Analysing influencing factors and correlation paths of learning burnout among secondary vocational students in the context of social media: An integrated ISM-MICMAC approach

By analysing the factors influencing secondary vocational students' learning burnout in the context of social media, this study unearthed the underlying causes of learning burnout. It also determined the correlation paths among the factors influencing learning burnout, providing references for educational and pedagogical improvement. This contributes to preventing secondary vocational students' learning burnout and enhancing learning efficiency in secondary vocational schools. Combined with previous research results and a theoretical basis, this study identifies 10 influencing factors employing the Delphi method, and uses Interpretative Structural Modelling (ISM) and Matrice d' Impacts Crois & eacute;s Multiplication Appliqu & eacute;s & agrave; un Classement (MICMAC) to elucidate the relationship between influencing factors of learning burnout among secondary vocational students in the context of social media. This study also constructs a corresponding mechanism model and subsequently proposes prevention and improvement strategies. The results show that the overdevelopment of social media, as driving factors, has the greatest impact on secondary vocational students' learning burnout. Simultaneously, it takes the lead in addressing cognitive bias among students, decreased self-control, and low learning efficiency, factors that contribute to learning burnout. This is particularly beneficial in alleviating the degree of learning burnout among secondary vocational students in the context of social media and improves overall learning outcomes for these students. The hierarchical structure and correlation paths identified in this study offer robust invaluable guidance for developing a scientific program to address the problem of learning burnout among this demographic. This includes implementing related educational practises, thereby reducing the unpredictability of the practical applications.