Una facultad de Universidad Nacional de Cordoba, con modalidades de gestión tendientes a impulsar la mejora en la calidad educativa

El presente trabajo analiza modalidades de gestión tendientes a impulsar la mejora en la calidad educativa en la Facultad de Ciencias Exactas, Fisicas y Naturales de la Universidad Nacional de Cordoba - Argentina. El sistema propuesto comprende: detección de problemáticas; gestión y ejecución de acciones de mejora sobre procesos de enseñanza- aprendizaje; ingreso y actuación académica; acompañamiento con tutorías; atención de problemas especiales; aplicación de modelos predictivos del avance de los alumnos de primer año, capacitación de profesores y gestión de indicadores. La propuesta se apoya en los resultados previos obtenidos en dos líneas de investigación. Por una parte, el estudio de los sistemas de ingreso y retención de alumnos. Por la otra, el desarrollo y experimentación de métodos que facilitan el trabajo en equipo. El trabajo presenta algunas de las herramientas utilizadas y ejemplifica el modo en que se aplican; Enfatiza la necesidad de definir objetivos comunes a todas las áreas y utilizar estrategias de gestión y seguimiento; Propicia la retroalimentación a la comunidad educativa en general y a los equipos de trabajo en particular, sobre el nivel de logro de los objetivos planteados, las problemáticas detectadas y las oportunidades de mejora y Además incluye evidencias de los avances obtenidos en torno a algunos tópicos de la propuesta

Pemilihan Lift Berdasarkan Metode SMAA II Dan Metode VIKOR

Perkembangan Multicriteria Decision Making (MCDM) dalam beberapa tahun terakhir sangat pesat, banyak metode baru yang dikembangkan. Namun, beberapa metode yang telah dikembangkan belum banyak digunakan dalam praktiknya, sehingga masih sedikit pengetahuan tentang kinerja metode tersebut. Ada begitu banyak metode yang belum kita ketahui kinerjanya, apalagi jika pengambilan keputusan melibatkan banyak pihak dan banyak kriteria yang digunakan secara diskrit. Tujuan dari penulisan ini adalah untuk melihat performansi dari penggabungan dua metode yaitu Stochastic Multicriteria Acceptability Analysis-2 (SMAA-2) dan VIKOR (Visekreterijumsko Optimizacija Kompromisno Rangiranje). Selain itu, kinerja dilihat dari studi kasus yang dilakukan pada proses pengambilan keputusan dalam pemilihan elevator. Penelitian ini menunjukkan bahwa Central Weight (CW) metode SMAA-2 dapat digunakan sebagai pembobotan untuk metode VIKOR. Hasil penggabungan metode SMAA-2 dan metode VIKOR memberikan konsistensi dalam menyelesaikan pengambilan keputusan./ The development of Multicriteria Decision Making (MCDM) in recent years is very rapid, many new methods have been developed. However, some of the methods that have been developed have not been widely used in practice, so there is still little knowledge of the performance of these methods. There are so many methods that we don't know the performance of, especially if the decision-making involves many parties and many criteria are used discretely. The purpose of this paper is to see the performance of combining two methods, namely, Stochastic Multicriteria Acceptability Analysis-2 (SMAA-2) and VIKOR (Visekreterijumsko Optimizacija Kompromisno Rangiranje). In addition, the performance is seen from case studies conducted on the decision making process in the selection of elevators. This study shows that the Central Weight (CW) of the SMAA-2 method can be used as a weighting for the VIKOR method. The results of combining the SMAA-2 method and the VIKOR method provide consistency in completing decision making

Applying multiple criteria decision analysis to comparative benefit-risk assessment: choosing among statins in primary prevention

Decision makers in different health care settings need to weigh the benefits and harms of alternative treatment strategies. Such health care decisions include marketing authorization by regulatory agencies, practice guideline formulation by clinical groups, and treatment selection by prescribers and patients in clinical practice. Multiple criteria decision analysis (MCDA) is a family of formal methods that help make explicit the tradeoffs that decision makers accept between the benefit and risk outcomes of different treatment options. Despite the recent interest in MCDA, certain methodological aspects are poorly understood. This paper presents 7 guidelines for applying MCDA in benefitrisk assessment and illustrates their use in the selection of a statin drug for the primary prevention of cardiovascular disease. We provide guidance on the key methodological issues of how to define the decision problem, how to select a set of nonoverlapping evaluation criteria, how to synthesize and summarize the evidence, how to translate relative measures to absolute ones that permit comparisons between the criteria, how to define suitable scale ranges, how to elicit partial preference information from the decision makers, and how to incorporate uncertainty in the analysis. Our example on statins indicates that fluvastatin is likely to be the most preferred drug by our decision maker and that this result is insensitive to the amount of preference information incorporated in the analysis

The SMAA-PROMETHEE method

Abstract: PROMETHEE methods are widely used in Multiple Criteria Decision Aiding (MCDA) to deal with real world decision making problems. In this paper, we propose to apply the Stochastic Multicriteria Acceptability Analysis (SMAA) to the family of PROMETHEE methods in order to explore the whole set of parameters compatible with some preference information provided by the Decision Maker (DM). The application of the presented methodology is described in a didactic example

Inducing a probability distribution in Stochastic Multicriteria Acceptability Analysis

In multiple criteria decision aiding, very often the alternatives are compared by means of a value function compatible with the preferences expressed by the Decision Maker. The problem is that, in general, there is a plurality of compatible value functions, and providing a final recommendation on the problem at hand considering only one of them could be considered arbitrary to some extent. For such a reason, Stochastic Multicriteria Acceptability Analysis gives information in statistical terms by taking into account a sample of models compatible with the provided preferences. These statistics are given assuming the existence of a probability distribution in the space of value functions being defined a priori. In this paper, we propose some methods aiming to build a probability distribution on the space of value functions considering the preference information given by the Decision Maker. To prove the goodness of our proposal we performed an extensive set of simulations. Moreover, a sensitivity analysis on the variables of our procedure has been done as well