7,041 research outputs found

    An E-Learning Investigation into Learning Style Adaptivity

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    Personalised trails and learner profiling within e-learning environments

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    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

    Introducing teachers and instructional developers to learning objects Four suggested shifts in prevailing discourse

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    peer reviewedBeing convinced that the learning objects yields value creation promises for e-learning, the author, drawing on state-of-the art literature, his experience of two European projects dealing with learning objects and his experience as a teacher, documents 4 issues regarding teachers' awareness and acceptance of this emergent instructional design approach.iClas

    A design of a multi-agent recommendation system using ontologies and rule-based reasoning: pandemic context

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    Learners attend their courses in remote or hybrid systems find it difficult to follow one size fits all courses. These difficulties have increased with the pandemic, lockdown, and the stress they cause. Hence, the role of adaptive systems to recommend personalized learning resources according to the learner's profile. The purpose of this paper is to design a system for recommending learning objects according learner's condition, including his mental state, his COVID-19 history, as well as his social situation and ability to connect to the e-learning system on a regular basis. In this article, we present an architecture of a recommendation system for personalized learning objects based on ontologies and on rule-based reasoning, and we will also describe the inference rules required for the adaptation of the educational content to the needs of the learners, taking into account the learner’s health and mental state, as well as his social situation. The system designed, and validated using the unified modeling language (UML). It additionally allows teachers to have a holistic view of learners’ progress and situations

    The use of accessibility metadata in e‑learning environments: a systematic literature review

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    E-learning environments constitute an essential element in education, as they help students to ensure their pass their courses and graduate on time. Although guidelines, techniques, and methods have been presented in some literature in recent years to contribute to the development of accessible e-learning environments that promote digital inclusion, their implementation is challenging. In this context, the use of accessibility metadata not only provides a way to enhance the description of adapted educational resources but also facilitates their search according to the needs and preferences of students, in particular those with disabilities. In this paper, a systematic review was conducted in order to provide the state of the art regarding the use of accessibility metadata in e-learning environments. A total of 746 documents were found during the period from 2012 to 2019, of which 31 were selected according to the inclusion and exclusion criteria relevant to our review. The findings revealed an intensive use of models and standards of accessibility in e-learning environments, however, using accessibility metadata remains underused. In fact, the evaluation of accessibility and adaptability through the use of its metadata was not found. The fndings obtained also helped to establish challenges and opportunities in this research feld as well as to provide an overview that could support those who generate educational resources to keep their interest in making them accessible.publishedVersio

    Adaptivity in E-learning systems

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    Multimodal teaching, learning and training in virtual reality: a review and case study

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    It is becoming increasingly prevalent in digital learning research to encompass an array of different meanings, spaces, processes, and teaching strategies for discerning a global perspective on constructing the student learning experience. Multimodality is an emergent phenomenon that may influence how digital learning is designed, especially when employed in highly interactive and immersive learning environments such as Virtual Reality (VR). VR environments may aid students' efforts to be active learners through consciously attending to, and reflecting on, critique leveraging reflexivity and novel meaning-making most likely to lead to a conceptual change. This paper employs eleven industrial case-studies to highlight the application of multimodal VR-based teaching and training as a pedagogically rich strategy that may be designed, mapped and visualized through distinct VR-design elements and features. The outcomes of the use cases contribute to discern in-VR multimodal teaching as an emerging discourse that couples system design-based paradigms with embodied, situated and reflective praxis in spatial, emotional and temporal VR learning environments
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