Knowledge Through Evolution

This chapter argues that a knowledge discovery system should be interactive, should utilise the best in artificial intelligence (AI), evolutionary, and statistical techniques in deriving results, but should be able to trade accuracy for understanding. Further, it needs to provide a means for users to indicate what exactly constitutes “interesting”, as well as understanding suggestions output by the computer. One such system is Haiku, which combines interactive 3D dynamic visualization and genetic algorithm techniques, and enables users to visually explore features and evaluate explanations generated by the system. Three case studies are described which illustrate the effectiveness of the Haiku system, these being Australian credit card data, Boston area housing data, and company telecommunications network call patterns. We conclude that a combination of intuitive and knowledge-driven exploration, together with conventional machine learning algorithms, offers a much richer environment, which in turn can lead to a deeper understanding of the domain under study.

Communication Barriers and Conflicts in Cross-Cultural E-Learning

The present chapter assesses the key questions of communication barriers in distance learning virtual communities. To examine their cultural aspects, a Web-survey for distance learners has been conducted. The principal areas of interest were a cultural dichotomy of West/East; discrepancies in educational cultures (teacher-centered vs. learner-centered); mismatches in communication and educational traditions in different cultures; conflict paradigm and methods of conflict resolution. The findings of the survey are summarized and interpreted and some implications for further research are discussed.

Posting Articles about Excavations in Electronic Forums

Having taken its name from the fragmentary and divisive nature of the 20th century Balkans, the geopolitical term “balkanization” has come to refer to any region or society with internal turmoil or divisions. At the same time, it is being used to express the divergence over time of languages. In both cases, “balkanization” is an indisputable reality nowadays and reflects current relationships among nations. In this sense, although the unification process of the EU is believed to be a given today, problems such as the downgrading of less widespread languages such as Balkan languages and dialects still remain unsolved, mostly due to the predominance of English, French or German in the scientific, political, economical and commercial world. Indicatively, there are nine officially acknowledged languages today in the Balkans, whose even existence is ignored by the majority of EU citizens. Some have no apparent relation to the other. Whatever the case is, the Balkans have to and will survive this “Babel,” together with all European Union states. Maintaining a country’s language is a multilateral case and duty of nations nowadays; it also concerns a place’s culture and its specific characteristics and lifestyle, which differentiate it from other nations. It has to do with ethnic identity and understanding of one’s existence over time.

Social Modeller

Computer applications and especially artificial intelligence (AI) in archaeology is a scientific field that emerged in the late 1970s. This fact came in response to several simultaneous needs, opportunities and interests that result from the systematic development of methodologies relative to excavating, recording and restoration of findings, and also the increasing amount of information gathered in excavation areas. One of the first uses of artificial intelligence on a practical level was the coupling of expert archaeological knowledge with computerbased applications such as expert systems (ES), in order to simulate archaeologist’s reasoning for a specific problem. Nowadays, the evolvement of the Internet provides a novel platform convenient for the development of new intelligent software and for offering valuable services in archaeology (Gardin, 1988; Huggett & Ross, 2004; Huggett & Ryan, 1994; & Wilcock, 1985, 1990).

Evaluation Models for E-Learning

E-learning is still a quite young discipline that undergoes a continuous process of change due to new potentials that technology brings every day. After hardly 10 years of experience, it is difficult to envisage what is the degree of success of such new approaches to learning. Of course, the number of virtual students is increasing day by day because of the flexibility of such new environments that overcome constraints of time and space (Salmon, 2000; Palloff & Pratt, 2003). However, no such effort has been put into evaluating how the process of learning is taking place and comparing e-learning results with traditional distance learning studies, or even presential courses. The present chapter attempts to show some evaluation models for e-learning and how their results may contribute to define future research agenda and new technological implementations. Our experience of coordinating and teaching courses in archaeology and ancient history in the UOC (Open University of Catalonia) may shed some light into such a complex issue.

Personalization Issues for Science Museum Web Sites and E-Learning

E-learning has the potential to be a very personalized experience and can be tailored to the individual involved. So far, science museums have yet to tap into this potential to any great extent, partly due to the relative newness of the technology involved and partly due to the expense. This chapter covers some of the speculative efforts that may improve the situation for the future, including the SAGRES project and the Ingenious Web site, among other examples. It is hoped that this will be helpful to science museums and centers that are considering the addition of personalization features to their own Web site. Currently, Web site personalization should be used with caution, but larger organizations should be considering the potential if they have not already started to do so.

Collaborative Geographic Information Systems

This study describes the origins, boundaries, and structures of collaborative geographic information systems (CGIS). A working definition is proposed, together with a discussion about the subtle collaborative vs. cooperative distinction, and culminating in a philosophical description of the research area. The literatures on planning and policy analysis, decision support systems, and geographic information systems (GIS) and science (GIScience) are used to construct a historical footprint. The conceptual linkages between GIScience, public participation GIS (PPGIS), participatory GIS (PGIS), and CGIS are also outlined. The conclusion is that collaborative GIS is centrally positioned on a participation spectrum that ranges from the individual to the general public, and that an important goal is to use argumentation, deliberation, and maps to clearly structure and reconcile differences between representative interest groups. Hence, collaborative GIS must give consideration to integrating experts with the general public in synchronous and asynchronous space-time interactions. Collaborative GIS provides a theoretical and application foundation to conceptualize a distributive turn to planning, problem solving, and decision making.

Geographical Information Systems (GIS) and Learning Applications in Archaeology

Progress made in the fields of designing and geometrically analyzing earth maps, has lead to the development of automatic techniques which are applied in collecting analyzing and representing any information relevant to geographical interest. Such a collection of techniques sets the frame of what we call geographical information system (GIS).

Open and Distance Learning Tools and Strategies

There exists nowadays an enormous variety of models of e-leaning, from the technological, methodological and management perspective. At the university level, but also in company-training, in schools and formal education institutions, the different educational models appear, moving in a continuum from those who use technology as a complement or support to traditional attended sessions, to those that base the teaching and learning process in completely online environments. They try a variety of teaching methods while using differing degrees of virtualisation in the organisation (Bates, 2005). Years ago, when ICT in education started to be widely used, the success of the e-learning experience and the institutions themselves depended on their technological means; the platform was the most important of the model adopted by e-learning institutions. Initial efforts were put in market analysis aiming at finding out which was the best platform developed by ICT providers. Major investments in economical terms were dedicated to the acquisition of what was considered “the best” platform. Some years later, it was seen that institutions were different from the rest, and that not all educational platforms could cover all their needs. They realised that the success of their educational offer could not only be based on technology but in the learning materials provided. At that moment, the industry of online resources and hypermedia materials for educational uses grew up quickly. For some years, the success of e-learning mainly depended on the quality of the online materials provided, and that distinguish one institution from others.

Basic Aspects of VLEs and Guidelines for Supporting Learning Communities and E-Collaboration

This chapter aims to present the basic design principles for virtual spaces for facilitating educational designers and developers by providing a point of reference for making decisions about whether or not to incorporate 3D environments into the resources they develop as well as for extending their capabilities by integrating more functionality.