1. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 1 Personalized Distance Learning Based on Multiagent Ontological System Vagan Terziyanvagan@it.jyu.fivagan@it.jyu.fi Igor Keleberda I.Keleberda@ieee.orgI.Keleberda@ieee.org Natalya Lesnalesna@kture.kharkov.ualesna@kture.kharkov.ua Sergey Makovetskiy sdmakovetskiy@ukr.netsdmakovetskiy@ukr.net

2. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 2 Authors Vagan Terziyan Industrial Ontologies Group Department of Mathematical Information Technologies University of Jyvaskyla (Finland) http://www.cs.jyu.fi/ai/vagan This presentation: http://www.cs.jyu.fi/ai/ICALT-2004.ppthttp://www.cs.jyu.fi/ai/ICALT-2004.ppt Igor Keleberda Department of Software Engineering Kharkov National University of Radioelectronics (Ukraine) http://poaslab.kture.kharkov.ua Natalya Lesna Educational and Methodical Office Kharkov National University of Radioelectronics (Ukraine) Sergey Makovetskiy Department of Software Engineering Kharkov National University of Radioelectronics (Ukraine) http://poaslab.kture.kharkov.ua

3. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 3 Motivation (problem) The majority of modern distant learning systems are characterized by usage of restricted set of educational materials. On the other hand, they provide insufficient level of personalization of the learning process.

4. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4 Motivation (solution) Semantic Web One possible way for overcoming mentioned difficulties is the usage of multiagent software technologies in the framework of the Semantic Web activities of the W3С consortium. These technologies are capable to automatically extract necessary educational materials (disposed over the whole Web space) to provide high-quality personalization of the education.

5. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 5 What is Semantic Web ? “The Semantic Web is a vision: the idea of having data on the Web defined and linked in a way that it can be used by machines not just for display purposes, but for automation, integration and reuse of data across various applications”

6. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 6 Semantic Web: New “Users” applications agents

7. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 7 Semantic Web: What to Annotate ? Educational resources Web resources / services / DBs / etc. Web users (profiles, preferences) Web access devices Industrial machines and devices Web agents / applications External world resources Shared ontology

8. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 8 IEEE Learning Technology Standards 1484.12.1: IEEE Standard for Learning Object Metadata (LOM) 1484.12.3: 1484.12.3: Standard for XML binding for Learning Object Metadata data model 1484.12.4: 1484.12.4: Standard for Resource Description Framework (RDF) binding for Learning Object Metadata data model P1484.2.1/D8 Draft Standard for Learning Technology — Public and Private Information (PAPI) for Learners (PAPI Learner) SW

9. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 9 Semantic Personalization Learner Agent-coordinator (semantic match engine) Shared ontology Learning resource Semantic annotation Profile

10. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 10 Global Understanding eNvironment (GUN) GUN is an initiative of the Industrial Ontologies Group (IOG), proactive, goal-driven, self-maintained lead with the goal of extending the current Semantic Web to facilitate proactive, goal-driven, self-maintained behavior of all kinds of resources that can be adapted to the Web. http://www.cs.jyu.fi/ai/OntoGroup/ GUN Resource Metadata Shared ontology Agent

11. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 11 Agent’s Proactive Behavior in GUN (1) GUN Able to make diagnostics of the learner and as result to know recent profile of the learner (learner’s state and condition); Knows target profile (desirable state and condition according to e.g. curriculum); Behaves to “maintain” the learner’s state (i.e. to minimize the gap between recent and target profiles); Able to discover and utilize other resources and services to reach own goals.

12. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 12 Agent’s Proactive Behavior in GUN (2) GUN Able to check access rights to appropriate information; Behaves to maximize the benefit for the commercial use of information from the resource; Able to navigate external reader within the resource.

13. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 13 From Web-Based Learning … WWW

14. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 14 … to GUN-Based Learning. WWW Semantic Web

15. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 15 Mechanism of personalization LOM LOM LOM LOM LOM PAPILearner PAPILearner OLOLOLOL OLOLOLOL O L,O R OROROROR OROROROR OROROROR OROROROR OROROROR Software agent MetadataOntology Learning Resource Learner Agent Communication Language

16. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 16 MOSPDL architecture

17. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 17 MOSPDL algorithm The MOSPDL algorithm contains the following stages: user registers in the MOSPDL agent-coordinator sends query for educational data profile learning resources agent creates the query to educational resources in the Internet educational Internet-resources give metadata for analysis of necessity of their usage in the learning process cont…

18. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 18 MOSPDL algorithm agent-coordinator provides selection of educational materials; then it sends query for needed educational materials learning resources agent builds the set of educational materials, which is recommended for the student the agent-coordinator sends the resulting set to the personal agent; the personal agent produces multimedia learning output for the student

19. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 19 The personal agent The main task of the personal agent is creation of the user profile. Algorithmic structure of the software agent contains the following stages: the stage of registration the stage of learning

20. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 20 The learning resources agent The learning resources agent plays the role of a searching machine, which is capable to realize search on several resources simultaneously. Algorithmic structure of the software agent contains the following stages: the stage of forming of the profiles for educational materials the stage of creation of the needed educational materials set

21. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 21 The agent-coordinator The agent-coordinator fulfils functions of the intermediary and realizes control over the learning process in the MOSPDL. Algorithmic structure of the agent-coordinator contains the following stages: the stage of searching for educational materials the stage of individual selection of an educational material

22. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 22 Distance learning portal

23. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 23 Learning resource

24. 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 4-th IEEE International Conference on Advanced Learning Technologies, Joensuu, Finland, August 30 – September 1, 2004 24 Conclusions The designed software system belongs to a new generation of distributed systems of distant Web-based learning, namely to multiagent ontological systems based on Semantic Web. The elaborated architecture and algorithm of MOSPDL is intended to solve the task of automation of the distant learning process, which is oriented on utilizing ontological models of student's profiles and learning resources profiles.