Recommendations of Experts to Advise Students on Ubiquitous Learning Experiences: Method and Validation

Ubiquitous learning systems have proved to be helpful in many learning situations. These systems are context-aware, so considering only student’s profiles to offer personalized recommendations it is not enough. It is also necessary to take into account contextual characteristics. We proposed a method to generate automatics recommendations of experts to advise students. The method considers previous experiences of these experts with other students and recommends expert that are available and physically close to the student; and experts that are available and online. This work presents the method and describes the experiments carried out to validate it using simulation techniques. The precision value obtained demonstrate that the method produces results that are fit-for-purpose.