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Exploiting Linked Data for supporting mobile learning experiences

Poster
Data di Pubblicazione:
2014
Abstract:
The evolution of mobile technologies in the last few years has radically changed the way and places in which people can get access to information. This transformation has influenced several contexts from business to everyday life activities. It is more and more common to see “digital natives” using their smartphone when they are walking around the city or waiting at the bus stop. Guessing what they are doing with their smartphone is not easy: are they gaming? Are they browsing Internet pages or checking their profile in their favorite social network? Recent statistics highlight the number of young people using their mobile devices for learning is growing. This is an important indicator which shows that mobile learning is ready to move from the research labs and experimental phase (which in almost 10 years have highlighted the educational potentials of mobile devices) towards a mature phase where students and, above all, teachers, will consider it as a learning methodology which complements, supports, enriches and sometimes substitutes more traditional learning strategies. A further step towards this transition is related to the advances in the technological development of mobile devices in the last decade, which have made it possible the commercial availability of smartphones with good computation capabilities , which are getting more and more popular amongst young people. Through the support of a smartphone, a walk around a city can turn into an opportunity for learning and it is not necessary to organize it in advance, as teachers use to do in traditional school trips. Indeed, the most popular mobile stores already include, in their catalogs, several applications providing specific information about hundreds of cities in the world. This information can be used to support the visit of a city successfully, but the scope of these applications rarely extend beyond their use as tourist guide. Specifically to their educational use, the information provided by these applications is usually extracted from proprietary data source, and cannot be easily customized to be really suitable for learning settings. Consequently, teachers wishing to organize learning experiences around the city have to prepare learning content in advance, and maintain it during the whole lifespan of the application. In this abstract, we present MeLOD, a mobile learning environment, which exploits the huge amount of dataset in the Linked Open Data (LOD) cloud to overcome the previous issues, by providing contextualized updated information based on students’ location. The position of the student sent by the mobile device is used to interlink Geonames, DBpedia and Europeana datasets to provide information about all the interesting cultural heritage sites close to the student. Moreover, students social activities like voting and commenting are used to enhance the knowledge base of the environment and to provide recommendations for next students’ visits. A prototype of the MeLOD mobile application has been developed for iOS devices and it is available for free on the Apple Store. More information about the environment are available at: http://melod.pa.itd.cnr.it/ The MeLOD environment is composed by two main modules: a mobile application, with a friendly user interface, that shows the information to the students during their visit, and a set of web services that elaborate the requests coming from the mobile application to provide interlinked information from different open datasets. The main datasets exploited by the MeLOD environment are (at the time of writing) three: DBpedia, Geonames and Europeana. Moreover, in the last few years, many municipalities, in the world in general and in Italy in particular, are releasing their data as Open Data. For instance the mun
Tipologia CRIS:
04.03 Poster in Atti di convegno
Elenco autori:
Arrigo, Marco; Fulantelli, Giovanni; Taibi, Davide
Autori di Ateneo:
ARRIGO MARCO
FULANTELLI GIOVANNI
TAIBI DAVIDE
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/232238
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