Your browser doesn't support javascript.
Student workload assessment for online learning: An empirical analysis during Covid-19
Cogent Engineering ; 9(1):18, 2022.
Artículo en Inglés | Web of Science | ID: covidwho-1623485
ABSTRACT
Covid-19 has forced most educational institutions around the world to migrate to online learning in an emergency mode to protect students from the pandemic. This sudden migration to online learning has created multi-dimensional demands on students. Therefore, student workload needs to be measured during online learning. The purpose of this study is to measure the student workload from student perception by evaluating online learning in terms of Mental demand (MD), Physical demand (PD), Temporal demand (TD), Effort (EF), Performance (PE) and Frustration (FR). This study through a cross-sectional survey analysed 223 student's workloads on six dimensions using a NASA -TLX scale. The study finds all six components of workload significant for student assessment during online learning. Besides, the NASA-TLX scale was tested using confirmatory factor analysis for its ability to assess student workload for online learning. This is the first study to assess the student workload for online learning and hence contributes to the theory of measurement of workload assessment for online learning. The educational institutions can use this study to measure the student workload assessment for various courses offered by them using this simple tool.
Palabras clave

Texto completo: Disponible Colección: Bases de datos de organismos internacionales Base de datos: Web of Science Idioma: Inglés Revista: Cogent Engineering Año: 2022 Tipo del documento: Artículo

Similares

MEDLINE

...
LILACS

LIS


Texto completo: Disponible Colección: Bases de datos de organismos internacionales Base de datos: Web of Science Idioma: Inglés Revista: Cogent Engineering Año: 2022 Tipo del documento: Artículo