Conversation-based Learning in the Social Semantic Web

Abstract

The collaborative approaches based on concepts of Knowledge construction and knowledge creation consider the learning as a direct function of processes of social participation and dynamic argumentative talk between peers. These approaches justify the Social Semantic Web’ success as a theoretical and technological model which establishes a synergy between an Ontology-based approach to knowledge (suitable for defining, structuring and sharing knowledge) and collaborative software environments (utilized to create and share knowledge socially). The above mentioned approaches make reference to Semantic Web and Social Web respectively. If the Ontologies are an effective mechanism for the formal representation and sharing of knowledge, the social/collaborative activities adopt pedagogical theories of Social Constructivism. Recently, the scientific community has promoted the Educational Social Semantic Web, where activities and educational content are easily created, shared and used by teachers and students even without possessing brilliant engineering knowledge skills or technological know-how. The purpose of this work is to model, according to Social Semantic Web’s principles, an adaptive environment able to support Instruction-based Conversation learning processes in a work environment. In such an environment, the conversational process is guided by a collaborative script automatically generated basing on the explicit representation of a disciplinary domain, a knowledge goal to be achieved, as well as learner’s characteristics (cognitive state) and corporate resources available at a given time. The environment maintains the learner's cognitive balance, minimizes the extraneous processing, appropriately manages the essential processing and maximizes the generative processing.