Acosta de La Cruz, Pedro R.Flores Salinas, José A.Meza Pinto, Miguel A.Tineo Córdova, Freddy C.2023-05-192023-05-192016-10-26Acosta de La Cruz, P. R., Flores Salinas, J. A., Meza Pinto, M. A., & Tineo Córdova, F. C. (2016). A prediction model based on data mining to forecast the expectations of passing from a college student. International Journal of Engineering Research & Technology, 5(10), 530-533. https://doi.org/10.17577/IJERTV5IS100394https://hdl.handle.net/20.500.12640/3399The present work has as objective to apply data mining techniques to develop a predictive model to forecast the chance of passing that will have a college student at the time of enrolling in a particular subject. Given that the academic record of the student can be known, and based on that information, we propose an Artificial Neural Network (ANN) that allows, using various configurations, to predict and assess our goal. The model has been applied to a compulsory subject of higher education of a University and given the results obtained. This model can be applied to any other subject analogous with satisfactory results.application/pdfengAttribution 4.0 Internationalinfo:eu-repo/semantics/openAccessArtificial neural networksData miningHigher educationPredictive techniquesRedes neuronales artificialesMinería de datosEducación superiorTécnicas predictivasinfo:eu-repo/semantics/articlehttps://doi.org/10.17577/IJERTV5IS100394https://purl.org/pe-repo/ocde/ford#2.00.00