An Ensemble Predictive Model Based Prototype for Student Drop-out in Secondary Schools

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dc.contributor.author Mduma, Neema
dc.contributor.author Kalegele, Khamisi
dc.contributor.author Machuve, Dina
dc.date.accessioned 2019-10-04T06:56:04Z
dc.date.available 2019-10-04T06:56:04Z
dc.date.issued 2019-08-22
dc.identifier.issn 2468-4376
dc.identifier.uri https://doi.org/10.29333/jisem/5893
dc.identifier.uri http://dspace.nm-aist.ac.tz/handle/123456789/444
dc.description Research Article published by Journal of Information Systems Engineering & Management en_US
dc.description.abstract When a student is absent from school for a continuous number of days as defined by the relevant authority, that student is considered to have dropped out of school. In Tanzania, for instance, drop-out is when a student is absent continuously for a period of 90 days. Despite the fact that several efforts have been made to improve the overall status of education at secondary level, the student drop-out problem still persists. Taking advantage of advancement in technology, several studies have used machine learning to address the student drop-out problem. However, most of the conducted studies have used datasets from developed countries, while developing countries are facing challenges on generating public datasets to be used to address this problem. Using a dataset from Tanzania which reflect a local scenario; this study presents an ensemble predictive model based prototype for student drop-out in secondary schools. The deployed model was developed by soft combining a tuned Logistic Regression and Multi-Layer Perceptron models. A feature engineering experiment was conducted to obtain the most important features for predicting student drop-out. Furthermore, a visualization module was integrated to assist interpretation of the machine learning results and we used flask framework in the development of the prototype. en_US
dc.language.iso en_US en_US
dc.publisher Journal of Information Systems Engineering & Management en_US
dc.subject student drop-out en_US
dc.subject predictive model en_US
dc.subject machine learning en_US
dc.subject feature engineering experiment en_US
dc.subject visualization module en_US
dc.title An Ensemble Predictive Model Based Prototype for Student Drop-out in Secondary Schools en_US
dc.type Article en_US

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