Currently, adaptive educational hypermedia systems (AEHS) are described with nonuniform methods, depending on the specific view on the system, the application, or other parameters. There is no common language for expressing functionality of AEHS, hence these systems are difficult to compare and analyze.

Traditional adaptive hypermedia systems have focused on providing adaptation functionality on a closed corpus, while Web search interfaces have delivered non-personalized information to users. In this paper, we show how we integrate closed corpus adaptation and global context provision in a Personal Reader environment. The local context consists of individually optimized recommendations to learning materials within the given corpus; the global context provides individually optimized recommendations to resources found on the Web, e. g., FAQs, student exercises, simulations, etc. The adaptive local context of a learning resource is generated by applying methods from adaptive educational hypermedia in a semantic web setting. The adaptive global context is generated by constructing appropriate queries, enrich them based on available user profile information, and, if necessary, relax them during the querying process according to available metadata.

ActiveMath is a complex Web-based adaptive learning environment with a number of components and interactive learning tools. The basis for handling semantics of learning content is provided by its semantic (mathematics) content markup which is additionally annotated with educational metadata. Several components, tools, and external services can make use of that content markup, for instance a course generator, a semantic search engine, and user input evaluation services. The components and services have to communicate, pass content and state changes, actions, etc including mathematical semantics and educational markup. The novel event infrastructure supports this communication. This article focuses on usage of the content’s semantics by selected novel components and sketches the communication.

In the last years, important steps have been undertaken to bring the e-learning web to its full potential.

In this paper, we integrate WebML, a high-level model and technology for building server-side Web applications, with UML-Guide, a UML-based system that generates client-side guides for the adaptation of Web applications.

It is extremely challenging to get an overview of the current state-of-the-art in technology enhanced learning in Europe. Rapid technological and pedagogical innovations, constantly changing markets, a vivid number of small and medium enterprises, complex policy processes, ongoing political and societal debates on the pros and cons of technology enhanced leaning, combined with many languages and different cultures, make it almost impossible for people to be informed. We want to introduce the media base and the measure tools for pattern-based cross media social network analysis, created by the PROLEARN network of excellence in professional learning. The main goal of this endeavour is the reduction of complexity for actors in digital social networks by applying ideas from social software and already successful methods for complexity reduction, such as information visualization, social network analysis and pattern languages.

Abstract. Research in Cooperative Query answering is triggered by the observation that users are often not able to correctly formulate queries to databases that return the intended result. Due to a lack of knowledge of the contents and the structure of a database, users will often only be able to provide very broad queries. Existing methods for automatically refining such queries based on user profiles often overshoot the target resulting in queries that do not return any answer. In this paper, we investigate methods for automatically relaxing such over-constraint queries based on domain knowledge and user preferences. We describe a framework for information access that combines query refinement and relaxation in order to provide robust, personalized access to heterogeneous RDF data as well as an implementation in terms of rewriting rules and explain its application in the context of e-learning systems. 1

Abstract. This chapter emphasizes integration of the Semantic Web technologies in intelligent learning systems by giving a proposal for an intelligent learning management system (ILMS) architecture we named Multitutor. This system is a Web-based environment for the development the e-learning courses and for the use of them by the students. Multitutor is designed as a Web-classroom client-server system, ontologically founded, and is built using modern intelligent and Web-related technologies. This system enables the teachers to develop tutoring systems for any course. The teacher has to define the metadata of the course: chapters, the lessons and the tests, the references of the learning materials. 1

Abstract: Adaptive learning systems typically involve learner profiles with sensitive information and activities that might breach learner’s privacy, such as tracking, profiling or collaborative filtering. In this paper we discuss privacy aspects of personalisation and adaptation in smart spaces for learning. A smart space for learning is a system for mediation of learning services, which is being developed in the EU IST ELENA project. We present privacy threats and requirements in smart spaces for learning with focus on a learner, we model learner profile data that are necessary for privacy protection, and propose privacy-enhancing technology based solutions.

The challenge of the semantic web is the provision of distributed information with well defined meaning, understandable for different parties. Particularly, applications should be able to provide individually optimized access to information by taking the individual needs and requirements of the users into account. In this paper we propose a framework for personalized e-Learning in the semantic web and show how the semantic web resource description formats can be utilized for automatic generation of hypertext structures from distributed metadata. Ontologies and metadata for three types of resources (domain, user, and observation) are investigated. We investigate a logic-based approach to educational hypermedia using TRIPLE, a rule and query language for the semantic web. keywords: Educational hypermedia, Semantic web, Ontologies, Adaptive hypermedia, Reasoning on the semantic web.