Current Situation and Strategy Formulation of College Sports Psychology Teaching Following Adaptive Learning and Deep Learning Under Information Education

Abstract

This study aims to explore the current situation and strategy formulation of sports psychology teaching in colleges and universities following adaptive learning and deep learning under information education. The informatization in physical education, teaching methods, and teaching processes make psychological education more scientific and efficient. First, the relevant theories of adaptive learning and deep learning are introduced, and an adaptive learning analysis model is implemented. Second, based on the deep learning automatic encoder, college students’ sports psychology is investigated and the test results are predicted. Finally, the current situation and development strategy of physical education in colleges and universities are analyzed. The results show that when the learning rate is 1, 0.1, and 0.01, there is no significant change in the analysis factors of recall, ndcg, item_coverage, and sps. When the learning rate is 1, their analysis factors change obviously, and it is calculated that the optimal learning rate of the model is 1. And the difficulty of the recommended test questions by using the sports psychology teaching method based on adaptive learning and deep learning is relatively stable. The test questions include various language points of sports psychology. Compared with others methods, adaptive learning and deep learning can provide comprehensive test questions for sports psychology teaching. This study provides technical support for the reform of sports psychology teaching in colleges and universities and contributes to optimizing the information-based teaching mode.

Optimization of the game improvement and data analysis model for the early childhood education major via deep learning

“…These principles harmonize seamlessly with the fundamental tenets of DL, which prioritize learning tailored to individual needs, foster critical comprehension, stimulate active creativity, and emphasize the transfer and application of knowledge. It is evident that DL stands as a potent tool for nurturing children's development and fostering their overall well-being 10 . The study of DL holds paramount importance from both a theoretical and practical perspective, especially in light of recent educational reforms and pedagogical advancements that place a strong emphasis on foundational literacy skills.…”

“…Figure 2 presents the CNN-optimized GIADA model. Equation (10) indicates feature extraction of data by CNN.…”