Abstract
In search of intelligent solutions that could help improve teaching in higher education, we discovered a set of analyzes that had already been discussed and just needed to be implemented. We believe that this reality can be found in several educational institutions, with paper or mini-projects that deal with educational data and can have positive impacts on teaching. Because of this, we designed an architecture that could extract from multiple sources of educational data and support the implementation of some of these projects found. The results show an important tool that can contribute positively to the teaching institution. Effectively, we can highlight that the implementation of a predictive model of students at risk of dropping out will bring a new analytical vision. Also, the system’s practicality will save managers a lot of time in creating analyzes of the state of the institutions, respecting privacy concerns of the manipulated data, supported by a secure development methodology.
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Acknowledgment
This work was supported by FCT - Fundação para a Ciência e a Tecnologia under Project UIDB/05757/2020 and Cognita Project (project number NORTE-01-0247-FEDER-038336), funded by the Norte 2020 - Norte’s Regional Operational Programme, Portugal 2020 and the European Union, through the European Regional Development Fund.
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Franco, T., Alves, P., Pedrosa, T., Varanda Pereira, M.J., Canão, J. (2021). Implementation of Big Data Analytics Tool in a Higher Education Institution. In: Rocha, Á., Adeli, H., Dzemyda, G., Moreira, F., Ramalho Correia, A.M. (eds) Trends and Applications in Information Systems and Technologies. WorldCIST 2021. Advances in Intelligent Systems and Computing, vol 1365. Springer, Cham. https://doi.org/10.1007/978-3-030-72657-7_20
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