International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

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 Volume 9, Issue 9 (September 2022), Pages: 70-77

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 Original Research Paper

 Centroid competitive learning approach for clustering and mapping the social vulnerability in Morocco

 Author(s): Ilyas Tammouch 1, *, Abdelamine Elouafi 1, Souad Eddarouich 2, Raja Touahni 1

 Affiliation(s):

 1Faculty of Science, Telecommunications Systems and Decision Engineering Laboratory, Ibn Tofail University, Kenitra, Morocco
 2Regional Educational Center, Rabat, Morocco

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 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0003-2752-4413

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2022.09.009

 Abstract:

Over the last three decades, growing inequalities in countries have compounded the issues faced by society's most vulnerable populations. Students are facing the brunt of the effects in particular. A student's social vulnerability emerges as a result of the interaction of a variety of individual and environmental factors that accumulate over time. Poverty, material deprivation, and a lack of parental education can all have an impact on student assessment in school. Previous research has focused on the impact of psychological, cognitive, and physical functioning on children's education, ignoring students’ social vulnerability and its impact on educational achievements in developing countries. This paper aims to identify vulnerable regions that need attention and intervention by clustering Moroccan students based on their social vulnerability using an unsupervised competitive learning approach “Centroid neural network,” subsequently displaying the results in a choropleth map to visualize the results. For this purpose, we used the PISA dataset which contains the full set of responses from individual students focusing on specific information such as their parent’s backgrounds, socioeconomic position, and school conditions. Based on our current findings, we concluded that social vulnerability has a detrimental impact on students’ cognitive development. Moreover, the choropleth map shows that 'Beni Mellal-Khenifra' has the highest level of social vulnerability among all regions, besides "Marrakech-Safi" "Eddakhla-Oued Eddahab" and "Guelmim-Oued Noun" all of which have a high level of social vulnerability as well, urging academicians to incorporate resilience building into the design of policies in these regions in order to improve student’s educational outcomes.

 © 2022 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Student’s social vulnerability, Centroid neural network, Choropleth map, Distance, Clustering

 Article History: Received 9 March 2022, Received in revised form 8 June 2022, Accepted 10 June 2022

 Acknowledgment 

No Acknowledgment.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Tammouch I, Elouafi A, and Eddarouich S et al. (2022). Centroid competitive learning approach for clustering and mapping the social vulnerability in Morocco. International Journal of Advanced and Applied Sciences, 9(9): 70-77

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 Figures

 Fig. 1 Fig. 2 Fig. 3

 Tables

 Table 1 Table 2 Table 3 Table 4 Table 5

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