English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In the future, the majority of PE (physical education) students in regular schools will become preschool teachers. As a result, these students’ sports habits and feelings will have a direct impact on future preschool education and the training of preschool children’s sports habits. As a result, PE curriculum in preschool normal schools must adapt to the future development of preschool education. This article develops a scientific, reasonable, and valuable children’s PE curriculum by constructing the basic framework of modern children’s PE curriculum. As a result, this research proposes two RNN-based models: one is a personalized recommendation model for children’s PE curriculum—LSAPR (long short-attention point-of-interest recommendation) model, and the other is a recommendation model for children’s PE curriculum sequence LSTM-RNNSR (long- and short-term memory-RNN sequence recommendation). The two models proposed in this paper have produced good off-line experimental results in various datasets, as well as a real-time personalized point-of-interest recommendation effect in practice.

Intelligent Analysis on the Rationalization of Children’s Physical Education Curriculum Based on Recurrent Neural Networks