RT info:eu-repo/semantics/article
T1 Forecasting the composition of demand for higher education degrees by genetic algorithms
A1 Hernández López, Montserrat
A1 Cáceres Hernández, José Juan
K1 higher education
K1 forecasting
K1 genetic algorithms
AB A genetic algorithm is developed to forecast the relative presence of different university studies in the higher education demand in the field of economics and business/management as a whole. A selection operator is defined that assumes that the better the job opportunities associated with a specific university study, the higher the future demand for such a degree. A transition matrix takes other factors into account which may influence on the changes in demand. The proposed algorithm is applied to the original populations of students enrolled on 2005/2006 to 2007/2008 courses. Then, a new algorithm, whose elements are corrected to adjust the forecasts, is applied to obtain the forecast of the demand composition on the 2009/2010 course. This methodological proposal is shown to be able to provide the type of forecast which is very useful in policy making decisions in the recent process of building the European Higher Education Area.
YR 2016
FD 2016
LK http://riull.ull.es/xmlui/handle/915/40638
UL http://riull.ull.es/xmlui/handle/915/40638
LA en
DS Repositorio institucional de la Universidad de La Laguna
RD 25-dic-2024