The knowledge discovery through the student's higher education census data

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The Higher Education Institutions have become the object of renewed interest [1, 2] as they hold the key to the knowledge-based economy and society [3] and have encompassed what is considered their third mission. They are confronted with a more diverse generation of students [4], identified by a heterogeneous group concerning age, sex, socioeconomic status, race, ethnic, motivation, expectations and personal projects [5]. Concerning that knowledge is the main driver for future social and economic development in the Knowledge Economy and Society, this paper adopts an inductive and exploratory methodological approach to analyze the student's data from Brazilian Higher Education Census. It uses Self-organizing Maps (SOM) that is a type of neural network which deals which a massive volume of data to explore patterns hidden in the data, focusing on knowledge discovery. The results allow us to visualize five different profiles, based on their OECD main areas of preference, dependence on financial funding, genre and academic status (entrant, enrolled and undergraduate).

Original languageEnglish
Title of host publicationProceedings of CISTI 2018
Subtitle of host publication13th Iberian Conference on Information Systems and Technologies [Memorias de la CISTI 2018: 13a Conferencia Iberica de Sistemas y Tecnologias de Informacion]
PublisherIEEE Computer Society
Pages1-6
Number of pages6
Volume2018
ISBN (Electronic)9789899843486
DOIs
Publication statusPublished - 27 Jun 2018
Event13th Iberian Conference on Information Systems and Technologies, CISTI 2018 - Caceres, Spain
Duration: 13 Jun 201816 Jun 2018

Conference

Conference13th Iberian Conference on Information Systems and Technologies, CISTI 2018
CountrySpain
CityCaceres
Period13/06/1816/06/18

Fingerprint

Data mining
Education
Students
Self organizing maps
Neural networks
Economics

Keywords

  • Higher education
  • Knowledge discovery
  • Self-organizing Map - SOM
  • Students profile

Cite this

de Campos, S. R. M., & Henriques, R. (2018). The knowledge discovery through the student's higher education census data. In Proceedings of CISTI 2018: 13th Iberian Conference on Information Systems and Technologies [Memorias de la CISTI 2018: 13a Conferencia Iberica de Sistemas y Tecnologias de Informacion] (Vol. 2018, pp. 1-6). IEEE Computer Society. https://doi.org/10.23919/CISTI.2018.8399164
de Campos, Silvia Regina Machado ; Henriques, Roberto. / The knowledge discovery through the student's higher education census data. Proceedings of CISTI 2018: 13th Iberian Conference on Information Systems and Technologies [Memorias de la CISTI 2018: 13a Conferencia Iberica de Sistemas y Tecnologias de Informacion]. Vol. 2018 IEEE Computer Society, 2018. pp. 1-6
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abstract = "The Higher Education Institutions have become the object of renewed interest [1, 2] as they hold the key to the knowledge-based economy and society [3] and have encompassed what is considered their third mission. They are confronted with a more diverse generation of students [4], identified by a heterogeneous group concerning age, sex, socioeconomic status, race, ethnic, motivation, expectations and personal projects [5]. Concerning that knowledge is the main driver for future social and economic development in the Knowledge Economy and Society, this paper adopts an inductive and exploratory methodological approach to analyze the student's data from Brazilian Higher Education Census. It uses Self-organizing Maps (SOM) that is a type of neural network which deals which a massive volume of data to explore patterns hidden in the data, focusing on knowledge discovery. The results allow us to visualize five different profiles, based on their OECD main areas of preference, dependence on financial funding, genre and academic status (entrant, enrolled and undergraduate).",
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de Campos, SRM & Henriques, R 2018, The knowledge discovery through the student's higher education census data. in Proceedings of CISTI 2018: 13th Iberian Conference on Information Systems and Technologies [Memorias de la CISTI 2018: 13a Conferencia Iberica de Sistemas y Tecnologias de Informacion]. vol. 2018, IEEE Computer Society, pp. 1-6, 13th Iberian Conference on Information Systems and Technologies, CISTI 2018, Caceres, Spain, 13/06/18. https://doi.org/10.23919/CISTI.2018.8399164

The knowledge discovery through the student's higher education census data. / de Campos, Silvia Regina Machado; Henriques, Roberto.

Proceedings of CISTI 2018: 13th Iberian Conference on Information Systems and Technologies [Memorias de la CISTI 2018: 13a Conferencia Iberica de Sistemas y Tecnologias de Informacion]. Vol. 2018 IEEE Computer Society, 2018. p. 1-6.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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AB - The Higher Education Institutions have become the object of renewed interest [1, 2] as they hold the key to the knowledge-based economy and society [3] and have encompassed what is considered their third mission. They are confronted with a more diverse generation of students [4], identified by a heterogeneous group concerning age, sex, socioeconomic status, race, ethnic, motivation, expectations and personal projects [5]. Concerning that knowledge is the main driver for future social and economic development in the Knowledge Economy and Society, this paper adopts an inductive and exploratory methodological approach to analyze the student's data from Brazilian Higher Education Census. It uses Self-organizing Maps (SOM) that is a type of neural network which deals which a massive volume of data to explore patterns hidden in the data, focusing on knowledge discovery. The results allow us to visualize five different profiles, based on their OECD main areas of preference, dependence on financial funding, genre and academic status (entrant, enrolled and undergraduate).

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de Campos SRM, Henriques R. The knowledge discovery through the student's higher education census data. In Proceedings of CISTI 2018: 13th Iberian Conference on Information Systems and Technologies [Memorias de la CISTI 2018: 13a Conferencia Iberica de Sistemas y Tecnologias de Informacion]. Vol. 2018. IEEE Computer Society. 2018. p. 1-6 https://doi.org/10.23919/CISTI.2018.8399164