492 research outputs found

    Systematising Learning and Research Information

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    This paper considers the ways in which information of relevance to the learning and research communities is organised and used. It contends that there is considerable overlap between the different types of online resources and information currently available within education. It describes some of the structured environments and data stores that have emerged in recent years, along with standards which are attempting to define the properties of discrete learning objects, through the specification of Learning Object Metadata (LOM). The paper contends that current developments of structured learning environments such as Managed and Virtual Learning Environments (MLEs and VLEs) are occurring on the whole in parallel to resource data stores, such as information gateways and portals. This discrepancy has arisen in part because these developments have occurred independently of one another and in part because there has to date been no rigorous definition of the underlying theoretical models. Furthermore, it argues that these predefined structured environments are unlikely to be sufficient to meet the information needs of users in different contexts. The paper goes on to describe an information toolkit, which provides a way of systematising information handling in learning and research, which helps users articulate information plans within specific contexts. The paper concludes with a description of two case studies which illustrate how this toolkit can be used

    Adaptive course sequencing for personalization of learning path using neural network

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    Advancements in technology have led to a paradigm shift fromtraditional to personalized learning methods with varied implementationstrategies. Presenting an optimal personalized learning path in aneducational hypermedia system is one of the strategies that is important inorder to increase the effectiveness of a learning session for each student.However, this task requires much effort and cost particularly in definingrules for the adaptation of learning materials. This research focuses onthe adaptive course sequencing method that uses soft computingtechniques as an alternative to a rule-based adaptation for an adaptivelearning system. The ability of soft computing technique in handlinguncertainty and incompleteness of a problem is exploited in the study. Inthis paper we present recent work concerning concept-based classificationof learning object using artificial neural network (ANN). Self OrganizingMap (SOM) and Back Propagation (BP) algorithm were employed todiscover the connection between the domain concepts contained in thelearning object and the learner’s learning need. The experiment resultshows that this approach is assuring in determining a suitable learningobject for a particular student in an adaptive and dynamic learning environment

    A Knowledge Representation Model for Massive Open Online Course Platforms

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    This paper describes a knowledge model for the design of Massive Open Online Course (MOOC) platforms. It is based on our generic instructional engineering method called Knowledge Field of Educational Environment with Competence Boundary Conditions (KFEEC). KFEEC uses the ontology as a foundation for the knowledge representation model. It provides a flexible structure to the various self-paced e-learning system designs but appears to be overcomplicated for the MOOC platform. This paper describes the KFEEC method, the steps of adapting the KFEEC to the MOOC platform design, and the specification of the resulting knowledge model. This model is a core of the MOOC platform that will be developed in future work

    Accessibility and adaptability of learning objects: responding to metadata, learning patterns and profiles of needs and preferences

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    The case for learning patterns as a design method for accessible and adaptable learning objects is explored. Patterns and templates for the design of learning objects can be derived from successful existing learning resources. These patterns can then be reused in the design of new learning objects. We argue that by attending to criteria for reuse in the definition of these patterns and in the subsequent design of new learning objects, those new resources can be themselves reusable and also adaptable to different learning contexts. Finally, if the patterns identified can be implemented as templates for standard authoring tools, the design of effective, reusable and adaptable resources can be made available to those with limited skills in multimedia authoring and result in learning resources that are more widely accessible

    Learning European history and geography in a multicultural and ICT perspective

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    Despite official educational guidelines, improved linguistic skills have been limited in all partner countries due to cuts in their national budgets. As a consequence, fewer CLIL experiences have been supported, to the benefit of those involving English. Another reason for this project resides in the difficulty in modifying the guidelines of national programmes, which are often short-sighted as far as other cultures are concerned. Finally, all European reports point out the shortage of materials and ICT-based contents suitable for interdisciplinary and multicultural education at school. The Multicultural Interdisciplinary Handbook (MIH) project meets these needs by providing new tools that will help teachers and pupils to plunge deeper into the culture and the language of another nation via its history and its landscape/geography. Moreover, it intends to promote a common European identity, as it introduces a European perspective in the schools ’ History and Geography syllabuses, which are usually limited to national borders

    Authoring and Sharing of Programming Exercises

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    In recent years, a number of exercises have been developed and published for educating students in the field of Computer Science. But these exercises exist in their own silos. There is no apparent mechanism to share these exercises among researchers and instructors in an effective and efficient manner. Moreover, the developers of these programming exercises are generally using a proprietary system for automatic submission and grading of these exercises. Each of these systems dictates the persistent format of an exercise that may not be inter-operable with other automatic submission and grading systems. This project provides a solution to this problem by modeling a programming exercise into a Learning Object metadata definition. This metadata definition describes the learning resource in terms of its contents, classifications, lifecycle and several other relevant properties. A learning Object (LO) is persisted in a repository along with its metadata. This repository supports simple and advanced queries to retrieve LO s and export them to various commercially available or home-grown e-learning systems. In a simple query, keywords given by the user are matched against a number of metadata elements whereas an advanced query allows a user to specify values for specific metadata elements

    A novel algorithm for dynamic student profile adaptation based on learning styles

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    The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.E-learning recommendation systems are used to enhance student performance and knowledge by providing tailor- made services based on the students’ preferences and learning styles, which are typically stored in student profiles. For such systems to remain effective, the profiles need to be able to adapt and reflect the students’ changing behaviour. In this paper, we introduce new algorithms that are designed to track student learning behaviour patterns, capture their learning styles, and maintain dynamic student profiles within a recommendation system (RS). This paper also proposes a new method to extract features that characterise student behaviour to identify students’ learning styles with respect to the Felder-Silverman learning style model (FSLSM). In order to test the efficiency of the proposed algorithm, we present a series of experiments that use a dataset of real students to demonstrate how our proposed algorithm can effectively model a dynamic student profile and adapt to different student learning behaviour. The results revealed that the students could effectively increase their learning efficiency and quality for the courses when the learning styles are identified, and proper recommendations are made by using our method

    Building communities for the exchange of learning objects: theoretical foundations and requirements

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    In order to reduce overall costs of developing high-quality digital courses (including both the content, and the learning and teaching activities), the exchange of learning objects has been recognized as a promising solution. This article makes an inventory of the issues involved in the exchange of learning objects within a community. It explores some basic theories, models and specifications and provides a theoretical framework containing the functional and non-functional requirements to establish an exchange system in the educational field. Three levels of requirements are discussed. First, the non-functional requirements that deal with the technical conditions to make learning objects interoperable. Second, some basic use cases (activities) are identified that must be facilitated to enable the technical exchange of learning objects, e.g. searching and adapting the objects. Third, some basic use cases are identified that are required to establish the exchange of learning objects in a community, e.g. policy management, information and training. The implications of this framework are then discussed, including recommendations concerning the identification of reward systems, role changes and evaluation instruments
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