Evidence for sustainable e-learning in quality online learning environments: a purposive approach to content analysis

This paper examines a methodology for establishing quality in online learning environments. For e-learning to be sustainable in flexible, open and distance learning, its value in learning must be able to be analysed. In the case of computer conferencing, one way to do this is with content analysis. This methodology is discussed with a review of current frameworks. These indicate that while some researchers and evaluators either use or modify existing frameworks, most researchers develop new ones, generally through the adaptation of existing theories, concepts or model, but in some cases through grounded theory approaches. The development and implementation of two frameworks are then discussed in detail. Both were developed to investigate and evaluate both collaborative learning and deep and surface learning as evidenced in computer conferences. Evidence of such learning attributes are precisely the elements of value in e-learning that can be shown through such a methodology. These attributes can then be integrated into courses developed for quality online learning environments.

Virtual non-profit organisations : literary virtual communities in Russia

This paper is a study of one of the "unknown" segments of the Internet - non-profit ventures in the Russian language. Based on the understanding of the concept of virtual community we consider the family of free publishing literary websites. We discuss their experience to demonstrate their contribution not only to the national culture, but also to the creation of open and democratic society in the former communist world, and to new forms of literary life. Some of the innovative concepts, principles and practices, adopted on those sites may be of interest to the Internet developers and communities worldwide.

Building agent-based hybrid intelligent systems : a case study

Many complex problems (e.g., financial investment planning, foreign exchange trading, data mining from large/multiple databases) require hybrid intelligent systems that integrate many intelligent techniques (e.g., fuzzy logic, neural networks, and genetic algorithms). However, hybrid intelligent systems are difficult to develop because they have a large number of parts or components that have many interactions. On the other hand, agents offer a new and often more appropriate route to the development of complex systems, especially in open and dynamic environments. Thus, this paper discusses the development of an agent-based hybrid intelligent system for financial investment planning, in which a great number of heterogeneous computing techniques/packages are easily integrated into a unifying agent framework. This shows that agent technology can indeed facilitate the development of hybrid intelligent systems.