• Sonuç bulunamadı

5. SONUÇ VE ÖNERİLER

5.4 SONUÇ

Bu araştırma sonucunda, online eğitim sistemlerinde (e-Learning sistemlerinde) etmenleri programlayarak onlara zeki özelliği kazandırmanın ve böylece sistemdeki kullanıcıların bireysel bilgi edinme gereksinimleri sağlamak, kullanıcıların birbirleri ile bilgi ve tecrübe alışverişinde bulunabilmelerine olanak vermek ve kullanıcı ile

görsel eğitim ortamları arasındaki iletişim ve etkileşim faaliyetlerini geliştirmek amacıyla bir akıllı e-Learning sistemi geliştirmeye yönelik bir yaklaşım ortaya atılmıştır. Örnek senaryolarla desteklenerek uygulamaya yönelik adımlar atılmıştır. Tasarlanan bu sistemin belirtilen teknolojiler (Oracle, Java Servlet, CORBA teknolojileri vb..) kullanılarak uygulanmaya konması gerekmektedir. Gelecekte yapılabilecek araştırmalar da dikkate alınarak, ek çalışmalar ile daha kullanışlı ve güvenli bir sistem geliştirilmelidir. Buradaki amaçlardan biri de tasarlanan bu sistemin daha kapsamlı sistemlerin geliştirilmesine temel oluşturmasıdır.

KAYNAKLAR

1. Negroponte, N.(1970). The Architecture Machine; Towards a More Human Environment, MIT Press.

2. Kay, A.(1984) Computer Software. In: Scientific American. 251(3), 41-47. 3. Kozierok, R. and Maes, P.(1993) A Learning Interface Agent for Scheduling

Meetings,ACM SIGCHI International Workshop on Intelligent User Interfaces, ACM, Orlando,Florida. 81-88.

4. Payne, T.R., Singh, R., and Sycara, K. (2002) Calendar Agents on the Semantic Web. IEEE Intelligent Systems, 17(3), 84-86.

5. Haubl, G., and Trifts, V. (2000). Consumer decision making in online shopping environments: The effects of interactive decision aids. Marketing Science, 19(1), 4-21.

6. Maes, P. (1994). Agents that reduce work and information overload. Communications of the ACM 37(7), 30-40.

7. Milewski, A.E. and Lewis, S.H. (1997). Delegating to software agents. International Journal of Human-Computer Studies, 46(4), 485 -500.

8. Shneiderman, B., and Maes, P. (1997) Direct Manipulation vs. Interface Agents. Interactions 4 (6), 42-61.

9. Novick, DG., and Sutton, S. (1997) Mixed initiative dialogue. In Proceedings of the 1997 AAAI Symposium. AAAI Press, 114-116.

10. Horvitz, E. (1999) Principles of Mixed-Initiative User Interfaces. Proceedings of CHI '99, ACM SIGCHI Conference on Human Factors in Computing Systems, Pittsburgh, PA, ACM Press. 159-166.

11. Boicu, M., Marcu, D.m Bowman, M., and Tecuci, T (2000) A Mixed-Initiative Approachto Teaching Agents to Do Things. Proceedings of the AAAI Fall Symposium 2000, NorthFalmouth, Massachusetts, USA.

http://www.dfki.de/~bauer/fs2000/Proceedings/marcu.pdf.

12. Allen, J.F., Byron, D.K., Dzikovska, M., Ferguson, G., Galescu, L., and Stent, A.(2001)Toward Conversational Human-Computer Interaction. AI Magazine 22(4), 27-37.

13. Chin, D.(1991). Intelligent Interfaces as Agents. In Intelligent User Interfaces. J. Sullivan and S. Tyler (eds). ACM Press, New York. 177-206.

14. Lieberman, H. (1997). Autonomous Interface Agents. In Proceedings of CHI 1997, 67-74.

15. Andre, E., and Rist, T. (1996) Coping with Temporal Constraints in Multimedia Presentation Planning. In Proceedings of the Eighth National Conference on ArtificialIntelligence, Menlo Park, Calif.: American Association for Artificial Intelligence. 142-147.

16. Etzioni, O., and Weld, D. A.(1994). Softbot-Based Interface to the Internet. Communications of the ACM 37(7), 72-76.

17. Johnson, W. L., Rickel, W., and Lester, J.C. (2000). Animated Pedagogical Agents: Faceto-Face Interaction in Interactive Learning Environments. International Journal of Artificial Intelligence in Education 11(1), 47-78.

18. Rickel, J., and Johnson, W. L.(1999) Animated Agents for Procedural Training in Virtual Reality: Perception, Cognition, and Motor Control. Applied Artificial Intelligence 13(4-5), 343-382.

19. Graesser, A.C., Wiemer-Hastings, K., Wiemer-Hasting, P., Kreuz, R., and the Tutoring Resarch Group.(1999) AUTOTUTOR: A Simulation of a Human Tutor. Journal of Cognitive Systems Research 1(1), 35-51.

20. Vanlehn, K., Freedman, R., Jordan, P., Murray, C., Osan, R., Ringenberg, M., Rose, C. P., Schulze, K., Shelby, R., Treacy, D., Weinstein, A., and Wintersgill, M. (2000). Fading and Deepening: The Next Steps for ANDES and Other Model- Tracing Tutors. In Intelligent Tutoring systems: Fifth International Conference, ITS 2000, eds. G.Gauthier, C. Frasson, and K. Vanlehn,. Berlin: Springer-Verlag. 474-483.

21. Downes, S. (1998) The future of online learning. http://www.atl.ualberta.ca/downes/future/home.html

22. Kruchten, P. (1995) Architectural Blueprints—The “4+1” View Model of Software Architecture. IEEE Software 12(6), 42-50.

23. Deters, R. (2000) Developing and deploying a multi-agent system, Proceedings of Autonomous Agents'2000, Barcelona, Spain. 175-176.

24. Finin, T., Labrou, Y., and Mayfield, J.(1997) KQML as an Agent Communication Language, MIT Press. Cambridge, MA, USA. 291-316. 25. Raj, G.S. (1998) Common Object Request Broker Architecture.

http://my.execpc.com/~gopalan/corba/corba.html

26. Nardi, B. A., Miller, J. R. and Wright, D. J. (1998) Collaborative, Programmable Intelligent Agents. Communications of the ACM. 41(3), 96-104.

27. Zhu, Junren (2001) Design of Asynchronous Learning Environment.

28. Laureano, Ana Lilia 1998. Multi-Agent Architecture for Intelligent Tutorial Systems, Mexico

29. Manouselis N., and Sampson D. (2003) Agent-Based e-Learning Discovery and Recommandation

30. Manouselis N., and Sampson D. (2002). Multi-Criteria Decision Making for Broker Agents in e-Learning Environments

31. Yannis A. Dimitriadis, Juan-Ignacio Asensio-Pérez, Alejandra Martínez- Monés, and César A. Osuna-Gómez. Component-Based Software Engineering and CSCL in the Field of e-Learning.

32. Enrique Rubio-Royo, Domingo J. Gallego, and Catalina Alonso-García. E-Learning in Distance Education and in the New Cooperative Environments 33. Rosic, M., Stankov, S., Glavinic, V. (2002), Application of Semantic Web and

Personal Agents in Distance Education System

34. Michael G. Panteleyev, Dmitry V. Puzankov, Pavel V. Sazykin, Denis A. Sergeyev (2002), Intelligent Educational Environments Based on the Semantic Web Technologies

35. Ali Jafari (2002), Conseptualizing Intelligent Agents for Teaching and Learning 36. Agarwal R., Deo A. and Das S., March 2004, Intelligent Agents in E-Learning,

India

37. Webber C., Pesty S. A two level multi-agent Architecture for a distance learning environment, Brazil

38. Albert Angern , Thierry Nabeth, Claudia Rode. (November 2001). Towards personalised, socially aware and active e-Learning systems

39. Ljiljana Stojanovic, Steffen Staab, Rudi Studer. E-Learning based on the Semantic Web, Germany

40. Thanos Vasilakos; Vladan Devedzic; Kinshuk; Witold Pedrycz. (2004) Computational intelligence in web-based education

41. Brusilovsky P., Adaptive and Intelligent Technologies for Web-based Education. 42. Dan Gâlea, Florin Leon and Mihai Horia Zaharia. E-learning Distributed

Framework using Intelligent Agents

43. Mohammed JEMNI, Issam Ben ALI. Automatic answering tool for e-Learning environment, TUNISIA

44. Paul Dan Cristea and Rodica Tuduce. Test Authoring for Intelligent e- Learning Environments, ROMANIA

45. Mihal Badjonski, Mirjana Ivanovic, Zoran Budimac. (2001) Intelligent Tutoring System as Multi-Agent System, YUGOSLAVIA

46. Sabin-Corneliu Buraga. (2003). Developing Agent-Oriented E-Learning Systems, ROMANIA

47. Kim Adolphe (2005), Intelligent e-Learnning with XML, CANADA 48. Francisco Ramos, Nuno Ribeiro and Hugo Gamboa. Intelligent Learning

Environment Based On Elearning Standards

49. Selby Markham, Jason Ceddia and Judi Sheard. Applying Agent Technology to Evaluation Tasks in E-Learning Environments, AUSTRALIA

50. D J Mullier, D J Hobbs, D J Moore. A Web Based Intelligent Tutoring System 51. Diane J. Litman, Scoot Silliman (2002). An Intelligent Tutoring Spoken

Dialogue System, USA

52. Dr Tanja Mitrovic. Current Trends in Intellignet Educational Systems, New Zeland

53. Joseph Beck, Mia Stern, and Erik Haugsjaa ,Applications of AI in Education 54. Lucia Maria Martins Giraffa, Rosa Maria Viccari. The use of Agents

techniques on Intelligent Tutoring Systems, ENGLAND

55. Paul Dan Cristea and Rodica Tuduce. Test Authoring For Intelligent E- Learning Environments, ROMANIA

56. Ruddy Lelouche and Tho Toan Ly. Using a Framework in the Development of an Intelligent Tutoring System, CANADA

57. Francisco Ramos, Nuno Ribeiro and Hugo Gamboa (2002), Intelligent Learning Environment Based On Elearning Standards

58. J. Beck, M. Stern, and E. Haugsjaa, “Applications of AI in education,” ACM Crossroads, pp. 11-15, 1996.

59. P. Brusilovsky, “Adaptive and intelligent Technologies forWeb-based

education,” Special Issue on Intelligent Systems and Teleteaching, 4: pp. 19-25, 1999.

60. C. Conati, A. Gertner, and K. VanLehn, “UsingBayesian networks to manage uncertainty in student modeling,” User Modeling and User-Adapted Interaction, 12(4): pp. 371-417, 2002.

61. A. Jameson, “Numerical uncertainty management inuser and student modeling: An overview of systemsand issues,” User Modeling and user-Adapted

Interaction, pp. 193-251, 1995.

62. W.L. Johnson, “Pedagogical agents for Web-basedlearning,” First Asia-Pacific Conference on Web Intelligence, pp. 43, 2001.

63. J. Martin and K. Vanlehn, “Student assessment usingBayesian nets,” International Journal of Human- Computer Studies, 42: pp. 575-591, 1995. 64. V.J. Shute and J. Psotka, “Intelligent tutoring systems:past, present, and future,”

Handbook of Research on Educational Communications and Technology, Macmillan, New York, pp. 570-600, 1996.

65. M. Villano, “Probabilistic student models: Bayesianbelief networks and knowledge space theory,” Proceedingsof 2nd International Conference on Intelligence Tutoring System, pp. 491-498, 1992.

Benzer Belgeler