There is a newer version of the record available.

Published June 26, 2018 | Version v1
Dataset Open

Psychosocial Risk Level Teachers School Repository 2016-2017

Creators

  • 1. National University of Colombia

Contributors

  • 1. Ph.D National University of Colombia
  • 2. Researcher National University of Colombia
  • 3. Reasearcher Private University of Colombia

Description

The database was created with 5344 records of psychosocial risk level colombian teachers school using physiological variables from May 2016 to December 2017 in five municipalities of a metropolitan area of city in Colombia. The application of physiological variables was made to the people who voluntarily participated in the study. The names and personal data were kept by the researcher.

Notes

The repository contains two datasets, one of the total population and a sample of the population to which associated physiological variables were evaluated. 1. The First dataset: -- Number of Instances: 5444 -- Number of Attributes: 115 (114 predictive attributes, 1 class) The second dataset --Number of instances: 481 --Number of attributes: 120 (119 predictive attributes, 1 class)

Files

Psychosocial Risk Assessment Level Colombian Teachers School HR, EDA, EMG.csv

Files (1.6 MB)

Additional details

References

  • Mosquera, R., Parra-Osorio, L., & Castrillón, O. D. (2018). Support Vector Machines, Naïve Bayes Classifier and Genetic Algorithms for the Prediction of Psychosocial Risks in Teachers of Colombian Public Schools. Inf. tecnol. vol.29, n.6, pp.153-162. http://dx.doi.org/10.4067/S0718-07642018000600153.
  • Mosquera, R., Parra-Osorio, L., & Castrillón, O. D. (2018). Prediction of Psychosocial Risks in Colombian Teachers of Public Schools using Machine Learning Techniques. Inf. tecnol. vol.29, n.4, pp.267-280. http://dx.doi.org/10.4067/S0718-07642018000400267.
  • Mosquera, R., Parra-Osorio, L., & Castrillón, O. D. (2016). Methodology for Predicting the Psychosocial Risk Level on Colombian Teachers using Data Mining Techniques. Inf. tecnol. vol.27, n.6, pp.259-272. http://dx.doi.org/10.4067/S0718-07642016000600026.
  • Mosquera Navarro, R., Castrillón, O. D. G., Osorio, L. P., & García, A. C. (2018). Classification system for the predicting of psychosocial risk level in public-school teachers based on Artificial Intelligence. XVIII Conferencia de La Asociación Española Para La Inteligencia Artificial (CAEPIA), 1367-1372.
  • Mosquera, R, Castrillón Gómez, O. D., & Parra-Osorio, L. (2019a). A new method based on Physical Surface Tension-Neural Net for the Prediction of Psychosocial-risk Level in Public School Teachers. (Versión 1) [Matlab]. Recuperado de https://doi.org/10.24433/CO.4268666.v1
  • Mosquera, R, Castrillón Gómez, O. D., & Parra-Osorio, L. (2019b). Aplicación del modelo hibrido k-nearest neighbors-Support Vector Machine para la predicción del riesgo psicosocial en docentes de colegios públicos colombianos. Presentado en 17th LACCEI International Multi-Conference for Engineering, Education, and Technology: "Industry, Innovation, And Infrastructure for Sustainable Cities and Communities", Jamaica. Recuperado de http://www.laccei.org/index.php/publications/laccei-proceedings