{"title":"基于深度学习模式的PSS体育教学创新的基本方向与实现路径","authors":"Huiming Ke, Yang Wang","doi":"10.17993/3ctecno.2023.v12n1e43.70-85","DOIUrl":null,"url":null,"abstract":"At present, the traditional model of PE in PSS (PSS)has seriously affected the quality of PE teaching in PSS and the perception of PE among primary and secondary school students. Because of the urgent need for innovation in PE in PSS, this study proposes the LSTM model to achieve an accurate prediction of the innovation direction of PE in PSS. Based on the LSTM model, the user behavior is classified by extracting the important features of the innovation direction. Expression to achieve accurate prediction of the future development direction of PE. Using the data confusion matrix to estimate the prediction accuracy of the LSTM model, the four evaluation indicators of Accuracy, Precision, F1, and AUC are 0.0532~0.2323 higher than the baseline model. The prediction results of PE teaching innovation in PSS from three aspects of teaching thought, teaching content, teaching objectives and essence are output, which has obvious guiding significance for the overall optimization of PE classrooms in PSS. This result shows that the LSTM prediction model has important practical value.","PeriodicalId":210685,"journal":{"name":"3C Tecnología_Glosas de innovación aplicadas a la pyme","volume":"149 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Basic direction and realization path of PE teaching innovation in PSS based on deep learning model\",\"authors\":\"Huiming Ke, Yang Wang\",\"doi\":\"10.17993/3ctecno.2023.v12n1e43.70-85\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"At present, the traditional model of PE in PSS (PSS)has seriously affected the quality of PE teaching in PSS and the perception of PE among primary and secondary school students. Because of the urgent need for innovation in PE in PSS, this study proposes the LSTM model to achieve an accurate prediction of the innovation direction of PE in PSS. Based on the LSTM model, the user behavior is classified by extracting the important features of the innovation direction. Expression to achieve accurate prediction of the future development direction of PE. Using the data confusion matrix to estimate the prediction accuracy of the LSTM model, the four evaluation indicators of Accuracy, Precision, F1, and AUC are 0.0532~0.2323 higher than the baseline model. The prediction results of PE teaching innovation in PSS from three aspects of teaching thought, teaching content, teaching objectives and essence are output, which has obvious guiding significance for the overall optimization of PE classrooms in PSS. This result shows that the LSTM prediction model has important practical value.\",\"PeriodicalId\":210685,\"journal\":{\"name\":\"3C Tecnología_Glosas de innovación aplicadas a la pyme\",\"volume\":\"149 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"3C Tecnología_Glosas de innovación aplicadas a la pyme\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17993/3ctecno.2023.v12n1e43.70-85\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"3C Tecnología_Glosas de innovación aplicadas a la pyme","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17993/3ctecno.2023.v12n1e43.70-85","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Basic direction and realization path of PE teaching innovation in PSS based on deep learning model
At present, the traditional model of PE in PSS (PSS)has seriously affected the quality of PE teaching in PSS and the perception of PE among primary and secondary school students. Because of the urgent need for innovation in PE in PSS, this study proposes the LSTM model to achieve an accurate prediction of the innovation direction of PE in PSS. Based on the LSTM model, the user behavior is classified by extracting the important features of the innovation direction. Expression to achieve accurate prediction of the future development direction of PE. Using the data confusion matrix to estimate the prediction accuracy of the LSTM model, the four evaluation indicators of Accuracy, Precision, F1, and AUC are 0.0532~0.2323 higher than the baseline model. The prediction results of PE teaching innovation in PSS from three aspects of teaching thought, teaching content, teaching objectives and essence are output, which has obvious guiding significance for the overall optimization of PE classrooms in PSS. This result shows that the LSTM prediction model has important practical value.