Bernd Tschiedel

A Conceptual View of Web-Based E-Learning Systems

Starting from a general framework for web-based e-learning systems that is based on an abstraction layer model, this paper presents a conceptual modelling approach, which captures the modelling of learners, the modelling of courses, the personalisation of courses, and the management of data in e-learning systems. Courses are modelled by outline graphs, which are further refined by some form of process algebra. The linguistic analysis of word fields referring to an application domain helps to set up these course outlines. Learners are modelled by classifying value combinations for their characteristic properties. Each learner type gives rise to intentions as well as rights and obligations in using a learning system. Intentions can be formalised as postconditions, while rights and obligations lead to deontic constraints. The intentions can be used for the personalisation of the learning system to a learner type. Finally, the management of data in an e-learning system is approached on two different levels dealing with the content of individual learning units and the integrated content of the whole system, respectively. This leads to supporting databases and views defined on them.

Logistics for Learning Objects

The increasing attention paid to the importance of context-awareness of content has contributed to more useable e-learning websites. While existing approaches mostly cover static learner characteristics, to date it has been difficult to cover the dynamics of context. E-learning content must be delivered in the right doses, at the right moment, and in an appropriate form. Our work presents a storyboarding-based approach for specifying content-intensive websites. E-learning sites can be validated with regard to learner context. The practicability of our method is shown upon the e-learning project DaMiT. The SiteLang methodology helps overcome the limitations of existing approaches based on pre-defined, structuring of content. It allows a flexible content generation upon learner context, depending on the dynamics of the learning process.

Learner typing for electronic learning systems

e-Learning systems will provide new pathways to knowledge and skills acquisition. To increase their quality using a parametric learner model is proposed. Tailoring the learning material presented to the respective parameter values may fit this material to the actual learners needs. We use a stereotype user model. Our learner characteristics complement the IMS UP. We first represent learners by points in a learner space. Then we propose increasingly generic ways of grouping together such points to form learner types. The less generic one models learner types using convex regions in the learner space. The more generic one models learner types using characteristic functions. While the latter approach allows for more flexible learner type combination the former approach allows for convincing definition of initial learner types. Combining both approaches thus may result in a reasonable number of useful learner types.