Semantic indexing of medical learning objects – usage of a semantic network by medical students
Date Submitted: Mar 28, 2015
Open Peer Review Period: Mar 30, 2015 - May 25, 2015
Background: The Semantically Annotated Media (SAM) project aims to provide a platform for searching, browsing and indexing medical learning objects (MLOs) based on a semantic network. Primarily, SAM supports the Aachen emedia skills lab, an interdisciplinary repository of multimedia medical learning objects for the Aachen Medical Model Curriculum (AMMC). The media are indexed with standardized keywords connected by a semantic net provided by SAM. Objective: The purpose of this study was to explore and assess a scenario-based evaluation of how medical students use SAM for accessing medical learning objects and to investigate the usability of SAM. Furthermore, it examined how well individual and broad interest is supported by SAM. Methods: In this study we chose a mixed-methods approach. Lean usability testing was combined with usability inspection by having the participants complete four typical usage scenarios before filling out a questionnaire. The questionnaire was based on the IsoMetrics usability inventory. Results: For the first time the study analyzed the typical usage patterns and habits of students using a semantic net for medical learning objects. Four scenarios capturing characteristics of typical tasks to be solved by using SAM yielded high ratings of usability items and showed good results concerning the consistency of indexing by different users. Long-tail phenomena emerge as they are typical for a collaborative Web platform: Suitable but nonetheless rarely used keywords were assigned to learning objects by some users. Conclusions: It is possible to develop a Web-based tool with high usability and acceptance for indexing and retrieval of medical learning objects. SAM can be applied to indexing multi-centered repositories of learning objects collaboratively.