A semantic web services-based infrastructure for context-adaptive process support

Current technologies aimed at supporting processes whether it is a business or learning process - primarily follow a metadata- and data-centric paradigm. Whereas process metadata is usually based on a specific standard specification - such as the Business Process Modeling Notation (BPMN) or the IMS Learning Design Standard - the allocation of resources is done manually at design-time, and the used data is often specific to one process context only. These facts limit the reusability of process models across different standards and contexts. To overcome these issues, we introduce an innovative Semantic Web Service-based framework aimed at changing the current paradigm to a context-adaptive service-oriented approach. Following the idea of layered semantic abstractions, our approach supports the development of abstract semantic process model - reusable across different contexts and standards - that enables a dynamic adaptation to specific actor needs and objectives. To illustrate the application of our framework and establish its feasibility, we describe a prototypical application in the E-Learning domain

Discovering the Impact of Knowledge in Recommender Systems: A Comparative Study

Recommender systems engage user profiles and appropriate filtering techniques to assist users in finding more relevant information over the large volume of information. User profiles play an important role in the success of recommendation process since they model and represent the actual user needs. However, a comprehensive literature review of recommender systems has demonstrated no concrete study on the role and impact of knowledge in user profiling and filtering approache. In this paper, we review the most prominent recommender systems in the literature and examine the impression of knowledge extracted from different sources. We then come up with this finding that semantic information from the user context has substantial impact on the performance of knowledge based recommender systems. Finally, some new clues for improvement the knowledge-based profiles have been proposed.Comment: 14 pages, 3 tables; International Journal of Computer Science & Engineering Survey (IJCSES) Vol.2, No.3, August 201

Layered evaluation of interactive adaptive systems : framework and formative methods

Peer reviewedPostprin

Adaptive development and maintenance of user-centric software systems

A software system cannot be developed without considering the various facets of its environment. Stakeholders – including the users that play a central role – have their needs, expectations, and perceptions of a system. Organisational and technical aspects of the environment are constantly changing. The ability to adapt a software system and its requirements to its environment throughout its full lifecycle is of paramount importance in a constantly changing environment. The continuous involvement of users is as important as the constant evaluation of the system and the observation of evolving environments. We present a methodology for adaptive software systems development and maintenance. We draw upon a diverse range of accepted methods including participatory design, software architecture, and evolutionary design. Our focus is on user-centred software systems

Personalised trails and learner profiling within e-learning environments

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

The influence of student characteristics on the use of adaptive e-learning material

Adaptive e-learning materials can help teachers to educate heterogeneous student groups. This study provides empirical data about the way academic students differ in their learning when using adaptive elearning materials. Ninety-four students participated in the study. We determined characteristics in a heterogeneous student group by collecting demographic data and measuring motivation and prior knowledge. We also measured the learning paths students followed and learning strategies they used when working with adaptive e-learning material in a molecular biology course. We then combined these data to study if and how student characteristics relate to the learning paths and strategies they used. We observed that students did follow different learning paths. Gender did not have an effect, but (mainly Dutch) BSc students differed from (international) MSc students in the intrinsic motivation they had and the learning paths and strategies they followed when using the adaptive e-learning materia

Engineering modular web-based education systems to support EML units of learning

Educational Modeling Languages (EMLs) have been proposed to support the modeling of units of learning enabling the description of different pedagogical approaches. Eventually, such models are intended to support the operation of appropriate computer systems, controlling and managing the corresponding units of learning. This paper considers EMLs involving a set of independent perspectives. Our purpose is to use this set of perspectives to facilitate the development of Web-based education systems that are able to support the execution of EML models. As a result, we obtain a modular architecture where different pedagogical approaches can be supported.Education for the 21 st century - impact of ICT and Digital Resources ConferenceRed de Universidades con Carreras en Informática (RedUNCI