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Open AccessArticle

Application of Computational Intelligence to Improve Education in Smart Cities

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Electrical Engineering and Computer College, State University of Campinas, Av. Albert Einsten, 400, Cidade Universitária Zeferino Vaz, Distrito Barão Geraldo, Campinas 13083-852 SP, Brazil
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Computer Science Department, State University of Londrina, Rod. Celso Garcia Cid, Km 380, s/n, Campus Universitário, Londrina 86057-970 PR, Brazil
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Author to whom correspondence should be addressed.
Sensors 2018, 18(1), 267; https://doi.org/10.3390/s18010267
Received: 30 November 2017 / Revised: 8 January 2018 / Accepted: 14 January 2018 / Published: 18 January 2018
(This article belongs to the Special Issue Sensing, Data Analysis and Platforms for Ubiquitous Intelligence)
According to UNESCO, education is a fundamental human right and every nation’s citizens should be granted universal access with equal quality to it. Because this goal is yet to be achieved in most countries, in particular in the developing and underdeveloped countries, it is extremely important to find more effective ways to improve education. This paper presents a model based on the application of computational intelligence (data mining and data science) that leads to the development of the student’s knowledge profile and that can help educators in their decision making for best orienting their students. This model also tries to establish key performance indicators to monitor objectives’ achievement within individual strategic planning assembled for each student. The model uses random forest for classification and prediction, graph description for data structure visualization and recommendation systems to present relevant information to stakeholders. The results presented were built based on the real dataset obtained from a Brazilian private k-9 (elementary school). The obtained results include correlations among key data, a model to predict student performance and recommendations that were generated for the stakeholders. View Full-Text
Keywords: computational intelligence; smart education; smart city, adaptive learning; creative school; self-learning computational intelligence; smart education; smart city, adaptive learning; creative school; self-learning
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MDPI and ACS Style

Gomede, E.; Gaffo, F.H.; Briganó, G.U.; De Barros, R.M.; Mendes, L.D.S. Application of Computational Intelligence to Improve Education in Smart Cities. Sensors 2018, 18, 267.

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