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Teaching effect portrait method and robot system based on big data and artificial intelligence

A big data and portrait technology, applied in the information field, can solve the problems of low subjectivity and accuracy of teaching effect portraits, and achieve the effect of improving objectivity and accuracy

Pending Publication Date: 2018-11-09
SOUTH CHINA NORMAL UNIVERSITY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Based on this, it is necessary to address the defects or insufficiencies of teaching effect portraits in the prior art, and provide teaching effect portrait methods and robot systems based on big data and artificial intelligence to solve the shortcomings of strong subjectivity and low accuracy of teaching effect portraits

Method used

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  • Teaching effect portrait method and robot system based on big data and artificial intelligence
  • Teaching effect portrait method and robot system based on big data and artificial intelligence
  • Teaching effect portrait method and robot system based on big data and artificial intelligence

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 2

[0050] On the basis of Example 1, in a preferred embodiment, the step S300 of evaluating labels includes:

[0051] S301, read each evaluation unit of each teacher from the big data storage system (such as Zhang San, 2018002, advanced mathematics, 2018-5-23 to 2018-8-12; Zhang San, 2018002, English, 2018 school year; Li Si, 2018003, chemistry, the first semester of 2017; etc.).

[0052] S302. Create a teaching effect portrait for each teacher (such as Zhang San's teaching effect portrait; Li Si's teaching effect portrait; etc.).

[0053] S303, use each evaluation unit of each teacher as an evaluation unit label of the teaching effect portrait of each teacher (for example, Zhang San, 2018002, advanced mathematics, 2018-5-23 to 2018-8-12 as Zhang An evaluation unit label of San’s teaching effect portrait; Zhang San, 2018002, English, 2018 school year as an evaluation unit label of Zhang San’s teaching effect portrait; Li Si, 2018003, chemistry, 2017 first semester as Li Si’s tea...

Embodiment 3

[0056]On the basis of Embodiment 1, in a preferred embodiment, the video recognition step S400 includes:

[0057] S401, identify each student from the teaching video corresponding to each evaluation unit of each teacher through face recognition technology, and encode the students. Preferably, the teaching video includes video recordings of classroom teaching process situations such as students listening to lectures, doing experiments, practicing, taking notes, answering questions, and reading aloud.

[0058] S402, obtaining a set of preset first actions from the teaching effect recognition knowledge base, and obtaining a preset action set of listening carefully to a class and a preset action set of not listening carefully to a class from the set;

[0059] S403, in the teaching video corresponding to each evaluation unit of each teacher, identify the action of each student and match each action with the set of preset actions of listening carefully to the class (if the preset ac...

Embodiment 7

[0103] On the basis of any one of Embodiments 1 to 6, in a preferred embodiment, the evaluation unit includes courses for a preset period of time; the first preset action includes students raising their heads and looking forward or / and Take notes with your hands.

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Abstract

The invention discloses a teaching effect portrait method and robot system based on big data and artificial intelligence. The method comprises the following steps: serving each evaluation unit of eachteacher as an evaluation unit label of a teaching effect portrait of each teacher, identifying the proportion of occupying the total duration of each evaluation by the total duration of the first preset actions of all students in the teaching record corresponding to each evaluation unit of each teacher, and serving the proportion as the value of one evaluation unit label of the teaching effect portrait of each teacher. Through the method and system disclosed by the invention, the portrait can be performed on the teaching effect of the teacher through the reaction on the course by the studentin the teaching process big data, the teaching effect of the teacher can be reflected more really and objectively, and the objectivity and accuracy of the teaching portrait and teaching evaluation canbe greatly improved.

Description

technical field [0001] The present invention relates to the field of information technology, in particular to a teaching effect portrait method and robot system based on big data and artificial intelligence. Background technique [0002] The existing teaching effect portrait is formed by students scoring teachers at the end of the term. [0003] In the process of realizing the present invention, the inventor finds that there are at least the following problems in the prior art: the student's evaluation of the teacher not only depends on how the teacher lectures, but also depends on the student's preference. Therefore, the existing teaching effect portraits cannot objectively evaluate the teaching effect, but are subject to the subjective influence of students, resulting in low accuracy of the teaching effect portraits. [0004] Therefore, the prior art still needs to be improved and developed. Contents of the invention [0005] Based on this, it is necessary to address t...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06F17/30G06Q10/06G06Q50/20
CPCG06Q10/06395G06Q50/205G06V40/20G06V20/42
Inventor 朱定局
Owner SOUTH CHINA NORMAL UNIVERSITY
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