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Data Descriptor

Information Competences and Academic Achievement: A Dataset

by
Jacqueline Köhler
* and
Roberto González-Ibáñez
Departamento de Ingeniería Informática, Universidad de Santiago de Chile, Avenida Víctor Jara #3659, Santiago 9170124, Chile
*
Author to whom correspondence should be addressed.
Data 2023, 8(11), 164; https://doi.org/10.3390/data8110164
Submission received: 3 August 2023 / Revised: 5 October 2023 / Accepted: 23 October 2023 / Published: 27 October 2023
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Abstract

Information literacy (IL) is becoming fundamental in the modern world. Although several IL standards and assessments have been developed for secondary and higher education, there is still no agreement about the possible associations between IL and both academic achievement and student dropout rates. In this article, we present a dataset including IL competences measurements, as well as academic achievement and socioeconomic indicators for 153 Chilean first- and second-year engineering students. The dataset is intended to allow researchers to use machine learning methods to study to what extent, if any, IL and academic achievement are related.
Keywords: information competences; academic achievement; machine learning information competences; academic achievement; machine learning

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MDPI and ACS Style

Köhler, J.; González-Ibáñez, R. Information Competences and Academic Achievement: A Dataset. Data 2023, 8, 164. https://doi.org/10.3390/data8110164

AMA Style

Köhler J, González-Ibáñez R. Information Competences and Academic Achievement: A Dataset. Data. 2023; 8(11):164. https://doi.org/10.3390/data8110164

Chicago/Turabian Style

Köhler, Jacqueline, and Roberto González-Ibáñez. 2023. "Information Competences and Academic Achievement: A Dataset" Data 8, no. 11: 164. https://doi.org/10.3390/data8110164

APA Style

Köhler, J., & González-Ibáñez, R. (2023). Information Competences and Academic Achievement: A Dataset. Data, 8(11), 164. https://doi.org/10.3390/data8110164

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