Rendimiento académico de los estudiantes de la carrera de Computación de la ESPAM MFL: Un análisis comparativo de las modalidades de aprendizaje y factores demográficos

• Ramón Joffre Moreira Pico ^[1] ; María Belén Villao Loor ^[1] ; Ramón Agustín Varela Muñoz ^[1] ; Ángel Alberto Vélez Mero ^[1]
  1. [1] Escuela Superior Politécnica Agropecuaria de Manabí, Campus Politécnico Sitio El Limón, Ecuador.
• Localización: RISTI: Revista Ibérica de Sistemas e Tecnologias de Informação, ISSN-e 1646-9895, Nº. Extra 61, 2023, págs. 352-369
• Idioma: español
• Títulos paralelos:
  • Academic performance of students in the Computing major at ESPAM MFL: A comparative analysis of learning modalities and demographic factors
• Enlaces
  • Texto completo (pdf)
• Resumen
  • español

    Este estudio analiza el rendimiento académico en la carrera de Computación de la ESPAM MFL, considerando siete períodos académicos y distintas modalidades de aprendizaje. Se utilizó una base de datos con información demográfica y calificaciones finales de los estudiantes. Se aplicaron análisis descriptivos, pruebas de normalidad, comparaciones de grupos y análisis de correlaciones. El objetivo fue examinar las calificaciones en función de las modalidades de aprendizaje y su impacto en el rendimiento académico. También se exploraron relaciones con variables como período académico, género, edad y nivel.

    Los resultados muestran diferencias en las calificaciones según las modalidades de aprendizaje y factores demográficos. Este análisis contribuye al entendimiento de cómo influyen estas variables en el desempeño de los estudiantes, con potencial para mejorar estrategias educativas y la calidad de la enseñanza.

  • English

    This study analyzes the academic performance in the Computer Science program at ESPAM MFL, considering seven academic periods and different learning modalities. A database with demographic information and final grades of students was used. Descriptive analyses, tests of normality, group comparisons using the non-parametric Kruskal-Wallis test, and correlation analyses using the Kendall’s Tau_b correlation coefficient were applied. The main objective was to examine the dynamics of grades in relation to the learning modalities and their potential impact on academic performance. Additionally, relationships between students’ average grades and variables such as academic period, gender, age, and level were explored.

    The results provide a rigorous and comprehensive insight into the academic performance in the Computer Science program at ESPAM MFL, highlighting differences in grades among different learning modalities and demographic factors.

    This analysis contributes to understanding how these variables influence students’ performance and can be useful for improving educational strategies and teaching quality at the institution.

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