How to use different dynamics to motivate the learners is crucial to the success of learning.
This study uses the DeLone and McLean model to determine the moderating impact of learning styles on the success of learning management systems from a student's point of view.
It is agreed upon that if SRL skills are important to the success of learning in the traditional classroom, then these skills can be expected to play an even more important role for students participating in the distance learning environment (Barnard, Lan, To, Paton, & Lai, 2009; Kramarski & Michalsky, 2010).
Several scholars suggested that if SRL skills are important to the success of learning in the traditional classroom (Effat & Gillies, 2015; Kramarski & Michalsky, 2010), then these skills can be expected to play an even more important role for students participating in the distance learning (DL) environment (Barnard et al., 2009).
Building on the work of Bryk and Schneider, Cranston connects the success of learning communities with the notion of trust, which is articulated as 'being relational in its orientation and developed around group norms of safety, risk-taking, and change orientation' (2011, pp. 59).
"The success of learning communities, though, hinges on the type of support offered to students, who at community colleges tend to be older and often work part- or even full-time," said Vince Tinto, a professor at Syracuse University who has researched and written extensively about learning communities.
The object of the study was to determine the feasibility and success of distance learning programmes in Tanzania and their ability to help Tanzania meet its human resources for health (HRH) needs.
Preceptors are key to the success of student learning in competency-based frameworks.
Good design is critical to the success of a learning object.
Owing to the success of deep learning techniques in automatic speech recognition, deep neural networks (DNNs) have been used as acoustic models for statistical parametric speech synthesis (SPSS).
Inspired by the success of transfer learning applied in high-level vision problems, Dong et al. [9] explored several transfer settings on compression artifact reduction and demonstrated the effectiveness of transfer learning in low-level vision problems.
