Chinese Personalized Course Content Push Algorithm in Online Vocational Education Based on Big Data

Abstract

In the past, most vocational education courses were provided by teachers and had to be learned in traditional ways. However, with the development of technology, online vocational education is becoming more and more popular. Using big data analysis can help us provide students with personalized course content according to their learning needs. This article aims to explore how big data analysis can be applied to online vocational education and how to improve students' academic performance. Using big data in vocational education can help us analyze students' learning behaviors and preferences, and provide personalized content according to their needs. Use big data analysis to generate personalized course content based on learners' learning behavior. This article proposes a personalized course content push algorithm based on big data for online vocational education that can provide refined and high-quality course resources, automatically identify learning needs based on learners' characteristic information, dynamically and adaptively present personalized learning activity sequences, and implement accurate content push, thereby improving students' learning efficiency and saving learning time. It includes the following steps: Based on personalized learning by students receiving vocational education, a personalized teaching service system framework for vocational education is constructed from four parts: a learning situation model, a professional model, an adaptive engine, and a presentation model; Adaptively recommend learning content, learning activity sequences, and knowledge tree structure suitable for learners based on the learning situation model and professional model, and display them on the page; At the same time, it can modify the learning behavior history of learners, maintain the learning situation model, and improve the accuracy of the learning situation model.