3. Producción

Browse

Settings

Author: search.filters.author.R. NavarroSubject: search.filters.subject.Higher education

Search Results

Now showing 1 - 2 of 2
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Challenges for university teachers in the design of virtual educational experiences during the pandemic
    (Universidad Cientifica del Sur, 2021-08-30)
    Como respuesta a la emergencia sanitaria, las instituciones de educación superior han tenido que migrar forzosamente a la virtualidad. Esto ha impactado en los agentes del entorno educativo, tanto en la enseñanza como en el aprendizaje. Por esta razón, en este artículo se analizarán las características particulares de la educación virtual y los principios de la enseñanza en este contexto. Asimismo, se describirán propuestas para diseñar experiencias educativas virtuales considerando las teorías motivacionales, del aprendizaje, y el diseño instruccional aplicado a la educación virtual. En esta misma línea, se discuten los retos que impone la pandemia para la educación universitaria y se proponen líneas de acción para la creación de experiencias educativas no presenciales. Se concluye que existe una necesidad imperante de capacitar a los profesores de tal manera que puedan usar las distintas herramientas digitales a su disposición y reconocer la unicidad de la educación virtual en contraposición a las clases tradicionales.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    The relationship between perceived learning, academic performance and academic engagement in virtual education for university students
    (Asian Online Journal Publishing Group, 2024-01-01)
    This study aimed to determine whether the three dimensions of academic engagement (cognitive, emotional and behavioral) were positively associated with perceived learning and academic performance. The participants were 301 university students from Lima. Structural equation models were used to test the proposed theoretical relationship between the variables. The results indicated that the model showed satisfactory fit indices (CFI = 0.956, TLI = 0.949, RMSEA = 0.043, SRMR = 0.062). Perceived learning was found to be predicted by cognitive engagement (β = 0.447, p < 0.01) and emotional engagement (β = 0.230, p < 0.05). However, there was no statistically significant relationship between behavioral engagement and perceived learning (β = 0.035, p = 0.840). On the other hand, academic performance was predicted by behavioral engagement (β = 0.393, p < 0.05) but not by cognitive (β = -0.164, p = 0.301) or emotional (β = 0.001, p = 0.991) engagement. The study highlights the importance of fostering academic engagement in university students to enhance both their academic performance and perceived learning.