Big data-based internet teaching system running method

Abstract

The present invention discloses a big data-based internet teaching system running method. According to the method, wireless real-time network teaching is implemented, and remote interaction between teachers and students is realized. The system uses a big data processing technology, so as to process and analyze massive learning client data. According to the method, the advantage of a collaborative filtering recommendation algorithm in electronic commerce is used for reference, and the collaborative filtering technology and a learning platform are combined, so that the use ratio of the online learning resources is improved greatly, and the teaching data is encrypted and then is transmitted remotely, thereby being ensured to transmit safely.

Description

[0001] Technical field [0002] The invention relates to an operation method of an Internet teaching system based on big data. Background technique [0003] Mobile learning, as a branch of network learning, is attracting more and more attention, and has become a new research hotspot in higher education technology and related fields. As a new form of learning, mobile learning has immeasurable application potential in the field of school education and training. The main purpose of mobile learning is to use mobile terminals and wireless communication networks to carry out teaching-related activities, including class learning, access to teaching resources, course evaluation and testing, and so on. [0004] With the development of the Internet, learning activities have expanded from the classroom to the Internet, and many Internet teaching system platforms have emerged, but there are still many defects in today's online learning systems: the utilization rate of teaching resources ...

AI Technical Summary

Problems solved by technology

[0004] With the development of the Internet, learning activities have expanded from the classroom to the Internet, and many Internet teaching system platforms have emerged. However, there are still many defects in today's online learning systems: the utilization rate of teaching resources is not high; there are countless learning resources, and learners are looking for needles in a haystack. Generally, it is impossible to quickly find the required resources; learners need to manually enter description words to search, and the system cannot actively recommend based on the user's own information

These defects make network learning lose its original advantages, therefore, it is urgent to integrate personalized service into the Internet teaching system platform

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