Personalized adaptive online learning method based on big data

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...

AI Technical Summary

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

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