380 research outputs found

    ICOPER Project - Deliverable 4.3 ISURE: Recommendations for extending effective reuse, embodied in the ICOPER CD&R

    Get PDF
    The purpose of this document is to capture the ideas and recommendations, within and beyond the ICOPER community, concerning the reuse of learning content, including appropriate methodologies as well as established strategies for remixing and repurposing reusable resources. The overall remit of this work focuses on describing the key issues that are related to extending effective reuse embodied in such materials. The objective of this investigation, is to support the reuse of learning content whilst considering how it could be originally created and then adapted with that ‘reuse’ in mind. In these circumstances a survey on effective reuse best practices can often provide an insight into the main challenges and benefits involved in the process of creating, remixing and repurposing what we are now designating as Reusable Learning Content (RLC). Several key issues are analysed in this report: Recommendations for extending effective reuse, building upon those described in the previous related deliverables 4.1 Content Development Methodologies and 4.2 Quality Control and Web 2.0 technologies. The findings of this current survey, however, provide further recommendations and strategies for using and developing this reusable learning content. In the spirit of ‘reuse’, this work also aims to serve as a foundation for the many different stakeholders and users within, and beyond, the ICOPER community who are interested in reusing learning resources. This report analyses a variety of information. Evidence has been gathered from a qualitative survey that has focused on the technical and pedagogical recommendations suggested by a Special Interest Group (SIG) on the most innovative practices with respect to new media content authors (for content authoring or modification) and course designers (for unit creation). This extended community includes a wider collection of OER specialists. This collected evidence, in the form of video and audio interviews, has also been represented as multimedia assets potentially helpful for learning and useful as learning content in the New Media Space (See section 4 for further details). Section 2 of this report introduces the concept of reusable learning content and reusability. Section 3 discusses an application created by the ICOPER community to enhance the opportunities for developing reusable content. Section 4 of this report provides an overview of the methodology used for the qualitative survey. Section 5 presents a summary of thematic findings. Section 6 highlights a list of recommendations for effective reuse of educational content, which were derived from thematic analysis described in Appendix A. Finally, section 7 summarises the key outcomes of this work

    The future of technology enhanced active learning – a roadmap

    Get PDF
    The notion of active learning refers to the active involvement of learner in the learning process, capturing ideas of learning-by-doing and the fact that active participation and knowledge construction leads to deeper and more sustained learning. Interactivity, in particular learnercontent interaction, is a central aspect of technology-enhanced active learning. In this roadmap, the pedagogical background is discussed, the essential dimensions of technology-enhanced active learning systems are outlined and the factors that are expected to influence these systems currently and in the future are identified. A central aim is to address this promising field from a best practices perspective, clarifying central issues and formulating an agenda for future developments in the form of a roadmap

    IMPROVING ADAPTIVE LEARNING IN A SMART LEARNING ENVIRONMENT

    Get PDF
    It has been broadly argued that, in the near future, the demand for skilled labor will increase whilst that for routine activities will decrease. In this regard, the need for making greater investments in education to re-skill workers and support continuous learning has been invoked as an essential requirement for preserving people’s employability.Digital technology is deemed increasingly necessary to sustain the educational endeavor, for the possibilities it offers to make more accessible and low-cost educational interventions. It allows for the creation of personalized learning paths and customized digital learning solutions, for courses to be available to a large attendance of learners, and for teaching-learning activities to be offered at significantly reduced cost.In this article, a learning unit structure designed to improve adaptive learning is proposed, and mechanisms for adaptive learning in a smart learning environment are discussed.The implemented teaching-learning solution is also illustrated. This is a preliminary application based on an approach that combines the teacher experience with learning analytics.

    Courseware Adaptation to Learning Styles and Knowledge Level

    Get PDF

    Personalised trails and learner profiling in an e-learning environment

    Get PDF
    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

    Using learning styles theory to improve on-line learning through computer assisted diagnosis

    Get PDF
    Despite the success in a number of education and training environments of a variety of Learning Styles diagnostic tools1,2 and particularly the success of Honey and Mumford3, there still appears to be a scarcity of research, development and action on the application of this work to e-learning. When we compare developments around the issues of, for example, content development and pedagogy4, authoring and packaging tools5, virtual and managed learning environments and interoperability6, or accessibility of learning products and services for disabled people7, we find comparatively little research and comparatively very little application of Learning Styles thinking to the development of e-learning products, services, environments and practices

    Models, Techniques and Applications of e-Learning Personalization

    Get PDF
    In recent years Web has become mainstream medium for communication and information dissemination. This paper presents approaches and methods for adaptive learning implementation, which are used in some contemporary web-interfaced Learning Management Systems (LMSs). The problem is not how to create electronic learning materials, but how to locate and utilize the available information in personalized way. Different attitudes to personalization are briefly described in section 1. The real personalization requires a user profile containing information about preferences, aims, and educational history to be stored and used by the system. These issues are considered in section 2. A method for development and design of adaptive learning content in terms of learning strategy system support is represented in section 3. Section 4 includes a set of innovative personalization services that are suggested by several very important research projects (SeLeNe project, ELENA project, etc.) dated from the last few years. This section also describes a model for role- and competency-based learning customization that uses Web Services approach. The last part presents how personalization techniques are implemented in Learning Grid-driven applications
    • 

    corecore