Predictive analysis and correlational exploration of public and academic attention in secondary vocational education

Autor: Pan Liu, Kai Liu, Junke Li, Yulin Zhao, Guanyu Wang
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Heliyon, Vol 10, Iss 4, Pp e25947- (2024)
Druh dokumentu: article
ISSN: 2405-8440
DOI: 10.1016/j.heliyon.2024.e25947
Popis: Secondary vocational education (SVE) is responsible for cultivating talents with moral and technical skills, receiving widespread attention from scholars and the public. Studying the two attentions can broaden the research perspectives and promote the development of SVE. However, there are the following problems: 1) the public attention and academic attention of SVE cannot be accurately characterized; 2) the relationship between the public attention and academic attention of SVE cannot be clear; 3) the impact of public attention and academic attention on SVE cannot be predicted. To address the above issues, this paper puts forward the PLSH (Pearson correlation–Linear regression, Seasonal autoregressive integrated moving average (SARIMA), and Holt-winters model) framework. It involves four research steps: 1) public attention and academic attention are obtained for SVE; 2) the correlation between them is analyzed and a linear model is developed; 3) the performance of the SARIMA model and Holt-winters model are conducted, and the best model is adopted to predict the public attention; 4) academic attention is predicted using the results from the previous step. The study shows that the PLSH framework can characterize academic and public attention to SVE, effectively reflecting their correlation and predicting their growth trends.
Databáze: Directory of Open Access Journals