ICTs and their impact on academic results: an analysis based on the TPACK model.

The integration of ICTs in the educational field has become an innovative tech nique for improving teaching-learning processes. This study aims to analyze the incidence of ICTs in the results of the Saber 11 tests applied in 2016, in Cun dinamarca and Bogotá. Since integrating ICTs in the classroom...

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Autores:
Morales Piñero, Juan Carlos
Cote Sánchez, María Carolina
Molina Bernal, Irma Amalia
Rodríguez Jerez, Sergio Alejandro
Tipo de recurso:
Part of book
Fecha de publicación:
2020
Institución:
Universidad Sergio Arboleda
Repositorio:
Repositorio U. Sergio Arboleda
Idioma:
eng
OAI Identifier:
oai:repository.usergioarboleda.edu.co:11232/1762
Acceso en línea:
http://hdl.handle.net/11232/1762
Palabra clave:
Rendimiento académico
Educación secundaria – Innovaciones tecnológicas
Tecnología educativa
Tecnología de la información
Métodos de enseñanza - Innovaciones tecnológicas
Mediciones y pruebas educativas
Academic achievement
Education, secondary - Technological innovations
Educational technology
Information technology
Teaching Methods - Technological innovations
Educational tests and measurements
TPACK
education
sector
teacher
Saber 11
socio-economic level
Rights
openAccess
License
Atribución-NoComercial-SinDerivadas 2.5 Colombia (CC BY-NC-ND 2.5 CO)
Description
Summary:The integration of ICTs in the educational field has become an innovative tech nique for improving teaching-learning processes. This study aims to analyze the incidence of ICTs in the results of the Saber 11 tests applied in 2016, in Cun dinamarca and Bogotá. Since integrating ICTs in the classroom should not be analyzed in isolation, the TPACK model will be taken as a frame of reference for this study. This model encompasses the two main components of education (pedagogy and content) and technology. A questionnaire was designed and applied to collect information on teachers’ competencies about the TPACK model. Li kewise, a quantitative analysis (linear regression and ANOVA) was proposed, taking the students’ average results, grouped by the institution, as an indepen dent variable. This allowed observing the variations of their behavior in contrast to the different independent variables. The relevance obtained by the students’ socio-economic family status (Sig. = 0,000) to explain the behavior of the inde pendent variable is highlighted, as well as the negative relationship between the technological infrastructure and the results obtained in the standardized tests of the government schools. In conclusion, the study corroborates previous research, stating that high socio-economic status institutions obtain better results than those of low status. However, the current integration of technology, pedagogy, and content is not relevant when explaining the Saber 11 test results.