Call for papers

The symposium will address and invites papers topics such as:

• Technology-enhanced learning in education and training
• Knowledge construction and development of competencies in knowledge networks
• Distributed decision making
• Web-based collective intelligence in innovation processes
• Assessment factors, performance evaluation, and building blocks of collective-intelligence-systems
• Pedagogical and didactical opportunities for technology-enhanced learning and teaching
• Knowledge construction and interaction, communication and collaboration in learning tasks
• Collaboration in communities and open networks
• Instructional design models and principles
• New trends in educational technology (Web 2.0, Open Educational Resources, Mobile learning)
• Required competencies for learning, teaching and tutoring in technology-enhanced networks
• Support systems for students and teachers
• Technical systems for the support of lifelong-learning, on demand learning and knowledge sharing
• Change management, implementation and dissemination of innovation in education and training
• Quality-management systems for technology enhanced learning
• Assessment methods
• Methods and designs to use collective intelligence for value creation
• Categorization of mechanisms of web-based collective intelligence
• Business models for the harnessing of collective intelligence
• Challenges and success factors to harness web-based collective intelligence in innovation processes
• Methods to design environments for collective intelligent behavior
• Methods and models to analyze web-based collective phenomena
• Concepts to coordinate and control collective value creation
• Scientific theories to analyze web-based collective intelligence
• Scientific theories to analyze web-based collective intelligence from different perspectives (such as economics, psychology and sociology etc.)
• Scientific theories to analyze innovation processes and innovation networks
• Technological and organizational triggers to activate collective intelligence
• Case studies of using web-based collective intelligence for value creation
• Design requirements and development of CI-Systems
• Architecture and components of CI-Systems
• Case studies and applications of CI-Systems
• Decision support systems considering social network information
• Assessment factors for social networks
• Performance evaluation of social networks
• Mechanisms for establishing knowledge networks
• Methods for designing CI-Systems
• Mechanisms for extracting, storing, and accessing collective knowledge
• Formal structures and representations of collective knowledge
• IT-supported modeling of collective knowledge

FernUni-Logo FernUniversität in Hagen, COLLIN 2011