Forecasting Student Enrollment Trends in Hotel Catering and Institutional Management at Kumasi Technical University
John Ayuekanbey Awaab *
Department of Statistical Sciences, Kumasi Technical University, Ghana.
Gloria Owusu Sarpong
Department of Hotel Catering and Institutional Management, Kumasi Technical University, Ghana.
Irene Ashley
Department of Hotel Catering and Institutional Management, Kumasi Technical University, Ghana.
Ishmael Ayim
Department of Hotel Catering and Institutional Management, Kumasi Technical University, Ghana.
Evelyn Catherine Impraim
Department of Hotel Catering and Institutional Management, Kumasi Technical University, Ghana.
*Author to whom correspondence should be addressed.
Abstract
This study considered the trends in enrollment for two major programs at Kumasi Technical University: The Higher National Diploma and the Bachelor of Technology in Hospitality and Catering Management. The research study employed descriptive statistics, stationarity tests, and ARIMA modeling to analyze past enrollment data and provide a forecast of future trends. It shows that the HND program has a higher and more stable enrollment base, with an average of 85.6 students, whereas the BTECH program is rather variable, with lower enrollment figures at an average of 28.2 students. The results of the test show that both the HND and BTECH time series data are stationary and therefore could be modelled for forecasting future trends using ARIMA models. Based on this, one would immediately project that the numbers studying for HND are likely to decline steadily from 2025 to 2029. Correspondingly, BTECH numbers would increase throughout this same period. These trends suggest that the university may need to adapt its curriculum and strategic direction, particularly for the HND program, in response to declining enrollments and capitalize on the growing demand for BTECH degrees in technology and engineering. This study emphasizes the need to align academic programs with the demands of the labor market and shifting student preferences as a means of ensuring long-term sustainability and relevance.
Keywords: Students enrollment, ARIMA model, higher education, curriculum development, time series analysis