2010-04-14 EDUCON eMadrid UMH (UPM) Oscar Martínez

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2010-04-14
Sem eMadrid
Oscar Martínez
EDUCON2010

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2010-04-14 EDUCON eMadrid UMH (UPM) Oscar Martínez

  1. 1. An Approach for Description of Open Educational Resources based on Semantic Technologies Nelson Piedra, Janneth Chicaiza, Jorge López Escuela Ciencias Computación, Universidad Técnica Particular Loja, Ecuador Oscar Martínez Bonastre, Centro de Investigación Operativa Universidad Miguel Hernández, España Edmundo Tovar Caro, Facultad de Informática, Universidad Politécnica de Madrid, España IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  2. 2. Outline • Introduction • OER: Using metadata and Ontologies • OER-CC ontology: Development process • OER-CC: Instantiation and Retrieval – Instantiation process – Information Retrieval • Conclusions • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  3. 3. Introduction • Open Educational Resources (OERs) initiatives promote their global exchange with the aim of increasing the human intellectual capacity. • Technology in general, and specifically Web, provides an interesting opportunity for people to get key competences while they´re using or even also sharing digital contents. • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  4. 4. Introduction • OER are teaching, learning, research digital resources and tools, which are available on the public domain or have been released under an intellectual property license, i.e., they allow their free use or even also be reusable by others. • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  5. 5. Introduction We hypothesized that growth of OER data repository should make difficult to find out information of value, i.e, it reduces possibilities of sharing educational resources. Consequently, we evaluated some solutions like • Using semantic technologies to describe OER could enable any agent (human or software-based) to process and understand content (applying inference rules to structured knowledge) • Metadata standards could be used to annotate OER, i.e., they´d improve their interoperability and discovery of knowledge. • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  6. 6. OER: Using metadata and Ontologies • The Open Educational Resources Initiatives are based on Open Access (OA) movement. • OER Projects can be classified according to used model (funding, technical, content and staffing) to ensure their sustainability. – producer-consumer models – Co-production models • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  7. 7. OER: Using metadata and Ontologies • Using semantics in OER Production – Semantic technologies would automate or semi- automate certain educative tasks through “synergy between human and machines” – People are the producers and customers: they are the source of knowledge and they request information also. – Machines are the enablers: they store and remember data, search and combine data, draw mathematical and logical inferences, etc.” • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  8. 8. OER: Using metadata and Ontologies • Using semantics in OER Production – Semantic technologies could automate certain educative tasks through “synergy between human and machines” • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  9. 9. OER: Using metadata and Ontologies • Using semantics in OER Production – To achieve these objectives, OER should be described by a standard schema in a way that any agent (human or software-based) could understand and processing its content. • Metadata Standards for Educational Material standards: – The IEEE LTSC (Learning Technology Standard Committee) developed IEEE LOM (Learning Object Metadata). – The IMS GLC (Global Learning Consortium) proposes IMS Learning Resource Metadata. – Dublin Core Metadata Initiative. • Ontologies: – METHONTOLOGY – On-To-Knowledge • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  10. 10. OER: Using metadata and Ontologies • Using semantics in OER Production – Gruber’s principles: • Clarity, coherence, extendibility, minimal encoding bias and minimal ontological commitment; the idea is to ensure the “knowledge sharing”. • To fulfill these criteria, ontology evaluation should be performed during development process. • Different types of evaluation: – Syntactic evaluation, to check languages specification – Semantic evaluation, focused on detecting if ontologies have inconsistencies and redundancies respectively – Lexical evaluation, it refers to the vocabulary used to represent concepts and domain relationships. • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  11. 11. OER: Using metadata and Ontologies • Using semantics in OER Production – Describing Objects and Learning Resources: Metadata Standards. • Semantic representation of LO: LOM2OWL ontology. Its structure allows to describe LOs using IEEE LOM standard. • Description of works licensed under Creative • Commons: CC published the metadata standard IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education ccREL (Creative Commons Rights Expression
  12. 12. OER-CC ontology: Development process • Main goals: – To describe OER and CC resources using a common vocabulary by users and producers, i.e., an implemented ontology offered to students and lecturers within an educational context. – To automate execution of tasks such as information retrieval using semantic web techniques. • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  13. 13. OER-CC ontology: Development process • Process and tools to build OER-CC ontology – OER ontology development. – CC ontology development. – Merging CC and OER ontologies. As a result, we unified concepts, terminology, definitions and constraints from both ontologies successfully. • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  14. 14. OER-CC ontology: Development process • Process and tools to build OER-CC ontology – Development process was based on METHONTOLOGY guidelines. • This method proposes an ontology building life cycle based on evolving prototypes. • It allows adding, changing and removing terms through each new version (prototype). • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  15. 15. OER-CC ontology: Development process • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  16. 16. OER-CC ontology: Development process • Process and tools to build OER-CC ontology – Once we had decided how to describe metadata, we selected well-referenced tools to model OER-CC ontology. – Concretely, we used CMaptools to represent and connect both knowledge domains, i.e., OER and CC respectively. • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  17. 17. OER-CC ontology: Concept Map • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  18. 18. OER-CC ontology: Development process • Process and tools to build OER-CC ontology – Cmaptools Ontology Editor (COE) was used for constructing, sharing and viewing modeled ontology based on CmapTools. – We selected COE to model OER-CC ontology using OWL language. – Protégé was used for implementing our ontology formally. Additionally, all prior results were imported to this ontology editor. – We used SWRL for deductive and reasoning capabilities and SPARQL for retrieval of educational resources metadata. • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  19. 19. OER-CC ontology: Development process • Instantiation process and tools – Population process “creates a knowledge base including instances of the ontology concepts and instances of the ontology relations” – This process can occur in 3 different ways: • Manual • Semi-automatic, • Automatic, • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  20. 20. OER-CC ontology: Development process • OER-CC Ontology Instantation – To instantiate our OER-CC ontology, we considered some resources generated in the Computer Science School (CSS) of the Technical University of Loja (Universidad Técnica Particular de Loja23, UTPL-Ecuador) – At this point, manual process was selected to populate OER-CC ontology with the CSS' educational resources, – Instantiation of CC domain was considered using different types of Creative Commons Licenses with jurisdiction at Ecuador. • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  21. 21. OER-CC ontology: Development process • Information Retrieval – We used SPARQL language for knowledge retrieval of our OER-CC ontology. – Thus, we developed some queries to retrieve information, e.g., properties of OERs and CC licenses. Initial results showed that our OER- CC ontology has been deployed successfully, i.e., using metadata from initial instantiation of educational objects. • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  22. 22. OER-CC ontology: Development process • Information Retrieval – Implemented query using SPARQL: Which are direct contributions of the UTPL at OERs production? and which are indirect contributions through their teachers/students? • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  23. 23. Conclusions – As a main contribution, we have introduced OER-CC ontology to model knowledge from OER and CC domains respectively. – Secondly, we have been able to inference knowledge using our OER-CC ontology, i.e., through classification of educational objects. – About work in progress, we continue improving OER-CC ontology. We are deploying methods to promote accessibility oriented to OER user requirements, e.g., the content of an educational resource could be ranked within the OER-CC ontology according to student or lecturer profile respectively. • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education
  24. 24. Thank you for your attention Questions • IEEE EDUCON Education Engineering 2010 – The Future of Global Learning Engineering Education

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