USING THE ANALYTIC HIERARCHY PROCESS TO IMPROVE TEACHING IN HIGHER EDUCATION
Universidad Nacional de Educación a Distancia (SPAIN)
About this paper:
Appears in:
INTED2012 Proceedings
Publication year: 2012
Pages: 593-600
ISBN: 978-84-615-5563-5
ISSN: 2340-1079
Conference name: 6th International Technology, Education and Development Conference
Dates: 5-7 March, 2012
Location: Valencia, Spain
Abstract:
Business simulators constitute one of the instructional methods more related to learning in university programs. They are defined as simplified mathematical abstractions of a situation related to the business world that allows participants, individually or in groups, to lead an organization or part of it, making decisions regarding operations that develop within a certain period of time, and observing its results. With them, students become aware of the real circumstances of the business world, learning from their experience in decision-making. That is why Business simulation games are a particularly important didactic learning methodology.
It could be stated that there are many studies that intend to measure business games efficacy as a didactic tool, even though there is no agreement in a point of view to measure its value. The purpose of this study is to contribute with new empirical evidence to such researches about business games teaching effectiveness in university education, and to value the business simulator that best suits future objectives.
Thus, the objective of this research is to determine the business game with more pedagogical efficiency from an academic approach, by implementing a multi-criteria methodology, the analytic hierarchy process. This technique will allow universities to select, within a set of games, the most suitable one according to its educational needs; obtaining a ranking displayed by the game, which based in the professor’s judgment and on a series of criteria, better complies with instructional expectations. Keywords:
Business simulation games, aggregate index of acceptability, educational needs and optimization.