Academic quality measurement: A multivariate approach

This paper applies a new quality measurement methodology to measure the quality of the postgraduate courses. The methodology we propose is the Academic Quality Measurement (AQM). The model is applied to several simulated data sets where we know the true value of the parameters of the model. A nonparametric model, based in Nearest Neighbours combined with Restricted Least Squared methods, is developed in which students evaluate the overall academic programme quality and a set of dimensions or attributes that determine this quality. The database comes from a Spanish Public University post graduate programme. Among the most important conclusion we say the methodology presented in this work has the following advantages: Knowledge of the attribute weights allow the ordering of the attributes according to their relative importance to the student, showing the key factors for improving quality. Student weights can be related to student characteristics to make market segmentation directly linked to quality objectives. The relative strengths and weaknesses of the service (high educations) can be determined by comparing the mean value of the attributes of the service to the values of other companies (Benchmark process or SWOT analysis).Quality Measurement, Postgraduate Programme, Nonparametric Model.

Academic quality measurement: A multivariate approach

This paper applies a new quality measurement methodology to measure the quality of the postgraduate courses. Themethodology we propose is the Academic Quality Measurement (AQM). The model is applied to several simulated data setswhere we know the true value of the parameters of the model. A nonparametric model, based in Nearest Neighbours combinedwith Restricted Least Squared methods, is developed in which students evaluate the overall academic programme quality and a setof dimensions or attributes that determine this quality. The database comes from a Spanish Public University post graduateprogramme. Among the most important conclusion we say the methodology presented in this work has the following advantages:Knowledge of the attribute weights allow the ordering of the attributes according to their relative importance to the student,showing the key factors for improving quality. Student weights can be related to student characteristics to make marketsegmentation directly linked to quality objectives. The relative strengths and weaknesses of the service (high educations) can bedetermined by comparing the mean value of the attributes of the service to the values of other companies (Benchmark process orSWOT analysis).Premio al mejor “Working Paper” del Departamento de Economía Financiera y Contabilidad de la Universidad Pablo de Olavide (edición 2011)

A New Approach for Academic Quality Measurement

This paper applies a new quality measurement methodology to measure the quality of the postgraduate courses. The methodology we propose is the Academic Quality Measurement (AQM). The model is applied to several simulated data sets where we know the true value of the parameters of the model. A nonparametric model, based in Nearest Neighbours combined with Restricted Least Squared methods, is developed in which students evaluate the overall academic programme quality and a set of dimensions or attributes that determine this quality. The database comes from a Spanish Public University post graduate programme. Among the most important conclusion we say the methodology presented in this work has the following advantages: Knowledge of the attribute weights allow the ordering of the attributes according to their relative importance to the student, showing the key factors for improving quality. Student weights can be related to student characteristics to make market segmentation directly linked to quality objectives. The relative strengths and weaknesses of the service (high educations) can be determined by comparing the mean value of the attributes of the service to the values of other companies (Benchmark process or SWOT analysis)