2022
DOI: 10.3389/fpsyg.2022.843428
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Learning Behavior Evaluation Model and Teaching Strategy Innovation by Social Media Network Following Learning Psychology

Abstract: With the development of various network technologies and the spread of coronavirus disease 2019, many online learning platforms have been built. However, some of them may negatively impact student learning outcomes. Therefore, this study aims to improve the online learning effect of students by comprehensively evaluating their learning behavior by using deep learning algorithms. On this basis, new teaching strategies are proposed. According to the structured deep network embedding model, a network representati… Show more

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Cited by 14 publications
(6 citation statements)
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“…The model provides a comprehensive understanding of soccer players’ performance in matches, encompassing their movements, positions, and skill levels. This article benefits coaches and team managers and offers valuable feedback to athletes, aiding them in enhancing their technical and tactical proficiency [ 39 ].…”
Section: Discussionmentioning
confidence: 99%
“…The model provides a comprehensive understanding of soccer players’ performance in matches, encompassing their movements, positions, and skill levels. This article benefits coaches and team managers and offers valuable feedback to athletes, aiding them in enhancing their technical and tactical proficiency [ 39 ].…”
Section: Discussionmentioning
confidence: 99%
“…Nevertheless, despite the remarkable performance demonstrated by the VLMS model in various aspects, it is essential to acknowledge its limitations. First, the model's performance may be constrained when dealing with complex multi-modal data, such as data containing noise or ambiguity (Yuan et al, 2022). In such cases, the model's performance may not meet expectations, highlighting the need for further research to enhance its robustness in adapting to more complex real-world scenarios.…”
Section: Discussionmentioning
confidence: 99%
“…Research on time series analysis in credit evaluation is committed to making full use of the time information in personal credit history data to more accurately understand credit trends, predict future credit performance and identify credit default risks (Talaat et al, 2023;Yuan et al, 2022). Researchers use time series analysis methods, such as trend modeling and feature extraction, to capture time series characteristics in individual credit histories.…”
Section: Research On Time Series Analysis In Credit Evaluationmentioning
confidence: 99%