Towards adaptive e-learning applications based on Semantic Web Services

The current state of the art in supporting E-Learning objectives is primarily based on providing a learner with learning content by using metadata standards like ADL SCORM 2004 or IMS Learning Design. By following this approach, several issues can be observed including high development costs due to a limited reusability across different standards and learning contexts. To overcome these issues, our approach changes this data-centric paradigm to a highly dynamic service-oriented approach. By following this approach, learning objectives are supported based on a automatic allocation of services instead of a manual composition of learning data. Our approach is fundamentally based on current Semantic Web Service (SWS) technology and considers mappings between different learning metadata standards as well as ontological concepts for E-Learning. Since our approach is based on a dynamic selection and invocation of SWS appropriate to achieve a given learning objective within a specific learning context, it enables the dynamic adaptation to specific learning needs as well as a high level of reusability across different learning contexts

Adressing context-awareness and standards interoperability in e-learning: a service-oriented framework based on IRS III

Current technologies aimed at supporting learning goals primarily follow a data and metadata-centric paradigm. They provide the learner with appropriate learning content packages containing the learning process description as well as the learning resources. Whereas process metadata is usually based on a certain standard specification – such as ADL SCORM or the IMS Learning Design – the used learning resources – data or services - are specific to pre-defined learning contexts, and they are allocated manually at design-time. Therefore, a content package cannot consider the actual learning context, since this is only known at runtime of a learning process. These facts limit the reusability of a content package across different standards and contexts. To overcome these issues, this paper proposes an innovative Semantic Web Service-based approach that changes this data- and metadata-based paradigm to a context-adaptive service-oriented approach. In this approach, the learning process is semantically described as a standard-independent process model decomposed into several learning goals. These goals are accomplished at runtime, based on the automatic allocation of the most appropriate service. As a result, we address the dynamic adaptation to specific context and - providing the appropriate mappings to established metadata standards - we enable the reuse of the defined semantic learning process model across different standards. To illustrate the application of our approach and to prove its feasibility, a prototypical application based on an initial use case scenario is proposed

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

Context-adaptive learning designs by using semantic web services

IMS Learning Design (IMS-LD) is a promising technology aimed at supporting learning processes. IMS-LD packages contain the learning process metadata as well as the learning resources. However, the allocation of resources - whether data or services - within the learning design is done manually at design-time on the basis of the subjective appraisals of a learning designer. Since the actual learning context is known at runtime only, IMS-LD applications cannot adapt to a specific context or learner. Therefore, the reusability is limited and high development costs have to be taken into account to support a variety of contexts. To overcome these issues, we propose a highly dynamic approach based on Semantic Web Services (SWS) technology. Our aim is moving from the current data- and metadata-based to a context-adaptive service-orientated paradigm We introduce semantic descriptions of a learning process in terms of user objectives (learning goals) to abstract from any specific metadata standards and used learning resources. At runtime, learning goals are accomplished by automatically selecting and invoking the services that fit the actual user needs and process contexts. As a result, we obtain a dynamic adaptation to different contexts at runtime. Semantic mappings from our standard-independent process models will enable the automatic development of versatile, reusable IMS-LD applications as well as the reusability across multiple metadata standards. To illustrate our approach, we describe a prototype application based on our principles

Ontology-Based Intelligent Agents in Workplace eLearning

Despite the ever increasing practices of e-learning, most workplace e-learning applications fail to meet the learners’ needs and ultimately fail to serve the organization’s quest for success. The dominance of technology-oriented approaches makes e-learning applications less goal-effective, and makes them perceived to be of poor quality and design. To solve this problem, a performance oriented approach is presented in this study. This approach aims to align the individual learning needs vis-à-vis the organizational goals and makes learning connected with work performance. Based on the approach, a prototype system has been developed that uses intelligent agent and ontology technology. A set of experiments have been conducted to demonstrate the effectiveness of the approach

Conceptualizing the e-Learning Assessment Domain using an Ontology Network

During the last year, approaches that use ontologies, the backbone of the Semantic Web technologies, for different purposes in the assessment domain of e-Learning have emerged. One of these purposes is the use of ontologies as a mean of providing a structure to guide the automated design of assessments. The most of the approaches that deal with this problem have proposed individual ontologies that model only a part of the assessment domain. The main contribution of this paper is an ontology network, called AONet, that conceptualizes the e-assessment domain with the aim of supporting the semi-automatic generation of it. The main advantage of this network is that it is enriched with rules for considering not only technical aspects of an assessment but also pedagogic

Open Source and Open Standards

Publication reference: Koper, R. (2008). Open Source and Open Standards. In J. M. Spector, M. Merrill, J. van Merriënboer & M. P. Driscol (Eds.), Handbook of Research on Educational Communications and Technology (3rd ed., pp. 355-368). New York: Routledge.The objective of this chapter is to create an understanding of the importance of open source software and open standards (OSS/OS) for e-learning research. Open source is a fundamental new way to develop software, and open standards are needed to make software components work together. It is argued that OSS and OS can improve the convergence of knowledge in the e-learning field, improve the general quality and interoperability of e-learning applications, and improve collaboration between researchers and users. All of these are beneficial and necessary requirements for e-learning research. After a general introduction into basic OSS and OS concepts, the following questions will be answered: a) How does OSS/OS facilitate the technological activities of the researchers in terms of methodology, collaboration and dissemination of results? b) How does OSS/OS facilitate the development of technological knowledge in the field? c) How does OSS/OS facilitate the development of technological artifacts in the field? The development and use of the open standard “IMS Learning Design” (a formal design language for online courses), and the open source applications that are developed to run and present IMS Learning Design courses will be used as an example to demonstrate the use of OSS/OS in e-learning research. In the concluding section we provide some practical information for researchers how to get involved in OSS and OS and how to use it in e-learning research

Creating a performance-oriented e-learning environment: A design science approach

E-learning is now being used by many organizations as an approach for enhancing the skills of knowledge workers. However, most applications have performed poorly in motivating employee learning, being perceived as less effective due to a lack of alignment of learning with work performance. To help solve this problem, we developed a performance-oriented approach using design science research methods. It uses performance measurement to clarify organizational goals and individual learning needs and links them to e-learning applications. The key concept lies in a Key Performance Indicator model, where organizational mission and vision are translated into a set of targets that drive learning towards a goal of improving work performance. We explored the mechanisms needed to utilize our approach and examined the necessary conceptual framework and implementation details. To demonstrate the effectiveness of the approach, a prototype workplace e-learning system was developed and used to evaluate the effectiveness of our approach. © 2011 Elsevier B.V. All rights reserved.postprin

EAOnto: a heavyweight ontology for supporting e-assessment generation

Different approaches that use ontology as a tool for generating, organizing and personalizing e-learning content can be found in literature. In the context of e-assessment, the notion of ontology has been used for different purposes. One of them is the use of ontologies as a mean of providing a structure to guide the automated design of assessments. Despite of the effort done in this direction, there is still a lot of work to be done since the most of the approaches have proposed lightweight ontologies that model a part of the assessment domain without considering pedagogical aspects. This paper presents a heavyweight ontology, called EAOnto, that conceptualizes the e-assessment domain including a set of rules representing pedagogical principles that are worth to follow. In addition, an empirical evaluation is discussed.Eje: Workshop Tecnología informática aplicada en educación (WTIAE)Red de Universidades con Carreras en Informática (RedUNCI