NETE Recommendations of Experts to advise students on ubiquitous learning experiences: Method and Validation

Abstract

Ubiquitous learning systems have proved to be
helpful in many learning situations. These systems are contextaware,
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.