Using word processing techniques for extracting professional skills and competencies from state university profiles in Costa Rica

Using word processing techniques for extracting professional skills and competencies from state university profiles in Costa Rica

Authors

DOI:

https://doi.org/10.22458/ie.v24i36.3818

Keywords:

random variable, probability distribution, education theory, teaching of statistics, secondary education, education

Abstract

The random variable and its probability distribution are fundamental concepts in statistical and probabilistic school education because they manifest in everyday experiences. Teaching them becomes a complex task due primarily to the difficulties associated with understanding them and the concept of function. Therefore, we proposed as a study objective to assess the random variable's instruction process and its probability distribution in Chilean secondary education, based on the Theory of Didactic Situations (TSD) and the Theory of Registration of Semiotic Representations (TRRS). We designed a test containing a didactic situation applied to 10th-grade Chilean students (15 to 16 years old) with a qualitative perspective and a descriptive-interpretive approach. The findings showed that more than half of the students (64%) managed to identify and represent the random variable in verbal, figural, or tabular language, and a similar percentage (59%), its probability distribution. Concerning the TRRS, this could indicate that students are in the process of building both objects. Subsequently from the TSD, we observed the vital role that the teacher played in the phases of the said didactic situation. Studying didactic theories, we discovered that bringing complex objects to the classroom can help actual teachers and those being trained to look at their practice with more understructure to make it more accessible and understandable to their students.

Author Biographies

Paola Chaves Bonilla, Observatorio Laboral de Profesiones

Paola Chaves Bonilla

Observatorio Laboral de Profesiones

San José, Costa Rica

pchaves@conare.ac.cr

ORCID: https://orcid.org/0000-0001-7017-328X

Carlos Gamboa-Venegas, Centro Nacional de Alta Tecnología

Carlos Gamboa-Venegas

Centro Nacional de Alta Tecnología

San José, Costa Rica

cgamboa@cenat.ac.cr

ORCID: https://orcid.org/0000-0001-9712-0575

Katherine Sandí Araya, Observatorio Laboral de Profesiones

Katherine Sandí Araya

Observatorio Laboral de Profesiones

San José, Costa Rica

ksandi@conare.ac.cr

ORCID: https://orcid.org/0000-0001-8129-3826

Karen Corrales Bolívar, Observatorio Laboral de Profesiones

Karen Corrales Bolívar

Observatorio Laboral de Profesiones

San José, Costa Rica

kcorrales@conare.ac.cr

ORCID: https://orcid.org/0000-0002-2979-2190

Javier Herrera Mora, Centro Nacional de Alta Tecnología

Javier Herrera Mora

Centro Nacional de Alta Tecnología

San José, Costa Rica

javier.herreramora11@gmail.com

ORCID: https://orcid.org/0000-0003-2906-502X

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Published

2022-01-24

How to Cite

Chaves Bonilla, P., Gamboa-Venegas, C., Sandí Araya, K., Corrales Bolívar, K., & Herrera Mora, J. (2022). Using word processing techniques for extracting professional skills and competencies from state university profiles in Costa Rica. Innovaciones Educativas, 24(36), 7–20. https://doi.org/10.22458/ie.v24i36.3818
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