ABSTRACT
Introduction: Student engagement is a best predictor variable of student' development and success. It can be highly influenced by internal and external environmental factors, such as perceived teacher support. Methods: In order to explore the influence of perceived teacher support on student engagement among higher vocational students, this study conducted a questionnaire on 1,136 Chinese higher vocational students using perceived teacher support, basic psychological needs satisfaction, learning drive, student engagement and Optimistic attributional styles for explaining positive events (OAS_P) five scales. Results: The results show that: (1) Perceived teacher support can't indirectly predict the student engagement among higher vocational students through basic psychological needs satisfaction; (2) Perceived teacher support can indirectly predict student engagement through learning drive; (3) Perceived teacher support can indirectly predict student engagement through basic psychological needs satisfaction and learning drive; (4) OAS_P has a significant moderation effect on both learning drive and student engagement. Discussion: The finding of this study stated that perceived teacher support has a significant influence on student engagement. So in the teaching process, teachers should pay attention to their learning psychology, provide them with various support and encouragement and beneficial guidance, stimulate their learning drive, help them form a positive and optimistic attribution style, and make them actively participate in learning and school life.
ABSTRACT
Traumatic brain injury (TBI) is a major cause of morbidity and mortality, both in adult and pediatric populations. However, the dynamic changes of gene expression profiles following TBI have not been fully understood. In this study, we identified the differentially expressed genes (DEGs) following TBI. Remarkably, Serpina3n, Asf1b, Folr1, LOC100366216, Clec12a, Olr1, Timp1, Hspb1, Lcn2, and Spp1 were identified as the top 10 with the highest statistical significance. The weighted gene coexpression analysis (WGCNA) identified 12 functional modules from the DEGs, which showed specific expression patterns over time and were characterized by enrichment analysis. Specifically, the black and turquoise modules were mainly involved in energy metabolism and protein translation. The green yellow and yellow modules including Hmox1, Mif, Anxa2, Timp1, Gfap, Cd9, Gja1, Pdpn, and Gpx1 were related to response to wounding, indicating that expression of these genes such as Hmox1, Anxa2, and Timp1 could protect the brains from brain injury. The green yellow module highlighted genes involved in microglial cell activation such as Tyrobp, Cx3cr1, Grn, Trem2, C1qa, and Aif1, suggesting that these genes were responsible for the inflammatory response caused by TBI. The upregulation of these genes has been validated in an independent dataset. These results indicated that the key genes in microglia cell activation may serve as a promising therapeutic target for TBI. In summary, the present study provided a full view of the dynamic gene expression changes following TBI.