Data analitics applied to the study of student dropout at the Pedagogical and Technological University of Colombia - UPTC
Keywords:
Social analysis, semantic annotation, API, information indexingAbstract
This work presents the application of data science techniques aimed at the prediction of student dropout patterns whose case study corresponds to structured information in the sectional UPTC-Duitama. In the application of data science, specialized algorithms were applied for the development of prediction models and data analysis is used. Additionally, a data set was structured whose content has been prepared to be trained. The final result of the research presents a predictive model obtained by means of data science techniques and that was validated by several quality metrics that show the quality of the final model obtained.
References
Downloads
Published
Issue
Section
License
Authors who publish in this journal agree to the following terms:
a. Authors give their rights to the article in a non-exclusive way for the magazine to be published for the first time by the journal as well as licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of authorship of work and initial publication in this magazine.
b. Authors can establish separate additional agreements for non-exclusive distribution of the version of the work published in the journal (for example, to an institutional repository or to publish it in a book), with an acknowledgment of its initial publication in this journal.
c. Authors are allowed and encouraged to disseminate their work electronically (e.g., in institutional repositories or your own website) prior to and during the submission process, as it can lead to productive exchanges, as well as a citation more early and most of published work (See the Effect of Open Access) (in English).
