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How Educational Data Mining Empowers State Policies to Reform Education: The Mexican Case Study

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Educational Data Mining

Part of the book series: Studies in Computational Intelligence ((SCI,volume 524))

Abstract

In this chapter we present a case study that illustrates how educational data mining (EDM) is able to support the implementation of government policies and assist the labor of public institutions. Specifically, we highlight the current educational reforms in Mexico and focus on one of its main goals: to enhance the education quality. In response, a valuable data source is mined to discover interesting findings what students think about education, family, teachers, and their surroundings. Thus, a brief description of the legal and social context is given, as well as a profile of the students opinions expressed in a national survey is shaped. Moreover, a framework to build an EDM approach is outlined and a sample of the mined results is stated. As a result of the findings generated by the EDM approach, an interpretation is provided to tailor a conceptual view of the observations made by students, as well as some initiatives to deal with the findings. The work concludes with an exposition of the reasons for presenting this kind of work, a comment on the research fulfilled, a viewpoint of the education in Mexico, and some suggestions to support State polices to enhance education.

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Notes

  1. 1.

    Some acronyms maintain the initials written in Spanish to preserve their national identity.

  2. 2.

    The symbol/separates the category from its subcategory.

  3. 3.

    Waikato Environment for Knowledge Analysis.

Abbreviations

AIWBES:

Adaptive and intelligent web-based educational systems

CBIS:

Computer-based information systems

CNTE:

National Coordination of Workers of the Education

CPEUM:

Politic Constitution of the Mexican United States

CV:

Confidence value

DK:

Domain knowledge

DM:

Data mining

EDM:

Educational data mining

EM:

Expectation maximization

ENLACE:

National Evaluation of the Academic Achievement of Scholar Centers

ES:

Educational systems

EXCALE:

Exams for the Quality and Educative Achievements

INEE:

National Institute for Educative Evaluation

ITS:

Intelligent tutoring systems

KDD:

Knowledge discovery in databases

LCMS:

Learning content management systems

LMS:

Learning management systems

PISA:

Program for International Student Assessment

SAV:

Statistical Package for the Social Sciences data document

SEP:

Secretary of Public Education

SNTE:

National Union of Workers of the Education

SPS:

Statistical Package for the Social Sciences syntax

SPSS:

Statistical Package for the Social Sciences

SQL:

Structured Query Language

TXT:

Text data file

USA:

United States of America

WBC:

Web-based courses

XLSX:

Excel extended

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Acknowledgments

The first author gives testimony of the strength given by his Father, Brother Jesus, and Helper, as part of the research projects of World Outreach Light to the Nations Ministries (WOLNM). Moreover, a mention is given to Mr. Lawrence Whitehill Waterson, a native British English speaker who tunes the manuscript, as well as Aldo Ramírez Arellano for his edition support. In addition, a special mention is given to the Instituto Nacional para la Evaluación de la Educación for the publication of the source data used in this case study for exclusively research purposes. Finally, this research holds a partial support from grants given by: CONACYT-SNI-36453, CONACYT 118862, CONACYT 118962-162727, IPN-PIFI/20131093-28/1398, CONACYT 360532/289763. and IPN-COFAA-SIBE DEBEC/647-391/2013.

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Authors and Affiliations

  1. WOLNM: Artificial Intelligence on Education Lab, 31 Julio 1859 No. 1099-B, Leyes Reforma Mexico City, 09310, Mexico

    Alejandro Peña-Ayala

  2. ESIME Zacatenco, Instituto Politécnico Nacional, Building Z-4, 2nd Floor, Lab 6, Miguel Othón de Mendizábal S/N, México, DF, 07320, Mexico

    Alejandro Peña-Ayala & Leonor Cárdenas

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  1. Alejandro Peña-Ayala
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  2. Leonor Cárdenas
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Correspondence to Alejandro Peña-Ayala .

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  1. Escuela Superior de Ingeniería Mecánica y Eléctrica, Zacatenco (ESIME-Z), World Outreach Light to the Nations Ministries (WOLNM), Instituto Politécnico Nacional (IPN), Gustavo A. Madero, Mexico City, Distrito Federal, Mexico

    Alejandro Peña-Ayala

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Peña-Ayala, A., Cárdenas, L. (2014). How Educational Data Mining Empowers State Policies to Reform Education: The Mexican Case Study. In: Peña-Ayala, A. (eds) Educational Data Mining. Studies in Computational Intelligence, vol 524. Springer, Cham. https://doi.org/10.1007/978-3-319-02738-8_3

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