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MIMIC model of teachers and students attitudes towards online learning during Covid-19: A gender perspective
Knowledge Management & E-Learning-an International Journal ; 15(2):174-191, 2023.
Artículo en Inglés | Web of Science | ID: covidwho-20245460
ABSTRACT
Academic institutions around the globe have shifted to online learning because of the unpredictable spread of COVID-19. The present study aimed to compare teachers' and students' attitudes towards online learning during the pandemic and to examine the effects of gender differences on their attitudes. In study 1, we adapted the Test of eLearning Related Attitudes for Pakistani students in three

steps:

expert review, piloting, and validation. The individual and collective expert review was performed to adapt the teacher version into the student version using the Technique for Research of Information by the Animation of a Group of Experts (TRIAGE). We tested three sets of measurement invariance models for participants' status and gender in study 2. Data were collected from 289 university teachers (men = 158, women = 131) and 444 undergraduate students (boys = 156, girls = 287). The results demonstrated that both groups had highly positive yet different attitudes towards online learning. Teachers were more satisfied than students. Model fit was poor, and the overall factor structure, factor loadings, and intercepts varied across groups. Intergroup gender invariance illustrated heterogeneity in attitudes towards online learning favoring men teachers and boy students. Study strengths and implications for the promotion of a positive experience of online learning are discussed.
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Texto completo: Disponible Colección: Bases de datos de organismos internacionales Base de datos: Web of Science Tipo de estudio: Estudio experimental / Estudio pronóstico / Ensayo controlado aleatorizado Idioma: Inglés Revista: Knowledge Management & E-Learning-an International Journal Año: 2023 Tipo del documento: Artículo

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Texto completo: Disponible Colección: Bases de datos de organismos internacionales Base de datos: Web of Science Tipo de estudio: Estudio experimental / Estudio pronóstico / Ensayo controlado aleatorizado Idioma: Inglés Revista: Knowledge Management & E-Learning-an International Journal Año: 2023 Tipo del documento: Artículo