Cargando…

Learning Behavior Evaluation Model and Teaching Strategy Innovation by Social Media Network Following Learning Psychology

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 comp...

Descripción completa

Detalles Bibliográficos
Autores principales: Yuan, Lijuan, Li, Hongming, Fu, Shiman, Zhang, Zizai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9355304/
https://www.ncbi.nlm.nih.gov/pubmed/35936300
http://dx.doi.org/10.3389/fpsyg.2022.843428
Descripción
Sumario: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 representation learning algorithm is proposed with the help of auto-encoders under deep learning. This study elaborates the concept and structure of the encoder model and tests its performance. After the node labels and dataset are trained, the applicable parameter λ(2) of the model is 0.3. During the teaching process, the model’s reliability in distinguishing users is examined. Therefore, this model can be applied to network teaching, is an innovative teaching strategy, and provides a theoretical basis for improving teaching methods.