Prediction of employment region of graduates using machine learning approach

Abstract

The equality of education is very important to the country's development. However, the number of teachers who work in the rural area has significantly decreased. This situation causes a shortage in the number of rural teachers. This study proposes machine learning models for predicting the employment region of higher vocational college graduates. The data is gathered from graduates from a vocational college in Guangxi, Beihai vocational college. The size of the population is 454 where 285 samples work in the urban area and 169 samples work in the rural area. This research was performed by pre-processing the data, comparing the performance of the algorithms, and resampling methods. The results indicate that the F1-score of the best machine learning model can reach 0.991 ± 0.015. As nations strive for educational equity, our findings offer a framework to inform strategies for attracting graduates to rural teaching roles in both rural and urban areas.