|
Descripción
|
|
|---|---|
| Social learning analytics introduces tools and methods that help improving the learning process by providing useful information about the actors and their activity in the learning system. This study examines the relation between SNA parameters and student outcomes, between network parameters and global course performance, and it shows how visualizations of social learning analytics can help observing the visible and invisible interactions occurring in online distance education. The findings from our empirical study show that future research should further investigate whether there are conditions under which social network parameters are reliable predictors of academic performance, but also advises against relying exclusively in social network parameters for predictive purposes. The findings also show that data visualization is a useful tool for social learning analytics, and how it may provide additional information about actors and their behaviors for decision making in online distance learning. | |
|
Internacional
|
Si |
|
JCR del ISI
|
Si |
|
Título de la revista
|
Computers in Human Behavior |
|
ISSN
|
0747-5632 |
|
Factor de impacto JCR
|
2,273 |
|
Información de impacto
|
Datos JCR del año 2013 |
|
Volumen
|
47 |
|
DOI
|
10.1016/J.CHB.2014.10.038 |
|
Número de revista
|
|
|
Desde la página
|
68 |
|
Hasta la página
|
80 |
|
Mes
|
SIN MES |
|
Ranking
|
|