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
07月03日
2017
07月07日
2017
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