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A learning content recommendation method and electronic equipment

A technology of learning content and electronic equipment, applied in the field of education, can solve the problems of poor pertinence of learning content and difficulty in immediately analyzing the learning level of new users, so as to improve the effect of learning.

Active Publication Date: 2019-04-16
GUANGDONG XIAOTIANCAI TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, when a new user uses a learning assistance app or a tutor machine for the first time, it is difficult to immediately analyze the learning level of the new user, resulting in the lack of pertinence in the learning content recommended to the new user

Method used

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  • A learning content recommendation method and electronic equipment
  • A learning content recommendation method and electronic equipment
  • A learning content recommendation method and electronic equipment

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0074] see figure 1 , figure 1 It is a schematic flowchart of a method for recommending learning content disclosed in an embodiment of the present invention. in, figure 1 The described learning content method is applicable to electronic devices such as mobile phones, tablet computers, tutoring machines, etc., and is not limited in the embodiments of the present invention. Wherein, the above-mentioned operating system of the mobile terminal may include but not limited to Android operating system, IOS operating system, Symbian (Symbian) operating system, Black Berry (Blackberry) operating system, Windows Phone8 operating system, etc., the embodiment of the present invention does not Do limited. like figure 1 As shown, the learning content recommendation method may include the following steps:

[0075] 101. The electronic device detects the test question answers and self-assessment levels input by the user to the output test questions.

[0076] In the embodiment of the pres...

Embodiment 2

[0091] see figure 2 , figure 2 It is a schematic flowchart of another learning content recommendation method disclosed in the embodiment of the present invention. like figure 2 As shown, the learning content recommendation method may include the following steps:

[0092] 201. The electronic device detects answers to test questions and self-assessment levels input by the user to the output test questions.

[0093] 202. The electronic device judges whether the answer to the test question matches the standard answer of the evaluation test question, if yes, execute steps 203 to 204, and if not, execute step 208.

[0094] 203. The electronic device acquires the user's age and the user's heart rate detected by the wearable device worn by the user when the user inputs the answers to the test questions and the self-assessment level.

[0095] In the embodiment of the present invention, the wearable device worn by the user may be provided with a heart rate sensor, specifically, it ...

Embodiment approach

[0111] Before adjusting the estimated mastery level according to the difference between the user's heart rate and the heart rate threshold, obtain the face image of the user when inputting the answer to the test question and the self-assessment level captured by the camera;

[0112] Carry out emotion recognition on the face image, judge whether the emotion of the face image is a positive emotion (such as excitement, joy, etc.), if not, execute the step of adjusting the estimated mastery degree according to the difference between the user's heart rate and the heart rate threshold.

[0113] 206. The electronic device determines the user's current mastery level of the first mastered knowledge point according to the self-assessment level.

[0114] 207. The electronic device determines the corresponding association degree threshold according to the current mastery degree of the first mastered knowledge point, and finds the knowledge points that are associated with the first mastered...

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PUM

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Abstract

The invention discloses a learning content recommendation method and electronic equipment, and the method comprises the steps: determining a first grasped knowledge point and a first non-grasped knowledge point of a user by judging whether a test question answer input by the user is matched with a standard answer, and determining the current grasped degree of the first grasped knowledge point according to the self-evaluation level input by the user; Determining a corresponding association degree threshold value according to the current mastering degree of the first mastered knowledge point, and finding out the knowledge point which is associated with the first mastered knowledge point and has the association degree higher than the association degree threshold value as a predicted masteredknowledge point; Searching knowledge points associated with the first ungrasped knowledge points as predicted ungrasped knowledge points; Learning content associated with predicting part or all of thegrasped knowledge points, the first ungrasped knowledge points, and the predicted ungrasped knowledge points is output. According to the method, the knowledge point mastering level of the new user can be rapidly analyzed, so that related learning contents are recommended to the new user in a targeted manner.

Description

technical field [0001] The invention relates to the field of education technology, in particular to a learning content recommendation method and electronic equipment. Background technique [0002] At present, most learning assistance applications (Application, APP) or tutoring machines have a content recommendation function, which can recommend content that meets the user's learning interest or learning intention for different users. However, in practice, it has been found that this content recommendation function mainly collects a large number of application usage behaviors generated by users when using learning assistance apps or tutoring machines, and analyzes users' preferences and learning levels, so as to recommend relevant learning for users. content. In practice, it is found that this learning content recommendation method is often limited by the amount of data and is not suitable for new users. Therefore, when a new user uses a learning assistance app or a tutor m...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06Q10/04G06Q50/20
CPCG06Q10/04G06Q10/06393G06Q50/205
Inventor 蒋小云
Owner GUANGDONG XIAOTIANCAI TECH CO LTD