1. Second International Conference on Multimedia and ICTs in Education MICTE 2003 – Badajoz - Spain A KNOWLEDGE ONTOLOGY AND ITS APPLICATION INTO A LEARNING ENVIRONMENT MODEL Inés Friss de Kereki ORT Uruguay University Javier Azpiazu, Andrés Silva Polytechnic University of Madrid

2. Part I: Introduction Part II: Knowledge Ontology Part III: Application Part IV: Conclusion

3. Part I: Introduction

4. Environments MODEL Ontologies Knowledge Management Requirements Engineering, Knowledge Engineering Learning, Teaching Engineering PhD Thesis: A learning environment model based on knowledge management techniques Introduction: Context and related areas

5. Introduction Knowledge: the most versatile and important of all production factors (Toffler et al., 1998) Knowledge: the most versatile and important of all production factors (Toffler et al., 1998) Accurate definition of knowledge related terms is required Accurate definition of knowledge related terms is required knowledge ontology (Part II) knowledge ontology (Part II) application (Part III) application (Part III)

6. Part II: Knowledge Ontology

7. Ontology Defines the vocabulary of an area Defines the vocabulary of an area basic terms basic terms relationships (Neches et al., 1991) relationships (Neches et al., 1991) An explicit formal specification of a shared conceptualization (Gruber, 1993) An explicit formal specification of a shared conceptualization (Gruber, 1993)

8. Ontology of knowledge descriptive knowledge descriptive knowledge procedural knowledge procedural knowledge heuristic knowledge heuristic knowledge anecdotic knowledge anecdotic knowledge

9. Descriptive knowledge It is the knowledge with which a situation is described, a concept or an idea It is the knowledge with which a situation is described, a concept or an idea Similar terms: Similar terms: systematic (Wiig, 1995) explicit (Nonaka et al., 1995) descriptive (Paradela, 2001) declarative (Gómez et al, 1997) to know why (Boyett, 2000)

10. Procedural knowledge The knowledge required to take an action, procedure or process ahead The knowledge required to take an action, procedure or process ahead Similar terms: Similar terms: pragmatic (Wiig, 1995) explicit (Nonaka et al, 1995) operative (Gómez et al, 1997) procedural (Poggioli, 1997) to know how (Boyett, 2000)

11. Heuristic knowledge It represents the learned lessons, best practices frequent and not frequent questions and the yellow pages. It represents the learned lessons, best practices frequent and not frequent questions and the yellow pages. Related to: Related to: tacit (Nonaka et al, 1995) heuristic (Gómez et al, 1997) community (Bryan-Kinns et al, 2002) strategic (Poggioli, 1997)

12. Anecdotic knowledge It refers to anecdotes, histories and stories linked to a knowledge It refers to anecdotes, histories and stories linked to a knowledge Similar terms Similar terms Anecdotic (Paradela, 2001)

13. Examples Object Oriented Programming Object Oriented Programming Classes Classes Elementary Math Elementary Math Arithmetic Progression Arithmetic Progression

14. Hierarchy

15. Knowledge main attributes Description Description Learning strategies Learning strategies Importance Importance Medium Medium Required level Required level

16. Part III: Application

17. What is a Learning Environment? It is the space where it is possible to manage knowledge or, rather, ignorance It is the space where it is possible to manage knowledge or, rather, ignorance Adaptable Adaptable Non sequential approaches Non sequential approaches

18. The Proposed Model

19. Implementation: PLE:ASE

20. PLE:ASE

21. Experimentation Understanding teaching Understanding teaching Search for new ways to solve problems Search for new ways to solve problems Knowledge transferability Knowledge transferability

22. Experimentation ORT Uruguay University ORT Uruguay University 1st year, Programming, Systems Engineering 1st year, Programming, Systems Engineering Groups (random): Groups (random): Control (8 students) Control (8 students) Training (19 students) Training (19 students) Training and environment (21 students) Training and environment (21 students) 2 test to each student 2 test to each student Statistical Tests: Statistical Tests: Mann-Whitney, Kruskal-Wallis Mann-Whitney, Kruskal-Wallis No significant differences at the beginning No significant differences at the beginning

23. Experimentation results The use of the environment allowed the students to enlarge or improve: The use of the environment allowed the students to enlarge or improve: their problem resolution methods and their problem resolution methods and their capacities to carry out the transfer of knowledge. their capacities to carry out the transfer of knowledge.

24. Part IV: Conclusion

25. It is possible to define a knowledge ontology and to apply it, with good results, into a learning environment model It is possible to define a knowledge ontology and to apply it, with good results, into a learning environment model

26. Questions?

27. Thanks!