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A Model for Faculty Evaluation in Higher Education Ecuadorian through Multi-Criteria Decision Analysis


Affiliations
1 School of Computer Science, Department of Systems Engineering, Quevedo State Technical University, Km 1.5 Santo Domingo de los Tsachilas – 120501, Quevedo – Los Rios – Ecuador
2 Department of Electrical Engineering, Quevedo State Technical University, Km 1.5 Santo Domingo de los Tsachilas – 120501, Quevedo – Los Rios – Ecuador
 

Objectives: To obtain a model based in Multi-Criteria Decision Making (MCDM) for the teacher ranking of an Ecuadorian University. Methods/Analysis: The model is adjusted to both governmental and institutional regulations; secondly we analyze the quality requirements of control state institutions and finally, in order structuring the problem through trees of hierarchical objectives according informant type and the modeling of preferences is necessary to get good utility functions; for that use attributes defined by the same university and state control institutions for the higher education with qualitative and quantitative scales. Findings: We obtain the evaluation model for the university professor supported by the concept of multiple criteria such as administrative management, research, teaching and community engagement, the qualitative/quantitative attributes are transformed by the definition of utility functions at intervals between 0 and 1; the established functions come from evaluation models established by the control institutions and the modeling of preferences. In addition, hierarchical target trees are defined for informants such as students, teachers, authorities and peers. Application/Improvement: The Quevedo State Technical University has obtained a model of support decision making for the classification of teachers. This could be implemented through software.

Keywords

Decision Analysis, Education Ecuadorian, Faculty Evaluation, MCDM, Teaching Quality
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  • A Model for Faculty Evaluation in Higher Education Ecuadorian through Multi-Criteria Decision Analysis

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Authors

Ivan F. Jaramillo
School of Computer Science, Department of Systems Engineering, Quevedo State Technical University, Km 1.5 Santo Domingo de los Tsachilas – 120501, Quevedo – Los Rios – Ecuador
Roberto B. Pico
Department of Electrical Engineering, Quevedo State Technical University, Km 1.5 Santo Domingo de los Tsachilas – 120501, Quevedo – Los Rios – Ecuador
Carlos V. Marquez De La Plata
Department of Electrical Engineering, Quevedo State Technical University, Km 1.5 Santo Domingo de los Tsachilas – 120501, Quevedo – Los Rios – Ecuador

Abstract


Objectives: To obtain a model based in Multi-Criteria Decision Making (MCDM) for the teacher ranking of an Ecuadorian University. Methods/Analysis: The model is adjusted to both governmental and institutional regulations; secondly we analyze the quality requirements of control state institutions and finally, in order structuring the problem through trees of hierarchical objectives according informant type and the modeling of preferences is necessary to get good utility functions; for that use attributes defined by the same university and state control institutions for the higher education with qualitative and quantitative scales. Findings: We obtain the evaluation model for the university professor supported by the concept of multiple criteria such as administrative management, research, teaching and community engagement, the qualitative/quantitative attributes are transformed by the definition of utility functions at intervals between 0 and 1; the established functions come from evaluation models established by the control institutions and the modeling of preferences. In addition, hierarchical target trees are defined for informants such as students, teachers, authorities and peers. Application/Improvement: The Quevedo State Technical University has obtained a model of support decision making for the classification of teachers. This could be implemented through software.

Keywords


Decision Analysis, Education Ecuadorian, Faculty Evaluation, MCDM, Teaching Quality



DOI: https://doi.org/10.17485/ijst%2F2017%2Fv10i18%2F149839