Track 17. Applications of Semantic Web technologies for Learning (SW-EL@ICALT2017)
Track Program Chairs
Track Description and Topics of Interest
It is well known that the application of the Semantic Web technologies provides several advantages like interoperability, integration and reuse. With respect to human learning and education, Semantic Web Technologies have been used for modeling various aspects of the learning experience, including content, metadata, learning design, pedagogical strategies, feedback, hints and learner profiles. By enabling automatic reasoning over such models, Semantic Web provides the grounds for the improvement of learning experiences from different viewpoints, such as adaptation and personalization, interoperability among systems, quality of search and recommender engines, etc. In addition, such technologies can be also adopted for Service-based Architectures to support service annotation, discovery, integration and coordination and for reasoning and collaboration among Intelligent Agents. Moreover, new applications of Semantic Web for Education are envisioned with respect to Seamless Learning and Context-aware Learning. In Seamless Learning, alignment and continuity of several, often heterogeneous forms of learning (formal in the classroom, informal in the city, etc.) are fundamental characteristics. In these scenarios, mechanisms, enabled by Semantic Web, like Open Badges could be employed.
Furthermore, in Context-aware Learning, new technologies like Augmented Reality can increase engagement and enable learners to construct broader understandings. In this case the glue among physical and digital worlds can be sustained also by the application of Semantic Web technologies.
Papers in this track addressing the following and other topics are encouraged:
- Semantic Web technologies to adapt and personalize the learning experience based on augmented reality
- Applications of Semantic Web technologies in Seamless learning for aligning activities (in different settings, with different devices, etc.) and handle continuity
- Building Intelligent Tutoring Systems by using Semantic Web technologies
- Embedding Intelligent Tutoring Systems in toys by means of Semantic Web technologies
- Using Semantic Web technologies in distributed architectures for Smart Environments (Smart City, Smart Classroom, etc.)
- Semantic Web languages and their formal extensions to build pedagogical models
- Applying machine (deep) learning approaches to build and/or refine Semantic Web models and rules
- Semantic Stream Processing to support human learning in the Smart City
- Uncertainty representation and reasoning in Semantic Web-based Applications for Human Learning
Track Program Committee
Nicola Capuano, University of Salerno, Italy
Angelo Gaeta, Università degli Studi di Salerno, Italy
Tatiana Gavrilova, St. Petersburg University, Russia
Giuseppe D’Aniello, Università degli Studi di Salerno, Italy
Carmen De Maio, Università degli Studi di Salerno, Italy
Sabrina Senatore, Università degli Studi di Salerno, Italy
Important Dates about ICALT 2017 can be found here.
The ICALT 2017 Author Guidelines can be found here.
The ICALT 2017 CfP can be found here.