# A Virtual Learning Architecture Enhanced by Fog Computing and Big Data Streams
## 2 Distance Learning
### State of the Art
#### 2.1.2 Teachers  
The main advantages of VLEs, when instructors are concerned, involve the flexibility of usage, the cooperation and collaboration among instructors and between instructors and students, the presence of common areas of knowledge to be shared across colleagues, the monitoring of students' progress, as well as creating and managing groups of students. However, the contribution in [10] alerts instructors and tutors to carefully follow students in the VLE usage, in order for them to avoid the adoption of the wrong strategies or bad habits, such as procrastination and trial and error. As a consequence, the employment of distance learning should be carefully tuned by teachers and adapted to the specific learning situations.  
Moreover, the quality of the provided content, in a VLE, is an essential point for its successful employment, and this is totally the province of teachers [9]. In this regard, the reification of subjects is a very important characteristic of any online course, and the teachers are encouraged to provide also experiences close to the real life of students and the most practical as possible, in order to be perceived as actually useful, genuine or authentic by the students themselves [11].  
In [15], new software modules were built in order to enhance Moodle with recommending capabilities targeted at teachers and instructors. These integrated modules allow for speeding up and customizing the creation of the courses, by taking advantage of past social usages of LOs on the part of colleagues teaching the same subjects or having similar pedagogical inclinations. The proposal seemed quite successful both in speeding up the time of creation of online courses and in the appreciation of a set of instructors, mainly those with little or scarce technical skills. Another work where recommending systems are applied to virtual learning environments is [16]. In this contribution, the authors focus on teachers again, especially considering their ICT-related skills and profile. The evaluation results of the contribution show that recommendations are personalized according to the ICT competences of instructors with a great degree of granularity thanks to the usage of fuzzy depiction.  
Carefully evaluating the integration between the cloud and VLEs from the perspective of teachers and instructors is very important as well [17]. This validation should take place also considering some theoretical pedagogical underpinnings, e.g., relatedness together with the inherent affordance of the system and how the functionalities provided by the VLE are chosen and used. However, the solutions based onto the cloud computing paradigm are proven to increase the availability of educational services, such as the sharing of documents between students and instructors and across teachers, as well as reusing collaborative pedagogic tools [5].  
Moreover, in cloud-based remote laboratories, the possible educational strategies provided to teachers increase [18]. They may vary from simulations, to recreation, where past collected actual data are used, until actualization, where lab equipment is remotely driven through micro-controllers in real time. Nevertheless, cloud-based solutions need to guarantee adequate performances, especially when dealing with interactive and collaborative learning tasks, and this is not always true.  
Focusing on the context, [PERSON] et al. [19] propose a system, very useful for teachers, to engage students in personalized learning paths, as well as to monitor their achievements, by integrating the learning process into the students' own environment by means of their own mobile devices. In [14], ubiquitous learning is presented as an extension of mobile-based learning. In this scenario, teachers are helped with performing a better orchestration of learning strategies and to continuously adapt them to the outcomes of the students.