How Educational Data Mining Empowers State Policies to Reform Education: The Mexican Case Study
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
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How Educational Data Mining Empowers State Policies to Reform Education: The Mexican Case Study Alejandro Peña-Ayala and Leonor Cárdenas
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.
Keywords Data mining Knowledge discovery in databases Educational data mining Educational policies Student opinions Clustering Association rules
Abbreviations AIWBES CBIS
Adaptive and intelligent web-based educational systems Computer-based information systems
A. Peña-Ayala (&) WOLNM: Artificial Intelligence on Education Lab, 31 Julio 1859 No. 1099-B, Leyes Reforma Mexico City 09310, Mexico e-mail: [email protected]; [email protected] A. Peña-Ayala L. Cárdenas ESIME Zacatenco, Instituto Politécnico Nacional, Building Z-4, 2nd Floor, Lab 6, Miguel Othón de Mendizábal S/N, México, DF 07320, Mexico e-mail: [email protected]
A. Peña-Ayala (ed.), Educational Data Mining, Studies in Computational Intelligence 524, DOI: 10.1007/978-3-319-02738-8_3, Springer International Publishing Switzerland 2014
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CNTE CPEUM CV DK DM EDM EM ENLACE ES EXCALE INEE ITS KDD LCMS LMS PISA SAV SEP SNTE SPS SPSS SQL TXT USA WBC XLSX
A. Peña-Ayala and L. Cárdenas
National Coordination of Workers of the Education Politic Constitution of the Mexican United States Confidence value Domain knowledge Data mining Educational data mining Expectation maximization National Evaluation of the Academic Achievement of Scholar Centers Educational systems Exams for the Quality and Educative Achievements National Institute for Educative Evaluation Intelligent tutoring systems Knowledge discovery in databases Learning content management systems Learning management systems Program for International Student Assessment Statistical Package for the Social Sciences data document Secretary of Public Education National Union of Workers of the Education Statistical Package for the Social Sciences syntax Statistical Pac
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