Skip to main content
SpringerLink
Log in

Moving Towards a Methodology Employing Knowledge Discovery in Databases to Assist in Decision Making Regarding Academic Placement and Student Admissions for Universities

  • Conference paper
  • First Online:
Technology Trends (CITT 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 798))

Included in the following conference series:

Abstract

At institutions of higher education, data is generated daily. This massive amount of information is stored in different repositories, and it is increasingly difficult to locate specific data on which decisions can be made because universities are unaware of processes that allow for the extraction of valuable and reliable information. In this paper, we present a methodology that includes the Knowledge Discovery in Databases (KDD) coupled with the HEFESTO version 2.0 methodology for the construction of Data Warehouses and the use of Data Mining (DM) techniques. By implementing the proposed methodology, problems stemming from a lack of information relating to student placement and admissions in the UNAE and New Student Orientation (NSO) departments at the Polytechnic School of Chimborazo (ESPOCH) may be resolved. To accomplish this established goal, a Data Warehouse (DW) was implemented based on the requirements of the UNAE to find reliable information through cleaning and data integration techniques while respecting the Extraction, Transformation, and Load (ETL) process. In addition, several methods of DM were analyzed, culminating in the discovery of the pertinent information to ascertain the classification of students by areas of study, gender analysis, as well as to know the projection of the number of students who will commence university careers offered by ESPOCH in upcoming years.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    http://community.pentaho.com/projects/data-integration/.

  2. 2.

    http://www.postgresql.org.es/.

  3. 3.

    http://www.cs.waikato.ac.nz/ml/weka/.

References

  1. Fernández, T., Duarte, A., Hernández, R., Sánchez, Á.: GRASP aplicado al problema de la selección de instancias en KDD (2010)

    Google Scholar 

  2. Juan, I., Moine, M., Gordillo, D.S., Ana, D., Haedo, S.: Proyectos de minería de datos, pp. 931–938 (2011)

    Google Scholar 

  3. Asencios, V.V.: Data Mining y el descubrimiento del conocimiento. Ind. Data 7(2), 83–86 (2004)

    Article  Google Scholar 

  4. Fayyad, U., Piatetsky-Shapiro, G., Smyth, P.: From data mining to knowledge discovery in databases. AI Magazine 17(3), 37 (1996)

    Google Scholar 

  5. Maimon, O., Rokach, L.: Data Mining and Knowledge Discovery Handbook, pp. 22–38. Springer, Boston (2010). https://doi.org/10.1007/978-0-387-09823-4

    Book  MATH  Google Scholar 

  6. Aluja, T.: La Minería de Datos, entre la Estadística y la Inteligencia Artificial. Qüestiió 25(3), 479–498 (2001)

    MathSciNet  Google Scholar 

  7. Daza Vergaraym, A.: Data Mining, Minería de Datos, Primera. Editorial Macro, Lima (2016)

    Google Scholar 

  8. Moine, M., Haedo, S., Gordillo, D.S.: Estudio comparativo de metodologías para minería de datos. XVII Congreso Argentino de Ciencias de la Computación, CACIC 2011 (2011). http://sedici.unlp.edu.ar/bitstream/handle/10915/20034/Documento_completo.pdf?sequence=1. Accessed 03 Dec 2015

  9. Inmon, B.: Building the Datawarehouse. Wiley Computer Publishing, New York (1998)

    Google Scholar 

  10. Kimball, R.: The Datawarehouse Toolkit. Wiley Computer Publishing, New York (1996)

    Google Scholar 

  11. Inmon, B.: Data warehousing 2.0 modeling and metadata strategies for next generation architectures. In: Architecture, p. 13 (2010)

    Google Scholar 

  12. Bernabeu, R.: Hefesto, p. 146 (2010)

    Google Scholar 

  13. Bradley, P., Fayyad, U.M., Mangasarian, O.: Data mining: overview and optimization opportunities. INFORMS J. Comput. 11, 217–238 (1999)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Pontificia Universidad Católica del Ecuador, Sede Ambato, Ambato, Ecuador

    María Isabel Uvidia Fassler & Diego Fernando Ávila-Pesántez

  2. Escuela Superior Politécnica de Chimborazo, Riobamba, Ecuador

    Andrés Santiago Cisneros Barahona, Diego Fernando Ávila-Pesántez & Ivonne Elizabeth Rodríguez Flores

  3. Universidad Nacional de Chimborazo, Riobamba, Ecuador

    María Isabel Uvidia Fassler & Andrés Santiago Cisneros Barahona

Authors
  1. María Isabel Uvidia Fassler
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andrés Santiago Cisneros Barahona
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Diego Fernando Ávila-Pesántez
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ivonne Elizabeth Rodríguez Flores
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to María Isabel Uvidia Fassler .

Editor information

Editors and Affiliations

  1. Eindhoven University of Technology, Eindhoven, The Netherlands

    Miguel Botto-Tobar

  2. Universidad Técnica de Babahoyo, Babahoyo, Ecuador

    Nelly Esparza-Cruz

  3. Universidad Técnica de Babahoyo, Babahoyo, Ecuador

    Joffre León-Acurio

  4. Universidad Técnica de Babahoyo, Babahoyo, Ecuador

    Narcisa Crespo-Torres

  5. Universidad Técnica de Babahoyo, Babahoyo, Ecuador

    Marola Beltrán-Mora

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Uvidia Fassler, M.I., Cisneros Barahona, A.S., Ávila-Pesántez, D.F., Rodríguez Flores, I.E. (2018). Moving Towards a Methodology Employing Knowledge Discovery in Databases to Assist in Decision Making Regarding Academic Placement and Student Admissions for Universities. In: Botto-Tobar, M., Esparza-Cruz, N., León-Acurio, J., Crespo-Torres, N., Beltrán-Mora, M. (eds) Technology Trends. CITT 2017. Communications in Computer and Information Science, vol 798. Springer, Cham. https://doi.org/10.1007/978-3-319-72727-1_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-72727-1_16

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-72726-4

  • Online ISBN: 978-3-319-72727-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation