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Video learning effect evaluation method based on artificial intelligence

An artificial intelligence and video technology, applied in the field of digital learning, can solve the problems of no assessment method, no help in improving learning results, and inability to know the content of online assessment, so as to improve the effect of learning.

Active Publication Date: 2020-07-24
圆梦共享教育科技(深圳)有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, all the digital systems are not aimed at whether the online video assessment is really helpful to improve learning outcomes. There is no effective evaluation method, so it is impossible to know whether the content of the online video assessment is appropriate

Method used

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  • Video learning effect evaluation method based on artificial intelligence

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0030] The present invention provides a method for evaluating the effectiveness of video learning based on artificial intelligence, and the specific test steps are as follows:

[0031] S1. Pre-school comprehensive test: Prepare a set of pre-school test papers, inspect the knowledge points of the students, and deeply understand the students' mastery of the knowledge points and the types of error-prone questions. The comprehensive test includes yesterday's knowledge points and today's knowledge points. To achieve the effect of review, review in advance for the knowledge connection points in the next video teaching, so that users can clarify the learning points;

[0032] S2. Sorting out wrong questions: Perform wrong question statistics on the test results of step S1, prepare wrong question sets, and centrally mark the question types with the highest wrong question rate, so as to determine common knowledge blind spots;

[0033] S3. Video adjustment: adjust the knowledge point foc...

Embodiment 2

[0042] The present invention provides a method for evaluating the effectiveness of video learning based on artificial intelligence, and the specific test steps are as follows:

[0043] S1. Pre-school comprehensive test: Prepare a set of pre-school test papers, inspect the knowledge points of the students, and deeply understand the students' mastery of the knowledge points and the types of error-prone questions. The comprehensive test includes yesterday's knowledge points and today's knowledge points. To achieve the effect of review, review in advance for the knowledge connection points in the next video teaching, so that users can clarify the learning points;

[0044] S2. Sorting out wrong questions: Perform wrong question statistics on the test results of step S1, prepare wrong question sets, and centrally mark the question types with the highest wrong question rate, so as to determine common knowledge blind spots;

[0045]S3. Video adjustment: adjust the knowledge point focu...

Embodiment 3

[0054] The present invention provides a method for evaluating the effectiveness of video learning based on artificial intelligence, and the specific test steps are as follows:

[0055] S1. Pre-school comprehensive test: Prepare a set of pre-school test papers, inspect the knowledge points of the students, and deeply understand the students' mastery of the knowledge points and the types of error-prone questions. The comprehensive test includes yesterday's knowledge points and today's knowledge points. To achieve the effect of review, review in advance for the knowledge connection points in the next video teaching, so that users can clarify the learning points;

[0056] S2. Sorting out wrong questions: Perform wrong question statistics on the test results of step S1, prepare wrong question sets, and centrally mark the question types with the highest wrong question rate, so as to determine common knowledge blind spots;

[0057] S3. Video adjustment: adjust the knowledge point foc...

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PUM

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Abstract

The invention discloses a video learning effect evaluation method based on artificial intelligence, and particularly relates to the field of digital learning, and the method comprises the steps: comprehensive testing before learning, wrong question arrangement, video adjustment, information recording playing, in-class testing, judgment model building, score judgment, and single-person learning result model building. According to the invention, process records of all users are collected and include data such as online visual evaluation watching time and playback times, after-learning test difficulty question answering accuracy and answering time, and the like, and the data are used as training data sources after a new teaching video is online, whether the teaching video is appropriate or not is predicted through the collected user data by taking the ability result of the user after the test as the classification basis, so that whether the video has the effect of improving the learning effect or not is evaluated.

Description

technical field [0001] The invention relates to the technical field of digital learning, and more specifically, the invention relates to an artificial intelligence-based video learning effect evaluation method. Background technique [0002] E-learning refers to a new learning mode in which an Internet platform is established in the field of education and students learn through the Internet. Also known as network learning or E-learning. The integration of information technology and curriculum with digital learning as the core is different from traditional learning methods. The integration of information technology and curriculum with digital learning as the core is different from traditional learning methods, and has the following distinctive features: ① learning is student-centered, and learning is personalized to meet individual needs; ② learning is based on Problem or topic-centered; ③The learning process is communication, and the learners are negotiated and cooperative;...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/783G06F16/75G06Q10/06G06Q50/20
CPCG06F16/783G06F16/75G06Q10/0639G06Q50/205Y02D10/00
Inventor 邱长海洪哲伦林威延陈树威
Owner 圆梦共享教育科技(深圳)有限公司
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