Educational software in the academic performance of students at the Amazonian State University, Ecuador

Descripción del Articulo

Low performance in Mathematics I at the Amazonian State University (UEA) highlighted the need to implement technological solutions to optimize learning. The study aimed to evaluate the impact of educational software on the academic performance of first-semester students. Using a quasi-experimental d...

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Detalles Bibliográficos
Autores: Zambrano-Vera, David, Zambrano-Tapia, Jennifer, Del Corral-Villarroel, Víctor, Vinocunga-Pillajo, Reni
Formato: artículo
Fecha de Publicación:2024
Institución:Instituto Universitario de Innovación Ciencia y Tecnología Inudi Perú
Repositorio:Revista Innova Educación
Lenguaje:español
OAI Identifier:oai:ojs2.revistainnovaeducacion.com:article/1020
Enlace del recurso:https://revistainnovaeducacion.com/index.php/rie/article/view/1020
Nivel de acceso:acceso abierto
Materia:evaluación del estudiante
innovación en enseñanza
rendimiento académico
software educativo
tecnología educacional
academic performance
educational software
educational technology
student assessment
teaching innovation
avaliação do estudante
desempenho acadêmico
inovação no ensino
tecnologia educacional
Descripción
Sumario:Low performance in Mathematics I at the Amazonian State University (UEA) highlighted the need to implement technological solutions to optimize learning. The study aimed to evaluate the impact of educational software on the academic performance of first-semester students. Using a quasi-experimental design, a total of 121 participants were divided into an experimental group (EG) with 29 students and a control group (CG) with 31 students, which were used without modifications. Participants were assessed through questionnaires and written tests, alongside an initial interview with the program director. The analysis methods included Fisher-Snedecor and t-Student tests to compare the groups. The results showed that both groups had homogeneous levels in the initial Pretest (mean scores of 7.4140 and 7.0323, respectively), ensuring equitable conditions before the intervention. At the end of the study, the EG achieved a significantly higher mean score in the Postest (14.0690 versus 10.4194 for the CG), demonstrating a positive impact of the software on learning. Additionally, 86.21% of the students reported increased motivation, and 79.31% highlighted improvements in teacher-student interaction. These results suggest that educational software is effective in overcoming the limitations of traditional methods. To apply it in other contexts, it is essential to ensure adequate technological infrastructure, train teachers in digital competencies, and design content tailored to the specific needs of students, considering both their initial preparation level and learning styles.
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