Higher education expansion has become a global concern issue, while little study addressed whether the patterns of program participation have been changed and to what level the trend will be in the future. This study focused on the heterogeneity of students’ program participation in higher education. Taking Taiwan’s higher education system as an example, we employed the concept of the Blau index and conducted autoregressive integrated moving average (ARIMA) models to tackle the issue. The series data were aggregated from the government’s data sets from 1950 to 2020. Blau index was used to transform heterogeneity data of the program participants in the target higher education. ARIMA was used to select a fitted predicated model and project future trends for the target series. Based on the parameters and the residual test, the findings suggest the Blau index and ARIMA model work well to deal with this issue. Considering many countries have moved to over-expanded higher education, the application of the Blau index and ARIMA for detecting heterogeneity of program participation can be extended to solve similar issues in other higher education systems.
Relation:
ICIC Express Letters Part B: Applications 14(4), p.349–357
