A proposal for student modeling based on ontologies and diagnosis rules

Expert Systems with Applications

Volumn 38, Issue 7, 2011, Pages 8066-8078

  Clemente, Julia ^a   Ramírez, Jaime ^b   De Antonio, Angélica ^b  

^a UNIVERSITY OF ALCALÁ   (Spain)

^b UNIVERSIDAD POLITÉCNICA DE MADRID   (Spain)

Author keywords

Intelligent Tutoring System; Pedagogic diagnosis; Student model; Virtual environments for training

Indexed keywords

COGNITIVE DIAGNOSIS; HIGH FLEXIBILITY; INTELLIGENT TUTORING SYSTEM; KNOWLEDGE STATE; LEARNING OBJECTIVES; NEW APPROACHES; ONTOLOGICAL ENGINEERING; PEDAGOGIC DIAGNOSIS; REASONING PROCESS; STUDENT MODEL; STUDENT MODELING; STUDENT MODELS; VIRTUAL ENVIRONMENTS;

COMPUTER AIDED INSTRUCTION; E-LEARNING; EDUCATION COMPUTING; KNOWLEDGE REPRESENTATION; ONTOLOGY; VIRTUAL REALITY;

STUDENTS;

EID: 79952445315     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2010.12.146     Document Type: Article

References (41)

1. Alem, L. K. R. (1996). Intelligent simulation environment an application to air traffic control training. In Proceedings of the first international conference on advancing simulation technology and training, SimTecT'96 (pp. 323-328).
2. B.S. Bloom, and D.R. Krathwohl Taxonomy of educational objectives: The classification of educational goals, by a committee of college and university examiners. Handbook I: Cognitive domain 1956 Longman
3. G. Brajnik, and C. Tasso A shell for developing non-monotonic user modeling systems International Journal of Human-Computer Studies 40 1 1994 31 62
4. Bredeweg, B., Breuker, J. (1993). Device models for model-based diagnosis of student behaviour. In Ohlsson S. (Ed.), Proceedings of the World conference on AI and education. Charlottesville, VA: AACE.
5. Buche, C., Querrec, R., Loor, P. D., Chevaillier, P. (2003). Mascaret: Pedagogical multi-agents system for virtual environment for training, Cyberworlds. In International conference on 0. 423.
6. Bull, S. (1997). Collaborative student modelling in foreign language learning. Ph.D. thesis, University of Edinburgh.
7. R.B. Burton Diagnosing bugs in a simple procedural skill 1982 Academic Press Ch. Intelligent tutoring systems, pp. 157-183.
8. W. Chen, and R. Mizoguchi Leaner model ontology and leaner model agent, cognitive support for learning - imagining the unknown Cognitive Support for Learning - Imagining the Unknown 2004 2004 189 200
9. W.J. Clancey Qualitative student models 1986 381 450
10. de Antonio, A., Ramírez, J., Clemente, J. (2007). A proposal for student modelling based on ontologies. In EJC (pp. 298-305).
11. J. de Kleer An assumption-based tms Artificial Intelligence 28 2 1986 127 162
12. J. de Kleer, and B. Williams Diagnosis with Behavioral Modes 1992 124 130
13. de Koning, K., Bredeweg, B. (1998). Using gde in educational systems. In Proceedings of the European conference on artificial intelligence (ECAI) (pp. 279-283).
14. H.W. Dongming Xu, and M. Wang A conceptual model of personalized virtual learning environments Expert Systems with Applications 29 3 2005 525 534 (Pubitemid 41230777)
15. A.J. Harrow A taxonomy of the psychomotor doma A guide for developing behavioral objectives 1972 Longman
16. P. Holt, S. Dubs, M. Jones, and J. Greer Student modelling: The key to individualized knowledge-based instruction, NATO ASI, series F Lecture notes in computer science 1994 Springer Verlag Ch. The state of student modelling, pp. 3-35.
17. M. Hospers, E. Kroezen, A. Nijholt, R. Den Akker, and D. Heylen An agent-based intelligent tutoring system for nurse education In applications of intelligent agents in health 2003 Birkhauser Publishing Ltd 143 159
18. X. Huang, G. McCalla, J. Greer, and E. Neufeld Revising deductive knowledge and stereotypical knowledge in a student model User Modeling and User-Adapted Interaction 1 1 1991 87 115
19. Ikeda, M., Kono, Y., Misoguchi, R. (1993). Nonmonotonic model inference. In Proceedings of the 13th international joint conference on artificial intelligence, IJCAI'93.
20. F. Mantovani VR learning: Potential and challenges for the use of 3D environments in education and training R. Giuseppe, G. Carlo, Towards cyberpsychology: Mind, cognitions and society in the internet age 2001 IOS Press Amsterdam 207 226
21. Kay, J. A. (1999). Scrutable User Modelling Shell for User-Adapted Interaction. Ph.D. thesis, University of Sydney.
22. A. Kornecki, T. Hilburn, T. Diefenbach, and M. Towhidnejad Intelligent tutoring issues for air traffic control training IEEE Transactions on Control Systems Technology 1 1993 2 9
23. D.R. Krathwohl, B.S. Bloom, and B. Masia Taxonomy of educational objectives: The classification of educational goals. Handbook II: The affective domain 1964 Longman
24. J.C. Lester, J.L. Voerman, S.G. Towns, and C.B. Callaway Cosmo: A life-like animated pedagogical agent with deictic believability 1997
25. W.J. Lewis, J. Rickel, and J. Lester Animated pedagogical agents: Face-to-face interaction in interactive learning environments International Journal of Artificial Intelligence in Education 11 2000 47 78
26. J. Los Arcos, W. Muller, O. Fuente, L. Ore, E. Arroyo, and I. Leaznibarrutia Intelligent tutoring systems Lecture notes in computer science 2000 Springer Berlin/Heid elberg (Ch. LAHYSTOTRAIN: Integration of virtual environments and ITS for surgery training)
27. G.I. McCalla, and J.E. Greer Granularity-based reasoning and belief revision in student models 1994
28. Noguez, J., Huesca, G. (2008). LaSiTo: A Lathe simulated virtual laboratory. In Proceedings of the 38th IEEE international conference on frontiers in education, FIE'08.
29. J. Noguez, and L.E. Sucar A probabilistic relational student model for virtual laboratories Mexican International Conference on Computer Science 0 2005 2 9 (Pubitemid 46415577)
30. V.A. Petrushin Intelligent tutoring systems: Architecture and methods of implementation. A survey Journal of Computer and System Sciences International 33 1995 117 139
31. R. Querrec, C. Buche, É. Maffre, and P. Chevaillier Multiagents systems for virtual environment for training. application to fire-fighting International Journal of Computers and Applications 1 2004 25 34
32. J. Rickel, and W.J. Lewis Animated agents for procedural training in virtual reality: Perception, cognition, and motor control Applied Artificial Intelligence 13 1998 343 382
33. J.A. Self Model-based cognitive diagnosis User Modeling and User-Adapted Interaction 3 2 1993 89 106
34. T.D. Soldato Detecting and reacting to the learner's motivational state ITS '92: Proceedings of the second international conference on intelligent tutoring systems 1992 Springer-Verlag London, UK 567 574
35. Suárez-Figueroa, M. C., de Cea, G. A., Buil, C., Dellschaft, K., Fernández-López, M., García, A., Gómez-Pérez, A., Herrero, G., Montiel-Ponsoda, E., Sabou, M., Villazón-Terrazas, B., Yufei, Z. (2008). Neon deliverable d5.4.1. neon methodology for building contextualized ontology networks. Technical Report. NeOn.
36. Tsybenko, Y. (1995). Device models in student modeling. In Greer J., (Ed.), Proceedines of international conference on artificial intellicence in education, AIED'95. AACE.
37. E. Wenger Artificial intelligence and tutoring systems: Computational and cognitive approaches to the communication of knowledge 1987 Morgan Kaufman
38. B. White, J. Frederiksen, K. Forbus, P. Whalley, J. Everett, and L. Ureel Causal model progressions as a foundation for intelligent learning environments 1990
39. B.J. Wielinga, A.T. Schreiber, and J.A. Breuker Kads: A modelling approach to knowledge engineering Knowledge Acquisition 4 1 1992 5 53
40. C. Xuesong, and T. Spedding A Web-based intelligent virtual learning environment for industrial continuous improvement Proceedings of IEEE international conference on industrial informatics 2006 IEEE Computer Society Press 1102 1107
41. D. Xu, H. Wang, and K. Su Intelligent student profiling with fuzzy models HICSS '02: Proceedings of the 35th annual Hawaii international conference on system sciences (HICSS'02) Vol. 3 2002 IEEE Computer Society Washington, DC, USA pp. 81.2