FORECASTING WITH ARIMAX MODELS FOR PARTICIPATING STEM PROGRAMS
學年 108
學期 2
出版（發表）日期 2020-02-01
作品名稱 FORECASTING WITH ARIMAX MODELS FOR PARTICIPATING STEM PROGRAMS
作品名稱（其他語言）
著者 Dian-Fu Chang; Chia-Chi Chen; Angel Chang
單位
出版者
著錄名稱、卷期、頁數 ICIC Express Letters Part B: Applications 11(2), p.121-128
摘要 Many studies have examined different fields of higher education expansion as well as the understanding of expansion through the relationship between higher education and other academic fields. This study examined how the expansion of higher education impacts STEM (science, technology, engineering and mathematics) programs and differentiates in the trajectories of Taiwan. This study aims to explore the expansion phenomenon related to the enrollment in STEM in expanding higher education. We used the classical ARIMA model to provide forecasts for the Ministry of Education (MOE) dataset. We then implemented ARIMAX (a multivariate autoregressive integrated moving average model) method to deal with the two concurrent series. The data source of this study, the time series data of student enrollment in the STEM programs and total student numbers (1950 to 2018), retrieved from MOE, Taiwan. We conducted the cross-correlation function to check the relationships between the series. We employed the ARIMAX methods to select the best fit model to predict student enrollment in STEM programs. The result revealed the selected ARIMAX(1,2,1) works well to establish the best fit model to predict enrollment in STEM programs. This finding provided implication to educational policy makers to implement the innovative STEM programs.
關鍵字 ARIMA;ARIMAX;Cross-correlation function;Higher education;STEM;Transfer function
語言 en_US
ISSN 2185-2766
期刊性質 國外
收錄於
產學合作
通訊作者 Angel Chang
審稿制度 是
國別 JPN
公開徵稿
出版型式 ,紙本
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/118153 )

SDGS 優質教育,性別平等