Adaptive System for Collaborative Online Laboratories

International audienceIn the last decade, researchers in the Online Engineering field have attempted to provide hands-on, web-based approaches for Distance Learning. The primary goal of this research is to produce online laboratories that serve as the educational substitute for in situ laboratories. A limitation of existing online laboratories, however, is that they generally only allow a single user to be connected at a time. Since group learning activities, such as peer assistance, peer emulation, and collaborative experimental setup, are core dimensions of the traditional laboratory experience, this shortcoming is a significant pedagogical bottleneck. Recent research has focused on creating Collaborative Online Laboratories (COL) which attempt to address this shortcoming by focusing on the group awareness aspect of the laboratory learning experience. This paper discusses how group awareness can serve as a key component in replicating the collaborative aspect of learning in local laboratories. We discuss strategies for describing group awareness and how these strategies are associated both with a tutor's pedagogical objectives and in the management of the group of collaborating students. We describe an experimental system that we have developed that uses Semantic Web technologies to define a knowledge-driven system that allows researchers to describe and execute a variety of collaborative strategies for online laboratories

Design of a performance-oriented workplace e-learning system using ontology

E-learning is emerging as a popular learning approach utilized by many organizations. Despite the ever increasing practices of e-learning in the workplace, most e-learning applications fail to meet learners' needs or serve organization's quests for success. Significant gaps exist between organizational interests and individual needs when they come to e-learning, which make e-learning applications less goal-effective. To solve this problem, a performance-oriented approach is presented in this study. Key performance indicators (KPIs) are set up to clarify organizational training needs, and help learners establish rational learning objectives. In addition, ontology is used for constructing formal and machine-understandable conceptualization of the performance-oriented learning environment. Using this approach, a KPI-oriented learning ontology and prototype system have been developed and evaluated to demonstrate the effectiveness of the approach. © 2010 Elsevier Ltd. All rights reserved.postprin

Proporcionar experiencias de aprendizaje ubicuo mediante la combinación de Internet de las Cosas y los estándares de e-Learning

[ES]Actualmente, el aprendizaje está teniendo lugar con mayor frecuencia en cualquier lugar y en cualquier momento. Esto implica que los ambientes del aprendizaje electrónico se expandan desde los entornos de aprendizaje solo virtuales a entornos que implican espacios físicos. Gracias a la evolución de Internet, las TIC (Tecnologías de la Información y Comunicación) y a la Internet de las Cosas, se pueden experimentar nuevos escenarios de aprendizaje por parte de los estudiantes, ya sea individualmente o en colaboración. Estos escenarios de aprendizaje ubicuos, permiten compaginar tanto ambientes virtuales como ambientes físicos. Por tanto, estas experiencias se caracterizan por las interacciones posibles del estudiante con el entorno físico, la detección de los datos contextuales, y también la adaptación de las estrategias pedagógicas y de los servicios según el contexto. Este artículo pretende aprovechar esta tendencia y sustentarla en las normas existentes de aprendizaje electrónico como IMS LD y LOM. La solución propuesta es extender los modelos de normas de aprendizaje electrónico como IMS LD y LOM para soportar Internet de las Cosas y para aportar un enfoque de adaptación de las actividades de aprendizaje según el contexto del estudiante y su huella digital utilizando la API eXperience. En este contexto y con el fin de permitir las capacidades de razonamiento y la interoperabilidad entre los modelos propuestos se proponen representaciones ontológicas y una implementación de la solución. Además, se plantea una arquitectura técnica que resalta los componentes de software necesarios y sus interacciones. Y, por último, se implementa y se evalúa un escenario de aprendizaje ubicuo

A framework for developing engineering design ontologies within the aerospace industry

This paper presents a framework for developing engineering design ontologies within the aerospace industry. The aim of this approach is to strengthen the modularity and reuse of engineering design ontologies to support knowledge management initiatives within the aerospace industry. Successful development and effective utilisation of engineering ontologies strongly depends on the method/framework used to develop them. Ensuring modularity in ontology design is essential for engineering design activities due to the complexity of knowledge that is required to be brought together to support the product design decision-making process. The proposed approach adopts best practices from previous ontology development methods, but focuses on encouraging modular architectural ontology design. The framework is comprised of three phases namely: (1) Ontology design and development; (2) Ontology validation and (3) Implementation of ontology structure. A qualitative research methodology is employed which is composed of four phases. The first phase defines the capture of knowledge required for the framework development, followed by the ontology framework development, iterative refinement of engineering ontologies and ontology validation through case studies and experts’ opinion. The ontology-based framework is applied in the combustor and casing aerospace engineering domain. The modular ontologies developed as a result of applying the framework and are used in a case study to restructure and improve the accessibility of information on a product design information-sharing platform. Additionally, domain experts within the aerospace industry validated the strengths, benefits and limitations of the framework. Due to the modular nature of the developed ontologies, they were also employed to support other project initiatives within the case study company such as role-based computing (RBC), IT modernisation activity and knowledge management implementation across the sponsoring organisation. The major benefit of this approach is in the reduction of man-hours required for maintaining engineering design ontologies. Furthermore, this approach strengthens reuse of ontology knowledge and encourages modularity in the design and development of engineering ontologies

A hybrid e-learning framework: Process-based, semantically-enriched and service-oriented

Despite the recent innovations in e-Learning, much development is needed to ensure better learning experience for everyone and bridge the research gap in the current state of the art e-Learning artefacts. Contemporary e-learning artefacts possess various limitations as follows. First, they offer inadequate variations of adaptivity, since their recommendations are limited to e-learning resources, peers or communities. Second, they are often overwhelmed with technology at the expense of proper pedagogy and learning theories underpinning e-learning practices. Third, they do not comprehensively capture the e-learning experiences as their focus shifts to e-learning activities instead of e-learning processes. In reality, learning is a complex process that includes various activities and interactions between different roles to achieve certain gaols in a continuously evolving environment. Fourth, they tend more towards legacy systems and lack the agility and flexibility in their structure and design. To respond to the above limitations, this research aims at investigating the effectiveness of combining three advanced technologies (i.e., Business Process Modelling and Enactment, Semantics and Service Oriented Computing – SOC–) with learning pedagogy in order to enhance the e-learner experience. The key design artefact of this research is the development of the HeLPS e-Learning Framework – Hybrid e-Learning Framework that is Process-based, Semantically-enriched and Service Oriented-enabled. In this framework, a generic e-learning process has been developed bottom-up based on surveying a wide range of e-learning models (i.e., practical artefacts) and their underpinning pedagogies/concepts (i.e., theories); and then forming a generic e-learning process. Furthermore, an e-Learning Meta-Model has been developed in order to capture the semantics of e-learning domain and its processes. Such processes have been formally modelled and dynamically enacted using a service-oriented enabled architecture. This framework has been evaluated using a concern-based evaluation employing both static and dynamic approaches. The HeLPS e-Learning Framework along with its components have been evaluated by applying a data-driven approach and artificially-constructed case study to check its effectiveness in capturing the semantics, enriching e-learning processes and deriving services that can enhance the e-learner experience. Results revealed the effectiveness of combining the above-mentioned technologies in order to enhance the e-learner experience. Also, further research directions have been suggested.This research contributes to enhancing the e-learner experience by making the e-learning artefacts driven by pedagogy and informed by the latest technologies. One major novel contribution of this research is the introduction of a layered architectural framework (i.e., HeLPS) that combines business process modelling and enactment, semantics and SOC together. Another novel contribution is adopting the process-based approach in e-learning domain through: identifying these processes and developing a generic business process model from a set of related e-learning business process models that have the same goals and associated objectives. A third key contribution is the development of the e-Learning Meta-Model, which captures a high-abstract view of learning domain and encapsulates various domain rules using the Semantic Web Rule Language. Additional contribution is promoting the utilisation of Service-Orientation in e-learning through developing a semantically-enriched approach to identify and discover web services from e-learning business process models. Fifth, e-Learner Experience Model (eLEM) and e-Learning Capability Maturity Model (eLCMM) have been developed, where the former aims at identifying and quantifying the e-learner experience and the latter represents a well-defined evolutionary plateau towards achieving a mature e-learning process from a technological perspective. Both models have been combined with a new developed data-driven Validation and Verification Model to develop a Concern-based Evaluation Approach for e-Learning artefacts, which is considered as another contribution

An Integrated Approach for Automatic\ud Aggregation of Learning Knowledge Objects

This paper presents the Knowledge Puzzle, an ontology-based platform designed to facilitate domain\ud knowledge acquisition from textual documents for knowledge-based systems. First, the\ud Knowledge Puzzle Platform performs an automatic generation of a domain ontology from documents’\ud content through natural language processing and machine learning technologies. Second,\ud it employs a new content model, the Knowledge Puzzle Content Model, which aims to model\ud learning material from annotated content. Annotations are performed semi-automatically based\ud on IBM’s Unstructured Information Management Architecture and are stored in an Organizational\ud memory (OM) as knowledge fragments. The organizational memory is used as a knowledge\ud base for a training environment (an Intelligent Tutoring System or an e-Learning environment).\ud The main objective of these annotations is to enable the automatic aggregation of Learning\ud Knowledge Objects (LKOs) guided by instructional strategies, which are provided through\ud SWRL rules. Finally, a methodology is proposed to generate SCORM-compliant learning objects\ud from these LKOs

Enabling smart learning systems within smart cities using open data

Deploying ad-hoc learning environments to use and represent data from multiple sources and networks and to dynamically respond to user demands could be very expensive and ineffective in the long run. Moreover, most of the available data is wasted without extracting potentially useful information and knowledge because of the lack of established mechanisms and standards. It is preferable to focus on data availability to choose and develop interoperability strategies suitable for smart learning systems based on open standards and allowing seamless integration of third-party data and custom applications. This paper highlights the opportunity to take advantage of emerging technologies, like the linked open data platforms and automatic reasoning to effectively handle the vast amount of information and to use data linked queries in the domain of cognitive smart learning systems

Computerization of workflows, guidelines and care pathways: a review of implementation challenges for process-oriented health information systems

There is a need to integrate the various theoretical frameworks and formalisms for modeling clinical guidelines, workflows, and pathways, in order to move beyond providing support for individual clinical decisions and toward the provision of process-oriented, patient-centered, health information systems (HIS). In this review, we analyze the challenges in developing process-oriented HIS that formally model guidelines, workflows, and care pathways. A qualitative meta-synthesis was performed on studies published in English between 1995 and 2010 that addressed the modeling process and reported the exposition of a new methodology, model, system implementation, or system architecture. Thematic analysis, principal component analysis (PCA) and data visualisation techniques were used to identify and cluster the underlying implementation ‘challenge’ themes. One hundred and eight relevant studies were selected for review. Twenty-five underlying ‘challenge’ themes were identified. These were clustered into 10 distinct groups, from which a conceptual model of the implementation process was developed. We found that the development of systems supporting individual clinical decisions is evolving toward the implementation of adaptable care pathways on the semantic web, incorporating formal, clinical, and organizational ontologies, and the use of workflow management systems. These architectures now need to be implemented and evaluated on a wider scale within clinical settings

Towards a generalised e-learning business process model

Modelling learning scenarios is central for e-learning domain. This has been manifested in the proliferation of the different Educational Modelling Languages, as well as in developed e-learning models. However, the existing modelled scenarios are deficient as they lack flexibility and the agility to respond to the dynamic nature of an e-learning process that is suitable to answer learners’ needs. This paper proposes a novel approach to develop a generalised business process model from a set of related business processes sharing the same goals and associated objectives. The proposed approach has been applied in the e-learning domain, which demonstrated its ability to develop a generalised e-learning business process model that is derived from the existing pedagogical models and technology-enhanced learning artefacts. Moreover, the proposed approach has been evaluated to test its effectiveness in generalising a set of business processes, which paves the ground to apply it in different contexts. The generalised e-learning business process model has been modelled using the industrial standard Business Process Modelling Notations (BPMN 2.0) so that processes can be dynamically enacted in service-oriented environments and, at the same time, adapting to answering e-learners’ learning requirements