Abstract
E-learning is being considered as a widely recognized option to traditional learning environments, allowing for highly tailor-made adaptive learning paths with the goal to maximize learning outcome ...
Highlights
As a result of digitalization, more and more educational content has been transferred from teacher-centered teaching to online-based learning platforms
Our results are in line with previous studies, showing that tasks tapping on verbal working memory (WM) typically are more sensitive for predicting academic achievements with textual content compared to tasks tapping on visuospatial WM (Rogers and Monsell, 1995; Pazzaglia et al, 2008; Gropper and Tannock, 2009; Van de Weijer-Bergsma et al, 2015)
The present study set out to test the relationship between e-learning online activities and individual differences in visuospatial and verbal WM performance
Summary
As a result of digitalization, more and more educational content has been transferred from teacher-centered teaching to online-based learning platforms. Such learning platforms, often called e-learning, can be defined as individualized instructions distributed over public or private computer networks (Manochehr, 2006). Both explanatory studies using traditional statistical techniques (Coldwell et al, 2008; Dawson et al, 2008; Macfadyen and Dawson, 2010; Yu and Jo, 2014; Zacharis, 2015) as well as predictive analytics studies using machine learning- and Online Activities and Working Memory neural networks (Lykourentzou et al, 2009; Hu et al, 2014; Sayed and Baker, 2015; Costa et al, 2017; Shelton et al, 2017) have been conducted to gain better insights in online learning activities with the aim to optimize and tailor e-learning platforms according to students’ individual needs (e.g., Thalmann, 2014; Truong, 2016)
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