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A Semantic Knowledge Base for Personal Learning and Cloud Learning Environments

A Semantic Knowledge Base for Personal Learning and Cloud Learning Environments. Alexander Mikroyannidis Paul Lefrere Peter Scott Knowledge Media Institute The Open University, UK. Outline. ROLE & OpenLearn Transition from LMS to PLE / CLE Semantic knowledge base architecture

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A Semantic Knowledge Base for Personal Learning and Cloud Learning Environments

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  1. A Semantic Knowledge Base for Personal Learning and Cloud Learning Environments • Alexander Mikroyannidis • Paul Lefrere • Peter Scott • Knowledge Media Institute • The Open University, UK

  2. Outline • ROLE & OpenLearn • Transition from LMS to PLE / CLE • Semantic knowledge base architecture • Stakeholder clusters • Collaborative ontology management • Final remarks

  3. ROLE – Responsive Open Learning Environments • FP7 EU project - www.role-project.eu • Targeting the adaptivity of Personal Learning Environments – PLEs • PLEs: learner-centric approach, use of lightweight services and tools that belong to and are controlled by individual learners • CLEs: the users of cloud-based services are academics or learners, who share the same privileges, including control, choice, and sharing of content on these services

  4. OpenLearn – openlearn.open.ac.uk • Moodle-based OER (Open Educational Resource) initiative • Contains 13 topic areas with 519 units, with more than 6,000 study hours of repurposed open content (from Quality assured Open University course materials) • Topics: • Arts and History • Business and Management • Education • Health and Lifestyle • IT and Computing  • Law  • Mathematics and Statistics  • Modern Languages  • Science and Nature  • Society  • Study Skills  • Technology

  5. Transition from LMS to PLE / CLE • From the LMS-based approach of OpenLearn towards the PLE and CLE paradigms: • Putting emphasis to the needs and preferences of learners • Wide range of OER to choose from, both from OpenLearn as well as from Web 2.0 sources • OER mashups • OER recommendations based on information from their profiles and portfolios

  6. Semantic knowledge base architecture • A semantic knowledge base enables the use of metadata and ontologies to annotate learning resources, and model various aspects of the learning process

  7. Ontology pyramid layers • Learner layer: models the profiles of learners • IEEE LOM, IEEE PAPI, IMS LIP, IMS RDCEO • Learning Resource layer: models the learning resources of PLEs and CLEs • Widget annotations: user-generated tags or automatically generated semantic annotations • Learning Domain layer: models the learning domain • Domain ontologies • Lexical layer: domain-independent ontologies of a purely lexicographical nature • WordNet

  8. Stakeholder clusters

  9. Collaborative ontology management • Knowledge integration: Integration of contributions from multiple participants. Reusability and integration is supported through ontology mappings. • Concurrency management: In case the same part of the knowledge base is concurrently edited by more than one author, this can cause conflicts. Various technologies available (CVS, Wiki, etc). • Consistency maintenance: Mechanisms for structural and semantic consistency preservation as well as change propagation need to be provided to ensure that the knowledge base is free of inconsistencies at all times.

  10. Collaborative ontology management (contd.) • Privilege management: Different levels of privileges to its users, based on their expertise, authority, and responsibility. • History maintenance: Recover from wrong or unintended changes to the knowledge base. The bitemporal ontology model of Heraclitus II (Mikroyannidis, 2007) retains the necessary information to achieve this goal. • Scalability: Long-term collaboration of diverse parties usually increases the size of knowledge bases; therefore, a collaborative environment has to be scalable to large ontologies. This is particularly important in the abundant environment of CLEs, where a wide variety of cloud-based services is employed.

  11. Final remarks • PLEs and CLEs address the crucial demands of today’s learner for a personalized and adaptive learning environment. • For the OpenLearn life-long learner, learning activities are less formal and organized than for LMS users. • We cannot rely on there being a course plan, a dedicated teacher, or a well defined list of fellow students. Consequently, the subject being taught and learnt and the material being used are more flexible, mostly depending on the needs and competencies of the learner. • We perceive a semantically enhanced PLE or CLE as the evolution of the present OpenLearn environment, as well as the evolution of LMS-based approaches in general.

  12. Image sources: • http://www.flickr.com/photos/hanspoldoja/4098840001/ • http://www.flickr.com/photos/petahopkins/2157928982/ • http://www.flickr.com/photos/sarahmstewart/2530959378/ • http://www.flickr.com/photos/shangrilacorp/4053538657/ • http://www.flickr.com/photos/11016633@N07/2232831953/

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