Evaluation Model of Physical Education Teaching Effect Based on Embedded Neural Network

In response to the uniqueness of sports learning evaluation, we innovatively chose neural networks as the modeling basis and constructed a sports teaching effectiveness evaluation model based on embedded neural networks. This model achieves intelligent and automated evaluation of physical education teaching through the flexible processing capability of an efficient learning ability logic system embedded with neural networks. Specifically, embedded neural networks can deeply mine complex data during the teaching process. The embedded neural network effectively solves the uncertainty in the evaluation process and significantly improves the accuracy and adaptability of the evaluation system. In the process of model construction, we pay special attention to the adaptive processing capability of data. By introducing an adaptive neural system, the model can dynamically adjust parameters to better adapt to different teaching scenarios and individual differences among students, ensuring the objectivity and impartiality of evaluation results. This adaptability not only enhances the flexibility of the evaluation system, but also provides solid support for its application in practical teaching.