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Tobias Ley

Organization: TU Graz
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Role in the project

He leads work package 4 on Maturing Services




Schoefegger, Karin, Seitlinger, Paul, Ley, Tobias
Towards a user model for personalized recommendations in work-integrated learning: A report on an experimental study with a collaborative tagging system
In: Proceedings of the 1st Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL 2010), Procedia Computer Science, 2010, pp. 2829-2838

Abstract The informal setting of learning at work give rise for unique challenges to the field of technology enhanced learning systems. Personalized recommendations taking into account the current context of the individual knowledge worker are a powerful approach to overcome those challenges and effectively support the knowledge workers to meet their individual information needs. Basis for these recommendations to adopt to the current context of a knowledge worker can be provided by user models which reflects the topics knowledge workers are dealing with and their corresponding knowledge levels, but research has only focused on user modeling in settings with a static underlying domain model so far. We suggest to model the users’ context based on the emergent topics they are dealing with and their individual current knowledge levels within these topics by extracting the necessary information from the user’s past activities within the system. Based on data from an experiment with students learning a new topic with the help of a collaborative tagging system, we started to evaluate this approach and report on first results.


Schoefegger, Karin, Weber, Nicolas, Lindstaedt, Stefanie, Ley, Tobias
Knowledge Maturing Services: Supporting Knowledge Maturing in Organisational Environments
In: Knowledge Science, Engineering and Management, Lecture Notes in Computer Science vol. 5914, Springer, 2009, pp. 370-381

Abstract The changes in the dynamics of the economy and the corresponding mobility and fluctuations of knowledge workers within organizations make continuous social learning an essential factor for an organization. Within the underlying organizational processes, Knowledge Maturing refers to the the corresponding evolutionary process in which knowledge objects are transformed from informal and highly contextualized artifacts into explicitly linked and formalized learning objects. In this work, we will introduce a definition of Knowledge (Maturing) Services and will present a collection of sample services that can be divided into service functionality classes supporting Knowledge Maturing in content networks. Furthermore, we developed an application of these sample services, a demonstrator which supports quality assurance within a highly content based organisational context.

Schöfegger, Karin, Seitlinger, Paul, Ley, Tobias
Temporal Patterns in Collaborative Tagging: Analyzing Maturing of Semantic Knowledge Structures
In: Svihla, Vanessa (eds.): It’s about time: Exploring temporality in group learning. Alpine Rendez-Vous, Garmisch-Partenkirchen, December 2009, 2009

Schoefegger, Karin, Weber, Nicolas, Lindstaedt, Stefanie N., Ley, Tobiay
Knowledge Maturing Services: Supporting Knowledge Maturing in Organisational Environments
In: Proceedings of Knowledge Science, Engineering and Management (KSEM), 2009

Weber, Nicolas, Schoefegger, Karin, Bimrose, Jenny, Ley, Tobias, Lindstaedt, Stefanie, Brown, Alan, Barnes, Sally-Anne
Knowledge Maturing in the Semantic MediaWiki: A design study in career guidance
In: Learning in the Synergy of Multiple Disciplines. Fourth European Conference on Technology Enhanced Learning (EC-TEL 2009), Nice, France, 2009

Schmidt, Andreas, Hinkelmann, Knut, Ley, Tobias, Lindstaedt, Stefanie, Maier, Ronald, Riss, Uwe
Conceptual Foundations for a Service-oriented Knowledge and Learning Architecture: Supporting Content, Process and Ontology Maturing
In: Schaffert, Sebastian and Tochtermann, Klaus and Pellegrini, Tassilo (eds.): Networked Knowledge - Networked Media: Integrating Knowledge Management, New Media Technologies and Semantic Systems, Springer, 2009

Abstract Effective learning support in organizations requires a flexible and personalized toolset that brings together the individual and the organizational perspective on learning. Such toolsets need a service-oriented infrastructure of reusable knowledge and learning services as an enabler. This contribution focuses on conceptual foundations for such an infrastructure as it is being developed within the MATURE IP and builds on the knowledge maturing process model on the one hand, and the seeding-evolutionary growth-reseeding model on the other hand. These theories are used to derive maturing services, for which initial examples are presented.


Schmidt, Andreas, Hinkelmann, Knut, Lindstaedt, Stefanie, Ley, Tobias, Maier, Ronald, Riss, Uwe
Conceptual Foundations for a Service-Oriented Knowledge & Learning Architecture: Supporting Content, Process, and Ontology Maturing
In: 8th International Conference on Knowledge Management (I-KNOW 08), Graz, 2008

Abstract The knowledge maturing model views learning activities as embedded into, interwoven with, and even indistinguishable from everyday work processes. Learning is understood as an inherently social and collaborative activity. The Knowledge Maturing Process Model structures this process into five phases: expressing ideas, distributing in communities, formalizing, ad-hoc learning and standardization. It is applicable not only for content but also to process knowledge and semantics. In the MATURE IP two toolsets will be develop that support the maturing process: a personal learning environment and an organisation learning environment integrating the levels of individuals, communities and organisation. The development is guided by the SER theory of seeding, evolutionary growth and reseeding and is based on generally applicable maturing services.