Marek Meyer

Modularization and Multi-Granularity Reuse of Learning Resource

Supervisor(s) and Committee member(s): Ralf Steinmetz (first examiner), Abdulmotaleb El Saddik (second examiner)


This thesis investigates modular reuse of learning resources. In particular, it considers a scenario of reuse in which existing learning resources serve as preliminary products for the creation of new learning resources for Web based training. Authors are interested in reusing the learning resources created by other authors. It is assumed that these authors belong to different organizations. Furthermore, these authors do not use a common authoring tool because they are obliged to use the tools specified by their respective organizations. There are content models which specify how learning resources may be constructed hierarchically. Authoring paradigms, such as authoring by aggregation, allow in principle a new learning resource to be created as the aggregation of different smaller learning resources. However, it is necessary that the learning resources to be combined are stored as individual resources. This approach works well if an organization systematically creates fine-grained, modular learning resources by using a suitable authoring environment. Many authoring tools use arbitrary content formats that are incompatible with other authoring tools or learning management systems. Thus, learning resources are not exchanged in their source format; instead, the Shareable Content Object Reference Model (SCORM) specifies a common exchange format for the learning resources. One disadvantage of this format is that the modular components of a learning resource are no longer able to be distinguished as individual learning resources.

This thesis enables the reuse of modular learning resources, which have due to an export process ceased to exist as individual learning resources. There are five contributions in the thesis that address the challenge of modular, multi-granularity reuse.
In the first contribution, an extension to the SCORM specification has been defined which enables the modular reuse of parts of a SCORM package and allows these learning resources to be modularized and aggregated. Furthermore, several approaches for modularization have been reviewed. As a result, a generic process model for the modularization of learning resources resulted from these various approaches. This process model is the second contribution of this thesis.

The third contribution is an extension of an authoring by aggregation process. The authoring by aggregation within existing implementations is restricted to pure content development only. This thesis has extended one of theses processes by a design phase which integrates the light-weight authoring approach of authoring by aggregation. After learning resources from different origins have been obtained and aggregated, the aggregation often looks like a patchwork. It is necessary to adapt the aggregated learning resources towards a unified appearance. This thesis proposes a framework for learning resource content representation and adaptation. This framework enables the development of adaptation tools which are able to work independent of different document formats and focus on a learning resource in its entirety instead of on individual documents.

Finally, the fifth contribution in this thesis is a new approach for the topical classification of learning resources. For cases in which no suitable training corpus is available, Wikipedia the online encyclopaedia is used as a substitute corpus for training machine learning classifiers. An evaluation of the Wikipedia based classifier has shown that it performs significantly better than traditional approaches.

KOM - Multimedia Communications Lab


Multimedia Communications Lab at the Department of Electrical Engineering and Information Technology at TUD is headed by Prof. Dr.-Ing. Ralf Steinmetz (Adjunct Professor of the Department of Computer Science). The Multimedia Communications Lab haunts the vision of seamless multimedia communication. Seamless multimedia communication has the potential to create a future where people from all over the world live, collaborate, and communicate independent of geographical constraints. The communication systems that support this collaboration have to be performant, dependable, secure, and adaptable to user requirements. The lab works on different Research Areas towards this vision:

  • Communication Services
  • IT Architectures
  • Knowledge Media
  • Mobile Networking
  • Network Mechanisms & QoS
  • Peer-to-Peer Networking
  • Ubiquitous Computing
  • Networked Gaming
  • IT for Mobility and Logistics

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