Personalized adaptive online learning method based on big data

An online learning and self-adaptive technology, applied in the field of online learning, can solve the problems of insufficient research work, not fully considering the influence of learners' sensitivity and learning effect, and achieve the effect of ensuring learning efficiency and learning effect

Inactive Publication Date: 2019-12-20
安徽学云教育科技有限公司
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Problems solved by technology

[0003] In recent years, data mining work has been widely carried out, but the research work on online learning personalized recommendation for learners is still insufficient
The current learning effect evaluation methods are all simple grade divisions, and there are few methods that apply more accurate big data analysis and prediction, and do not fully consider learners' personality characteristics (such as learning ability, learning efficiency, sensitivity to changes in learning content, etc.) etc.) on the effect of learning

Method used

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  • Personalized adaptive online learning method based on big data

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Embodiment Construction

[0027] refer to figure 1 , a kind of personalized adaptive online learning method based on big data that the present invention proposes, comprises:

[0028] Track the user's online question-making data, and divide the learning sections according to the user's question-making records.

[0029] According to the user's test data, calculate the error rate of each learning section of the user, and recommend exercises to the user according to the error rate of each learning section.

[0030] In this way, in this embodiment, real-time follow-up of the user's learning progress is realized through the summary of the test data, and the weak link in the user's learning is summarized in real time through the wrong question rate, so as to recommend exercises for the user's weak link. In this way, this embodiment realizes a comprehensive understanding of the user's learning situation based on the test data, points out the learning direction to the user through exercise recommendation, and ...

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Abstract

The invention provides a personalized adaptive online learning method based on big data. The method comprises the steps of tracking an online exercise data of a user, and dividing learning sections according to exercise records of the user; and according to the exercise data of the user, computing an error rate of each learning section of the user, and recommending exercises to the user accordingto the error rate of each learning section. According to the method, targeted guidance for each user is achieved by using the single user as a unit, the best and optimum learning method can be achieved for each user, and thus the learning efficiency and learning effect of each user are ensured via individual education.

Description

technical field [0001] The invention relates to the technical field of online learning, in particular to a personalized adaptive online learning method based on big data. Background technique [0002] With the continuous innovation and rapid development of information technology, the update of network technology is changing with each passing day, and the resulting massive data has received more and more attention, and the era of big data has come. In recent years, data mining, data analysis, and data-based content recommendation systems have been widely used in various industries. In the field of education, how to make it easy for students to learn and teachers to teach has become a problem that more and more people pay attention to. As the application of big data in the field of education, personalized adaptive learning has become a typical application case. [0003] In recent years, data mining work has been widely carried out, but the research work on online learning pe...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G09B7/04G09B7/08
CPCG09B7/04G09B7/08
Inventor 张元平
Owner 安徽学云教育科技有限公司
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