A subject syllabus similarity analysis to address students mobility issue

Currently, students' mobility in Higher Education has become very common and frequent. Although the transitioning process could be thought to be smooth and quick, students moving from one institution to another must go through rigorous and unfortunately, non-standardized academic validation processes. Usually, most part of the process, including credits recognition and syllabi comparison are manually performed, consuming excessive time and massive human effort. Some of these academic processes however, could be optimized by means of computer technologies, which support data processing and help solving real-life problems usually found in the academic field. In the specific case of Ecuador, we have identified that each Higher Education Institution (HEI) manages customized curricular information management systems which include non-standard syllabi structured documents. The existence of custom made formats at every HEI has originate a large variety of data models. In this work, we propose to address these problems by identifying similarities between different current syllabi of Ecuadorian HEIs, aiming to the optimization, integration and improvement of the academic activities related to the students' mobility processes, such as credits recognition. This proposal relies on the definition of a standard data model, which is used to describe the academic syllabus and that allows the implementation of a computer-based system focused on similarities detection through the use of semantic web technologies and text mining tools.