Filtering Learning Objects Repositories by a Didactic Search Engine

Abstract

Nowadays, thanks to the Internet, the request for distance learning is increasing. Private companies and public institutions are very sensitive to the saving of costs that such type of education could implicate, i.e., with no limits in time and place. Besides, the results obtained by this kind of learning are comparable to those reached by the classic in-presence lessons. Consequently, instructional designers need didactic instruments to build courses in a rapid way, especially if they would build their courses starting from learning objects already posted into Learning Object Repositories by other peers. Our work proposes a system, at a very early stage of development, with the aim to help instructional designers to find and retrieve learning objects suitable for their courses, starting from the classic conceptual map of the course to be built. The system contains an OLAP module to let teachers to drill-down into concepts as well. © Springer-Verlag Berlin Heidelberg 2013.