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Researchers in distance education are interested in observing and modelling of learner's personality profile, and adapting their learning experiences accordingly. When learners read and interact with their reading materials, they do unselfconscious activities like annotation which may be key feature of their personalities. Annotation activity requires the reader to be active, to think critically and to analyse what has been written, and to make specific annotations in the margins of the text. These traces are reflected through underlining, highlighting, scribbling comments, summarizing, asking questions, expressing confusion or ambiguity, and evaluating the content of reading. In this paper, the authors present a semi-automatic approach to build learners' personality profiles based on their annotation traces yielded during active reading sessions. The experimental results show the system's efficiency to measure, with reasonable accuracy, the scores of learner's personality traits.

Many annotation systems proposed in the literature suffer from an under-exploitation of the annotation's semantic at the level of the assistance presented to the learner during annotative activity. Thus, these tools offer the same classic features to its users, such as management, search, sharing and storage of annotations. In this paper, we propose a new annotation system which differs in its novel features. The system tries to assist the learner via web services during learning activities. Therefore, from a user's annotation, our system is able to interpret a goal implicitly expressed and tries to discover and invoke a web service that can meet this annotation's objective. This system is based on an annotation model composed of an ontology and pattern annotation. This enrichment will provide advantages for both the provider, who will find his service within the consumer's reach, and the learner, who will have at his disposal an intelligent annotation tool.

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