on student capability level positioning and a computer system
  • A self-adaptive learning method based on student capability level positioning and a computer system
  • A self-adaptive learning method based on student capability level positioning and a computer system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0056] Such as figure 1 As shown, this embodiment provides an adaptive learning method for student ability level positioning, including:

[0057]Obtain the user's historical learning data and pre-test learning data;

[0058] Analyzing the historical learning data and pre-test learning data to obtain analysis results, the analysis results include the mastery rate of historical pre-test knowledge points, the mastery rate of pre-test knowledge points of this lesson, the improvement rate of historical knowledge points, and the conquering rate of historical knowledge points ;

[0059] Obtain the user's pre-learning student level according to the analysis result;

[0060] generating a user's learning route based on the pre-learning student level;

[0061] Push learning content based on the learning route.

[0062] The historical learning data includes the number of knowledge points mastered by the students in the historical pre-test, the number of knowledge points whose ability ...

Embodiment 2

[0080] refer to figure 1 As shown, in the self-adaptive learning method for student ability level positioning provided by this embodiment, the collected historical learning data also includes the user's test score data at school, and the analysis results include the test score ranking percentile. The calculation formula for obtaining the user's pre-learning student level according to the analysis result is:

[0081] level4=λ*master_rate_current+(1-λ)*level3

[0082] level3=θ*exam+(1-θ)*level1

[0083] level1=master_rate_history+improve_space

[0084] improve_space=(1-master_rate_history)*(α*improve_rate+(1-α)*capture_rate)

[0085] Among them, Level4 indicates the level of students before learning, master_rate_history indicates the mastery rate of historical knowledge points, master_rate_current indicates the mastery rate of first-test knowledge points in this lesson, improve_space indicates the improvement rate of historical knowledge points, capture_rate indicates the his...

Embodiment 3

[0088] This embodiment corresponds to Embodiment 1, and provides a student ability level positioning self-adaptive learning computer system, including:

[0089] The collection module is used to obtain the user's historical learning data and pretest learning data;

[0090] The analysis module is used to analyze the historical learning data and pre-test learning data to obtain analysis results, the analysis results include historical pre-test knowledge point mastery rate, pre-test knowledge point mastery rate for this lesson, historical knowledge point promotion rate and Historical knowledge point capture rate;

[0091] A calculation module, used to obtain the user's pre-learning student level according to the analysis result;

[0092] A planning module, configured to generate a user's learning route based on the pre-learning student level;

[0093] A push module, configured to push learning content based on the learning route.

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Abstract

The invention relates to a student capability level positioning adaptive learning method and a computer system. The method comprises the steps of obtaining historical learning data and pre-test learning data of a user; analyzing the historical learning data and the pre-test learning data to obtain an analysis result, the analysis result comprising a historical pre-test knowledge point mastery rate, a current class pre-test knowledge point mastery rate, a historical knowledge point improvement rate and a historical knowledge point attack rate; obtaining a pre-learning student level of the useraccording to the analysis result; generating a learning route of the user based on the pre-learning student level; and pushing learning contents based on the learning route. Compared with the prior art, the method has the advantages of improving user learning efficiency and the like.

Description

technical field [0001] The invention relates to the technical field of learning devices, in particular to a self-adaptive learning method and computer system for student ability level positioning. Background technique [0002] In the existing online education system, understanding a student's level is a preliminary and important part. Only by having a more accurate understanding of the students' situation can the follow-up strategies be prioritized or abandoned, and topics such as pushing questions can be effectively carried out. In the current online education system, the measurement of students' level is based on the ability value. Ability value is a display of mastery of knowledge points based on IRT theory. The learning level of the pre-test stage is the average ability value of the students in the specific class. The learning level of the learning stage is the average learning ability of the students in a specific class. The existing method can roughly locate the ge...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9535G09B5/00
Inventor 崔炜谢忱
Owner SHANGHAI SQUIRREL CLASSROOM ARTIFICIAL INTELLIGENCE TECH CO LTD
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