Big data location-based interactive remote teaching method

Abstract

The invention discloses a big data location-based interactive remote teaching method. According to the method, wireless real-time network teaching can be achieved, remote interaction of teachers and students can be achieved; a system can process and analyze massive learning client data by using a big data processing technology; a collaborative filtering technology is combined with a learning platform by learning from the advantages of a collaborative filtering recommendation algorithm in electronic commerce; and the learning interest of a user can be accurately located, so that a learning resource is accurately provided and the utilization rate of the online learning resource is greatly improved.

Description

[0001] Technical field [0002] The invention relates to an interactive distance teaching method based on big data positioning. 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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