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Tracks & Call for Papers

The symposium will be divided into three different tracks.

Track 1: Technology-enhanced learning in education and training - Knowledge construction and development of competencies in knowledge networks

Track 2:Web-based collective intelligence in innovation processes

Track 3: Assessment Factors, Performance Evaluation, and Building Blocks of Collective-Intelligence-Systems

We kindly invite authors from either a theoretical or practical background to submit papers for the tracks. They only can be written in English. The papers will be peer-reviewed in a double-blind process.

Papers should fit to the style sheet and not exceed a total length of 12 pages (Word 97-2003, Word 2007, LaTeX). Please remove name etc. from the submitted papers and also meta-data from the submitted Word-/PDF-documents.

Accepted papers will be published in the proceedings (We are planning to publish the conference proceedings in Springer Lecture Notes). Publishing of an accepted paper in the proceedings requires at least one of the authors attending the symposium and paying the symposium fee.

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Track 1: Technology-enhanced learning in education and training - Knowledge construction and development of competencies in knowledge networks

With the rise of the network society a new mode of knowledge construction emerges; knowledge is created in networks operating in informal, non-hierarchical, heterogeneously organized structures that are essentially transient. This new mode of knowledge construction operates in a context of application in that problems are not set within a disciplinary framework. It does more than assemble a diverse range of specialists. The shape of the final solution will be transdisciplinary rather than mono- or interdisciplinary (Gibbons et al., 1994). This process is now accelerated through the development of technology-enhanced learning and new web applications that facilitate collaboration, social interaction and negotiation of meaning (so-called social software or Web 2.0 applications).

Along with societal change the characteristics and competencies of learners, "knowledge workers" or members in a knowledge building community interacting in technology-enhanced environments are also changing. Today's kids grow-up digital and it is purposed that they form the "Net Generation" with a specific set of behaviors, skills and competencies.

In (higher) education settings as well as in professional development and corporate training, mainly relying on traditional, formal modes of teaching and learning, it is a challenge to integrate and respond to these open forms of knowledge construction.

The main question is: ‘What are critical factors that can be derived for successful design and sustainable implementation of technology-enhanced knowledge networks?’

Possible topics include, but are not limited to:

  • Pedagogical and didactical opportunities for technology-enhanced learning and teaching
  • Knowledge construction and interaction, communication and collaboration in learning tasks
  • Collaboration in communities and/or 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


Track Chair:

Theo J. Bastiaens, FernUniversitaet in Hagen, Germany

Committee:
Claudia de Witt, FernUniversitaet in Hagen, Germany
Olaf Zawacki-Richter, FernUniversitaet in Hagen, Germany

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Track 2: Web-based collective intelligence in innovation processes

The internet is an important economic factor for many companies. More and more companies exist with the internet as a basis for the whole business model. With the rising of Web 2.0 the internet is no longer only a distribution and communication channel between companies and customers. The enhancement of technologies and changing user behavior offers new challenges and also new opportunities for companies. Recently, the collective intelligence of internet users and online customers has thrust into the spotlight. Concepts and terms like Crowdsourcing, Wikinomics or “Wisdom of crowds” are heavily discussed in this context. All these concepts focus on value creation by groups of individuals. Some companies have already started to use this collective intelligence for value creation. Two examples are Threadless and InnoCentive. Threadless uses the crowd of customers to design t-shirts and to choose the portfolio of products. The open innovation marketplace InnoCentive offers companies the opportunity to find creative and new solutions created by the masses. However, the basic concepts, features and mechanism of collective intelligence are widely unexplored. Systematic approaches to integrated collective behavior and collective intelligence into value creation do not exist. There are still many open questions: What are appropriate designs for business models using collective intelligence? How can information and communication technology boost collective intelligence? How can online users and customers be motivated to take part?

Possible topics include, but are not limited to:

  • 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 (economically, psychological, sociological 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


Track Chairs:

Ulrike Baumoel, FernUniversitaet in Hagen, Germany
Sabine Fliess, FernUniversitaet in Hagen, Germany
Henrik Ickler, FernUniversitaet in Hagen, Germany

Committee:
Homa Bahrami, University of California at Berkeley, USA
Peter A. Gloor, MIT Center for Collective Intelligence, USA
Axel Hochstein, Stanford University, USA
Norbert Hoffmann, Swiss Life AG, Zuerich, Switzerland
Reinhard Jung, Universitaet St. Gallen, Switzerland
Wilhelm Roedder, FernUniversitaet in Hagen, Germany
Klaus Tochtermann, Universitaet Graz, Austria
Brigitte Werners, Ruhr-Universitaet Bochum, Germany

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Track 3: Assessment Factors, Performance Evaluation, and Building Blocks of Collective Intelligence Systems

Knowledge, that is inherent to social networks of communities, can constitute an important competitive advantage for enterprises, organizations, and individuals. The knowledge could be used to improve communication flows, create new knowledge and competencies, or to optimize innovation processes. However, it is still unclear how information management systems could support these activities, effectively present and process the knowledge inherent to social networks. In order to address these issues, different alternatives for assessing social networks have to be investigated and understood. In a second step, the assessment results obtained from applying the assessment factors to social networks could be used for a performance evaluation of those networks. In addition to this, the assessment factors and the results of the performance evaluation can be considered for the design of information management systems, which are called Collective-Intelligence-Systems (CI Systems). These systems are expected to provide mechanisms for the cooperative construction of knowledge, have the ability of analyzing collective knowledge, and provide support for decision-making. In general, these CI Systems will affect the conventional knowledge processing, as we know it. However, in order to achieve a sustainable performance of CI-Systems, it is essential to find characteristic design parameters and basic components of CI-Systems, which, in turn, can be considered for the actual development of CI-Systems. The design parameters and the basic components could be identified through a classification of different kinds of CI-Systems.

Possible topics include, but are not limited to:

  • 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


Track Chairs:
Joern Altmann, Seoul National University, Korea
Bernd J. Kraemer, FernUniversitaet in Hagen, Germany

Committee:
Aurélie Aurilla Arntzen Bechina, College University I Buskerud, Kongsberg, Norway
Joerg M. Haake, FernUniversitaet in Hagen, Germany
Gunter Schlageter, FernUniversitaet in Hagen, Germany
Chen-Yu Phillip Sheu, University of California at Irvin, USA

01.12.2009
FernUni-Logo FernUniversität in Hagen, COLLIN 2010