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Abstract. In a cluster of many servers containing heterogeneous multimedia learning material and serving users with different backgrounds (e.g. language, interests, previous knowledge, hardware and connectivity) it may be difficult for the learners to find a piece of material which fit their needs. This is the case of the COLDEX project. Recommender systems have been used to help people sift through all the available information to find that most valuable to them. We propose a recommender system, which suggest multimedia learning material based on the learner's background preferences as well as the available hardware and software that he/she has.

Interactive multimedia learning systems are not suitable for people with disabilities. They tend to propose interfaces which are not accessible for learners with vision or auditory disabilities. Modeling techniques are necessary to map real world experiences to virtual worlds by using 3D auditory representations of objects for blind people and visual representations for deaf people. In this paper we describe common aspects and differences in the process of modeling the real world for applications involving tests and evaluations of cognitive tasks with people with reduced visual or auditory cues. To validate our concepts, we examine two existing systems using them as examples: AudioDoom and Whisper. AudioDoom allows blind children to explore and interact with virtual worlds created with spatial sound. Whisper implements a workplace to help people with impaired auditory abilities to recognize speech errors. The new common model considers not only the representation of the real world as proposed by the system but also the modeling of the learner's knowledge about the virtual world. This can be used by the tutoring system to enable the learner to receive relevant feedback. Finally, we analyze the most important characteristics in developing systems by comparing and evaluating them and proposing some recommendations and guidelines.

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