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Computers can be a great benefit for pupils with cognitive disabilities or related difficulties. But even more than in standard learning scenarios, the orchestration plays an important role. Designing learning software for a special target group should not only focus on the pupils but also on the teachers. Finally, to get the best possible benefit from the software, the hardware which is used in the classroom must be carefully selected and arranged. In this paper we present an example of how teachers use a computerised learning environment to teach pupils with special educational needs. We describe a use of software to reintegrate a boy with autism spectrum disorders into a school class where children with and without disabilities are taught. The software development process was based on a participatory design approach which involved contributions from teachers, researchers and programmers. As well as standard single user tasks a special feature of the application is the provision for collaborative learning tasks for pupils with cognitive disabilities.

The purpose of this paper is to show that conjoint measurement has proved to be an effective tool for identifying customer preferences. However, in order to market products and services successfully information about the variable costs for the various attributes and their respective levels needs to be considered. A platform approach could reduce these costs and generate very effective preference drivers.

This paper proposes and elaborates a model, which examines a joint implementation of conjoint measurement and the platform concept. The model is empirically tested on data gathered on a stratified random sample of customers through the application of valid and reliable measures. The model is tested using a conjoint and regression design.

The results in this paper show the usefulness of a joint implementation of conjoint measurement and the platform concept. Variable costs can be reduced considerably and preferences can be adequately identified. In combining market information (preference data) with cost data profitability is increased.

This paper specifically is to address the following four questions: What are the most important attributes and levels for customers? What are the variable costs for those attributes and levels? Could an implementation of the platform concept reduce those costs significantly? Are there any efficient preference drivers?

The increasing need to access and elaborate dynamic and heterogeneous information sources distributed over the Internet calls for new models and paradigms for application design and development. The mobile agent paradigm promotes the design of applications where agents roam through Internet sites to locally access and elaborate information and resources, possibly co‐operating with each other. Focuses on mobile agent co‐ordination, and presents the TuCSoN co‐ordination model for Internet applications based on mobile information agents. TuCSoN exploits a notion of local tuple‐based interaction space, called a tuple centre. A tuple centre is a tuple space enhanced with the capability of programming its behaviour in response to communication events. This enables properties to be embedded into the interaction space, and a mobile agent to be designed independently of the peculiarities of the information sources. Several issues critical to Internet applications can then be charged on tuple centres transparently to agents. The effectiveness of the TuCSoN model is first shown by means of an application example in the area of Internet information retrieval, then discussed in the context of workflow management and electronic commerce.

The purpose of this paper is to propose a computer‐supported collaborative learning (CSCL) research framework.

The framework was developed from a review and synthesis of the literature. More specifically, gaps in the literature were identified and a general framework for future CSCL research was proposed.

This paper proposes a research framework that identifies a fit profile between learning objectives, learning tasks, and technology in CSCL. The fit profile, in turn, is expected to influence users' learning processes and outcomes.

This framework can serve as a foundation for future research in CSCL. More specifically, research should give consideration to the collaborative learning objective and task, which will vary in degrees of complexity and cognitive demands. Also, researchers will want to evaluate the level of sophistication of the CSCL technology, as well as its appropriateness for a given objective and task, which ultimately influences the learning process and outcomes.

Considerations and guidelines for development of CSCL applications are provided.

CSCL is an important research area that has attracted the attention of researchers from various disciplines (e.g. information systems, educational psychology). However, the findings are varied and sometimes conflict with each other. By emphasizing a fit profile between learning objectives, learning tasks, and technology, this paper proposes a theory‐based research framework to address the inconsistencies observed in the literature.