LearningRlab: Educational R Package for Statistics in Computer Science Engineering

Author:

Cuadrado-Gallego Juan J.12ORCID,Gómez Josefa1ORCID,Tayebi Abdelhamid1ORCID,Usero Luis1ORCID,Hellín Carlos J.1ORCID,Valledor Adrián1ORCID

Affiliation:

1. Computer Sciences Department, University of Alcalá, 28801 Alcalá de Henares, Spain

2. Department of Computer Science and Software Engineering, Concordia University, Montreal, QC H3G 2J1, Canada

Abstract

This paper describes and evaluates the educational interest of LearningRlab, an educational R package developed for teaching statistics in computer science engineering. The package was developed by final degree project students to be used as an educational environment for statistics students who evaluated the package and provided feedback for future versions. Such a process increases the motivation of both groups of students. This paper presents how the use of the R packages conceived and developed for engineering education can improve the learning process in the computer science engineering bachelor’s degree. Two different evaluations, one performed by a group of statistics students, and the other performed by final degree project students, were used to evaluate the impact on the learning process of the first version of the package to develop the second version of the package, which corrects and enhances the first version. The evaluation results show a positive effect on the learning process in both subjects. The analysis of the learning outcomes reflected in the grades of the experimental and control groups demonstrates that LearningRlab can be used as a teaching aid for statistics and final degree project subjects of the computer science engineering degree. The average laboratory grade of the students who used the package (5.76) was noticeably higher than the average laboratory grade of students who did not use it (1.84).

Funder

University of Alcala

Comunidad de Madrid

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

Reference22 articles.

1. Gómez, J.M., Monheimius, D., Benito, E., and Cuadrado-Gallego, J. (2023, April 03). Introduction to LearningRlab. Available online: https://cran.r-project.org/web/packages/LearningRlab/vignettes/learningRlab.html.

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3. IncDTW: An R Package for Incremental Calculation of Dynamic Time Warping;Leodolter;J. Stat. Softw.,2021

4. CoClust: A Python Package for Co-Clustering;Role;J. Stat. Softw.,2019

5. Millard, S. (2023, April 03). EnvStats: An R Package for Environmental Statistics. Available online: http://www.springer.com/book/9781461484554.

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