Middleware for the Development of Context-Aware Applications inside m-Learning: Connecting e-Learning to the Mobile World

Using virtual learning environments in bricolage mode for orchestrating learning situations across physical and virtual spaces

“…As an alternative for overcoming such limitation, the evaluation showed that the learning buckets can be a simple instrument to connect the different physical and virtual spaces, by enabling the access from a space to contextualized artifacts created in another space. Finally, as we also described in Section 2, there are other approaches in the literature that include context-awareness features, but restrict the teacher-controlled flexibility offered to the students during the enactment (e.g., Glahn & Specht, 2010;Martin et al, 2009;Milrad et al, 2011;Sotsenko et al, 2014;Trifonova & Ronchetti, 2004), which affects negatively the roles of the teacher and other actors orchestration aspect. The evaluation carried out suggests that the learning buckets surpass this limitation: they enabled the students a flexible management of learning artifacts across-spaces; also, the configurable constraints of the learning buckets showed to be like an "equalizer", able to "tune" the flexibility offered to the students, and therefore, the orchestration load over the different actors, enabling the teacher a controlled sharing of the load with the students.…”

“…The architecture includes some contextawareness capabilities: tracking the location of users, and enabling the access to specific Moodle resources from pre-defined "contexts" (physical regions delimited with geographical coordinates, and globally configured in Moodle). M2Learn is a framework to create mobile context-aware applications (e.g., capable of detecting location using multiple sensors, such as GPS or RFID reader) and integrate them with VLEs, such as Moodle (Martin et al, 2009). Another approach is the one by Milrad, Kohen-Vacs, Vogel, Ronen, and Kurti (2011).…”

“…However, they have been traditionally isolated from mobile devices (Casany et al, 2012), preventing their use in ubiquitous learning environments that include other physical spaces beyond the usual ones in blended learning (typically the classroom and home). Several approaches have proposed solutions to allow the ubiquitous access to VLEs by means of mobile devices (see e.g., Casany et al, 2012;Glahn & Specht, 2010;Martin et al, 2009;Santamarina, Moreno-Ger, Torrente, & Manjón, 2010;Trifonova & Ronchetti, 2004). Nevertheless, these works tend to present limitations that may affect negatively certain orchestration aspects: i) most approaches have a limited, if any, capability to regulate the degree of flexibility offered to the students, which may be necessary in some pedagogical approaches (Hannafin & Land, 1997;Zimmerman, 1990), especially in ubiquitous learning environments, which may demand a sharing of the orchestration load with the students (Sharples, 2013); ii) usually, the proposals do not allow the integrated use of technologies commonly employed by teachers (e.g., common VLEs or Web 2.0 tools), which may hamper their embedding in teachers' current practice (Cuendet, Bonnard, Do-Lenh, & Dillenbourg, 2013;Prieto, Wen, Caballero, & Dillenbourg, 2014); iii) also, several of these proposals do not implement mechanisms to be aware of the context in which learning takes place, which is an important factor in the seamless combination of different learning spaces (Li et al, 2004;Milrad et al, 2013).…”

Trends of use of technology in engineering education

“…The role of mobile devices in education started just as the basis of a very rudimentary mobile learning, but with the integration of ubiquitous computing and context-awareness paradigms, such as location-based technologies its functionalities are being extended to provide a real improvement on the learning experience [6]. The success of mobile devices in education in a short-term and its integration with ubiquitous technologies will probably foster the arrival of ubiquitous learning in a few years.…”

Intelligent Classroom with Motion Sensor and 3D Vision for Virtual Reality e-Learning

“…Their study content of subject covered 2D and 3D transformations, algorithms for drawing basic graphical elements in raster graphics, fractal theory, animation, colour-processing, modelling and drawing 3D objects. Martin et al [3] proposed a framework to provide contextual information from different sources, including different kind of geographical sensors and external services. These studies moved from satisfaction with e-learning to m-learning.…”