XML-based Adaptation Framework for Psychological-driven E-learning Systems

E-learning systems grew to popular knowledge delivery systems until now. Several applications have already been implemented and many project initiatives have been started. Although such systems come with interesting advantages, there are still many unsolved problems. Enriching common learning content by applying multimedia did not meet the general expectation to decrease drop out rates of e-learners using such systems. Additionally, most e-learners complain about a "one-size-fits-all " philosophy, a resulting cognitive overload and consequently the lack of personalization of existing applications. In this paper a user-centric approach is presented in order to improve the usability and acceptance, thus, making e-learning systems more successful. For this purpose psychological factors are integrated in an adaptable learning system which is based on meta data enriched learning objects specified and described in XML documents. General learning objects are transformed into personalized learning objects depending on the user profile and adaptation rules. Beside learning objects also layout and navigation through the content are adapted and personalized. An adaptation framework is introduced to show the interaction of the discussed concepts to fulfill the request for individualized learning systems

Semi-Automatically Generated Hybrid Ontologies for Information Integration

ABSTRACT Large and medium-sized enterprises and organizations are in many cases characterized by a heterogeneous and distributed information system infrastructure. For data processing activities as well as data analytics and mining, it is essential to establish a correct, complete and efficient consolidation of information. Information integration and aggregation are therefore fundamental steps in many analytical workflows. Furthermore, in order to evaluate and classify the result of an integrated data query and thus, the quality of resulting data analytics, it is previously necessary to determine the data quality of each processed data source. This paper aims mainly at the first aspect of the mentioned twofold challenge. Both, data dictionary as well as information source content are analyzed to derive the conceptual schema, which is then provided as a machine-readable description of the information source semantics. Several descriptions of the semantics can be integrated to a global view by eliminating possible redundancies and by applying ontology similarity measures. Attributes for data quality metrics are included in the descriptions but not yet determined. The implementation of the presented approach is evaluated by extracting the semantics of a specific MySQL database, represented as RDF triples

Virtually Guided Personalized E-Learning

Abstract. E-learning systems are tremendously popular. Lifelong learning, learning anytime and anywhere are one of most effective slogans for pushing distance learning. Unfortunately, the promises that all learners benefit from elearning could not be kept. The amount of frustrated, un-motivated users is quite huge proved by high drop out rates. Despite enormous efforts to provide high-level multimedia learning lessons, most e-learners complain about a "onesize-fits-all" philosophy, a resulting cognitive overload and consequently the lack of personalization of existing applications. The work presented in this paper introduces an approach of how to make e-learning systems more usercentric with respect to psychological differences and individualities. The big step from common to personalized e-learning is realized through the introduction of multi-level topic maps. Psychological factors such as cognitive styles, learning modalities, learning strategies, aspects relevant for managing the learning environment, and learning objects are represented as topics associated in networks to build individual learning sequences and surroundings. Single output depends on the chosen path taken in the topic maps, whereby this decision is supported through virtual guidance provided by the system

Active Data Integration for Distribution of Up-to-date Tourism Media

Abstract. The importance of the World Wide Web to gather information on any topic in the field of tourism grows more and more. This is because of the vast quantity and broad spectrum of tourism information that are already distributed on various Web sites. The information requested by the tourist is diversified. Every information, which can be associated with the vacation, could be of interest. The efficient use oft the existing information is limited by time wasting locating and filtering of information in the Web. Missing options for defining personal preferences requires the tourist to scan the whole information provided. Beside tourists also provider of touristic products use information systems to make information of different categories available for their clients. Information technology support could achieve tremendous time saving, especially if the generation of media and the distribution have to be done periodically. The approach described in this paper demonstrates how automating the collecting, rehashing and distributing of the information can unburden information provider and consumer.