Utilising adaptive interface techniques in the design of systems introduces certain risks. An adaptive interface is not static, but will actively adapt to the perceived needs of the user. Unless carefully designed, these changes may lead to an unpredictable, obscure and uncontrollable interface. Therefore the design of adaptive interfaces must ensure that users can inspect the adaptivity mechanisms, and control their results. One way to do this is to rely on the user's understanding of the application and the domain, and relate the adaptivity mechanisms to domainspecific concepts. We present an example of an adaptive hypertext help system POP, which is being built according to these principles, and discuss the design considerations and empirical findings that lead to this design.

Classically, humans have been perceived as a source of faults in systems. Modern ergonomic views are promoting a somewhat different idea according to which humans are a factor of safety in unexpected situations. The safety of a system cannot be achieved without taking into account these two sides of cognition which compose what is called cognitive flexibility. In this paper, we will consider the cases of a nuclear accident and a plane crash-landing where human cognitive flexibility has impacted on the final safety of the system. We aim to discuss the violations that humans have performed in these cases with the assumption that they do not always deteriorate system safety. The discussion gravitates around a core argument according to which violations per se do not inform on the safety impairments in a system. Some other dimensions have to be taken into account. Among these, we are of the opinion that the accuracy of the operators’ mental model plays a key role, allowing some violations to improve system safety in emergency situations.

Computer games are one of the most successful application domains in the history of interactive systems. This success has come despite the fact that games were ‘separated at birth ’ from most of the accepted paradigms for designing usable interactive software. It is now apparent that this separate and less-constrained environment has allowed for much design creativity and many innovations that make game interfaces highly usable. We analyzed several current game interfaces looking for ideas that could be applied more widely to general UIs. In this paper we present four of these: effortless community, learning by watching, deep customizability, and fluid system-human interaction. These ideas have arisen in games because of their focus on user performance and user satisfaction, and we believe that they can help to improve the usability of other types of applications. Keywords Computer games, game interfaces, user communities, interface customization, interface design

: Although massively parallel architectures are expected to provide the next major advance in computing power, writing applications on parallel distributed computers is considerably more difficult than programming conventional computers. Today's parallel distributed programming requires from the programmer to take care of quite complex tasks such as data and load distribution, data communication, process coordination, and tuning according to hardware characteristics. No programming environment taking care of this additional complexity is available. In this paper we present our concept and realization of a sophisticated program development environment PDE for parallel distributed programming. Strong use of expert knowledge and AI techniques within the PDE make it possible to free the application programmer from all parallelization complexity. Good parallel efficiency is achieved through application domain knowledge and by extracting the parallel structure of applications at the design a...

Adaptive systems provide personalised services in accordance with their knowledge or assumptions about each interacting user. Such systems adapt their own behaviour to find the optimal response to a specific user need or goal. In adaptive e‐learning systems, personalisation is based upon the premise that distinct learners follow distinct strategies during learning and show distinct preferences in the consumption of learning materials. Indeed, adaptive e‐learning systems have proven to be more efficient than non‐adaptive approaches in some application domains and for some types of learners. An efficient adaptive system is capable of deciding autonomously what, how, when and why to personalise. Though, the last two aspects (when and why) are mostly triggered through its environment. Therefore, accurate internal models of the system’s real world are of major importance, i.e. the better the system knows the targets in its environment, the higher its capability of adapting successfully. First of all,