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A big data based method for pass rates optimization in mathematics university lower division courses

Author

Listed:
  • Fernando A Morales
  • Cristian C Chica
  • Carlos A Osorio
  • Daniel Cabarcas J

Abstract

In this paper an algorithm designed for large databases is introduced for the enhancement of pass rates in mathematical university lower division courses with several sections. Using integer programming techniques, the algorithm finds the optimal pairing of students and lecturers in order to maximize the success chances of the students' body. The students-lecturer success probability is computed according to their corresponding profiles stored in the data bases.

Suggested Citation

  • Fernando A Morales & Cristian C Chica & Carlos A Osorio & Daniel Cabarcas J, 2018. "A big data based method for pass rates optimization in mathematics university lower division courses," Papers 1809.09724, arXiv.org, revised Oct 2020.
    • Handle: RePEc:arx:papers:1809.09724
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    References listed on IDEAS

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    4. Giacomo De Giorgi & Michele Pellizzari & William Gui Woolston, 2012. "Class Size And Class Heterogeneity," Journal of the European Economic Association, European Economic Association, vol. 10(4), pages 795-830, August.
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