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The ever-increasing use of portable devices, such as smartphones and tablet PCs, has stimulated the adoption of mobile computing in different application areas. The user who carries portable devices can explore wireless communication technologies to access resources in anywhere and anytime. In addition, the widespread use of location systems (Hightower, LaMarca, & Smith, 2006), such as the GPS, has allowed a contextualized access to information (Dey, 2001). In this scenario, the ubiquitous computing initially introduced by Weiser (1991) and Satyanarayanan (2001) is becoming reality (Barbosa et al., 2015). The ubiquitous computing is a computational model that aims to pro-actively serve the needs of users, acting in an invisible way. The goal is to provide a continuous integration between technology and the environment, helping users in their daily tasks.
The application of mobile and ubiquitous computing in the improvement of learning strategies has created two research fronts called mobile learning and ubiquitous learning. Mobile learning (m-learning) (Saccol et al., 2011; Tatar, 2003; Klein et al., 2018) is fundamentally about increasing learners’ capability to carry their own learning environment along with them. M-learning is the natural evolution of e-learning. The mobile computing has the potential to make learning even more accessible. In m-learning model, mobile computers are still not embedded in the learners’ surrounding environment, and as they cannot seamlessly obtain information about contexts (Dey, 2001).
On the other hand, ubiquitous learning (Barbosa et al., 2011; Wagner et al., 2014; Rosa et al., 2015; Abech et al., 2016; Pimmer, Mateescu, & Gröhbiel, 2016; Guabassi et al., 2018) refers to learning supported by the use of mobile and wireless communication technologies, sensors and location/tracking mechanisms (Barbosa et al., 2018), which work together to integrate learners with their environments. In addition, ubiquitous learning systems can involve the collaborative development of learning contents and learning processes, as well as, the use of social media for informal learning, communication and encouragement of participation (Marinagi, Skourlas, & Belsis, 2013).
Ubiquitous learning systems connect virtual and real objects, people and events, in order to support a continuous, contextual and meaningful learning. While the learner is moving with mobile device, the system dynamically supports learning process by communicating with embedded computers in the environment. The essence of Ubiquitous Learning is to realize which information can be presented throughout the learners’ daily tasks, in different forms and places, and to link this data with the learners’ educational process. Technologies that support Ubiquitous Learning should provide these aspects through mechanisms that allow knowing learners’ profiles, contexts involving them, and how learners relate to contexts.
Nowadays there are works about recommendation of educational material, which are becoming increasingly important due to the dissemination of ubiquitous learning. The web already provides a huge quantity of materials that can be useful for educational purposes. In this scenario, teachers not only need to examine whether this vast quantity of materials available falls in line with the syllabus but, ideally, also check if they comply to the learning profiles of students (Akbulut & Cardak, 2012; Felder & Silverman, 1988; Peterson, Rayner, & Armstrong 2009) and to the teaching context where the learning is occurring (Barbosa et al., 2011; Rosa et al., 2015; Abech et al., 2016, Guabassi et at., 2018).