An intelligent recommender system for trainers and trainees in a collaborative learning environment for UML

Intelligent Decision Technologies

Volumn 6, Issue 2, 2012, Pages 79-95

  Tourtoglou, Kalliopi ^a   Virvou, Maria ^a  

^a UNIVERSITY OF PIRAEUS   (Greece)

Author keywords

adaptive user interaction; collaboration; collaborative learning; CSCL; group formation tool; intelligent learning system; perturbation model; recommendation; Recommender system; stereotypes; student modelling; UML

Indexed keywords

COLLABORATION; COLLABORATIVE LEARNING; CSCL; GROUP FORMATIONS; INTELLIGENT LEARNING SYSTEMS; PERTURBATION MODEL; RECOMMENDATION; STEREOTYPES; STUDENT MODELLING; UML; USER INTERACTION;

INTERNATIONAL TRADE; KNOWLEDGE BASED SYSTEMS;

RECOMMENDER SYSTEMS;

EID: 84865449491     PISSN: 18724981     EISSN: 18758843     Source Type: Journal    
DOI: 10.3233/IDT-2012-0125     Document Type: Review

References (83)

1. A.W. Neumann, Recommender Systems for Information Providers: Designing Customer Centric Paths to Information, Heidelberg: Physica-Verlag, 2009.
2. R. Burke, Hybrid Recommender Systems: Survey and Experiments, User Modeling and User-Adapted Interaction 12(4) (2002), 331-370.
3. E. Rojsattarat and N. Soonthornphisaj, Hybrid recommendation: Combining content-based prediction and collaborative filtering, In Intelligent Data Engineering and Automated Learning (2003), 337-344.
4. J. Reye, Student Modelling Based on Belief Networks, International Journal of Artificial Intelligence in Education 14(1) (2004), 1-33.
5. C. Conati, A. Gertner and K. Vanlehn, Using Bayesian Networks toManageUncertainty in Student Modeling, User Modeling and User-Adapted Interaction 12(4) (2002), 371-417.
6. H. Nguyen, Capturing user intent for information retrieval, in: Proceedings of the 19th National Conference on Artifical intelligence, A.G. Cohn, ed., Aaai Conference On Artificial Intelligence, AAAI Press, 2004, pp. 997-998.
7. Z. Jeremic, J. Jovanovic and D. Gasevic, Evaluating an Intelligent Tutoring System for Design Patterns: the DEPTHS Experience, Educational Technology and Society 12(2) (2009), 111-130.
8. V. Tsiriga and M. Virvou, Dynamically Initializing the Student Model in a Web-based Language Tutor, in: Proceedings of the 2002 First International IEEE Symposium "Intelligent Systems", (Vol. I), IEEE Computer Society, 2002, pp. 138- 143.
9. F. Wei, S.H. Moritz, S.M. Parvez and G.D. Blank, A student model for object-oriented design and programming, J Comput Small Coll 20(5) (2005), 260-273.
10. K. Kabassi, M. Virvou and G. Tsihrintzis, Requirements Capture for a Personalised Medical Tutor, The International Special Topic Conference on Information Technology in Biomedicine, 2006.
11. I. Hatzilygeroudis and J. Prentzas, Using a Hybrid Rule-Based Approach in Developing an Intelligent Tutoring System with Knowledge Acquisition and Update Capabilities, Journal of Expert Systems with Applications 26(4) (2004), 477-492.
12. H.D. Surjono and J.R. Maltby, Adaptive Educational Hypermedia Based on Multiple Student Characteristics, Advances in Web-Based Learning - ICWL 2003, 2003, 442-449.
13. M. Virvou and M. Moundridou, Student and Instructor Models: Two Kinds of User Model and their Interaction in an ITS Authoring Tool, in: User Modeling 2001: Proceedings of the 8th International Conference UM2001, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), Vol. 2109, M. Bauer, P. Gmytrasiewicz and J. Vassileva, eds., Springer, Berlin, 2001, 158-167.
14. P. Brusilovsky and D.W. Cooper, Domain, task, and user models for an adaptive hypermedia performance support system, in: Proceedings of the 7th International Conference on Intelligent User Interfaces, IUI '02. ACM, New York, NY, 2002, pp. 23-30.
15. P. Brusilovsky, E.W. Schwarz and G. Weber, ELM-ART: An Intelligent Tutoring System onWorldWideWeb, in: Proceedings of the Third International Conference on Intelligent Tutoring Systems, C. Frasson, G. Gauthier and A. Lesgold, eds, Lecture Notes In Computer Science, 1086. Springer-Verlag, London, 1996, pp. 261-269.
16. M. Stern, B.P.Woolf and J.F.Kurose, Intelligence on theWeb? In Artificial Intelligence in Education, 1997, 490-497.
17. M. El-Khouly and S. Abou El-Seoud, On Line Student Model, International Journal of Computing and Information Sciences 4(1) (2006), 40-45.
18. M. Virvou and V. Tsiriga, Student Modelling in a Web-based Algebra Tutor. In Proceedings of TELEMATICA 2001 International Conference on Telematics andWeb-Based Education, 2001, 43-44.
19. R.A. Faraco, M.C. Rosatelli, A. Fernando and O. Gauthier, An Approach of Student Modelling in a Learning Companion System, Advances in Artificial Intelligence - IBERAMIA 2004, 2004, 891-900.
20. S. Labidi and N. Sergio, Student modeling and semi-Atutomatic domain ontology construction for SHIECC, Frontiers in Education, Annual, 30th Annual Frontiers in Education, Vol 1 (FIE'2000), 2000, pp. F1B/14-F1B/18.
21. S. Kirkpatrick, C.D. Gelatt and M.P. Vecchi, Optimization by Simulated Annealing, Science 220 (1983), 671-680.
22. A.L. Soller, Supporting Social Interaction in an Intelligent Collaborative Learning System, International Journal of Artificial Intelligence in Education 12(1) (2001), 40-62.
23. M.A. Constantino-Gonz'alez and D.D. Suthers, A Coached Collaborative Learning Environment for Entity-Relationship Modeling, Intelligent Tutoring Systems. Proceedings of the 5th International Conference (ITS 2000), G. Gauthier, C. Frasson and K. VanLehn, eds, Berlin: Springer-Verlag, 2000, pp. 325- 333.
24. M.C. Rosatelli and J. Self, A Collaborative Case Study System For Distance Learning, International Journal of Artificial Intelligence in Education 14 (2004), IOS Press, 1-29.
25. N. Baghaei and A. Mitrovic, Collect-UML: Supporting Individual and Collaborative Learning of UML Class Diagrams in a Constrain-Based Intelligent Tutoring System, Lecture Notes in Computer Science, 3684, Springer Berlin/Heidelberg, 2005, 458-464.
26. B. Barros and M.F. Verdejo, Analysing student interaction processes in order to improve collaboration. The DEGREE approach, International Journal of Artificial Intelligence in Education 11 (2000).
27. A. Vizcáino, J. Contreras, J. Favela and M. Prieto, An Adaptive, Collaborative Environment to Develop Good Habits in Programming. In ITS 2000, LNCS 1839, Springer 2000, 262- 271.
28. Chen, Weiqin, Pedersen, Roger Heggernes, Pettersen, Øystein. CoLeMo: Acollaborative learning environment forUML modelling, Interactive Learning Environments 14(3) (2006), 233-249.
29. M.A. Mart'inez Carreras, A.F. G'omez-Skarmeta, E. Mart'inez Graci'a and M. Mora G'onzalez, COLAB: A platform design for collaborative learning in virtual laboratories, WORKSHOP held on the 18th IFIP World Computer Congress, 2004.
30. Y. Tamura and S. Furukawa, CSCL Environment for "Six Thinking Hats" Discussion, Knowledge-Based Intelligent Information and Engineering Systems (2008), 583-589.
31. N. Khandaker, L.-K. Soh and H. Jiang, Student Learning and Team Formation in a Structured CSCL Environment, Proc. ICCE'2006, Beijing, China, 2006, 185-192.
32. S. Jondahl and A. Mørch, Simulating Pedagogical Agents in a Virtual Learning Environment, in: Proceedings Computer Support for Collaborative Learning (CSCL 2002), G. Stahl, ed., Boulder, CO, USA: Lawrence Erlbaum, 2002, pp. 531- 532.
33. S. Lukosch, M. Hellweg and M. Rasel, CSCL, Anywhere and Anytime, Lecture Notes in Computer Science. Groupware: Design, Implementation, and Use, 12th International Workshop, CRIWG 2006, LNCS 4154, 2006, 326-340.
34. J. Rick andM. Guzdial, Situating CoWeb: a scholarship of application, International Journal of Computer-Supported Collaborative Learning 1 (2006), 89-115.
35. E.J. Elliott and A. Bruckman, AquaMOOSE 3D: math learning in a 3D multi-user virtual world, in: CHI '01 Extended Abstracts on Human Factors in Computing Systems (Seattle, Washington, March 31-April 05, 2001). CHI '01. ACM, New York, NY, 2001, pp. 259-260.
36. B. Prasad, HYREC: A Hybrid Recommendation System for E-Commerce. Case-Based Reasoning Research and Development, Springer, 2005, 408-420.
37. V. S'anchez-Anguix, S. Esparcia, E. Argente, A. Garc'ia- Fornes and V. Juli'an, Collaborative Information Extraction for Adaptive Recommendations in aMultiagent Tourism Recommender System, Advances in Practical Applications of Agents and Multiagent Systems, Y. Demazeau, F. Dignum, J.M. Corchado and J. Bajo, eds, 8th International Conference on Practical Applications of Agents and ultiagent Systems, PAAMS 2010, Salamanca, Spain, 26-28 April 2010, Advances in Soft Computing 70 (Springer 2010), 35-40.
38. F. Ricci and H. Werthner, Case-Based Querying for Travel Planning Recommendation, Information Technology and Tourism 4(3-4) (2002), 215-226.
39. I.-E. Liao, W.-C. Hsu, M.-S. Cheng and L.-P. Chen, A library recommender system based on a personal ontology model and collaborative filtering technique for English collections, The Electronic Library 28(3) Emerald Group Publishing Limited, (2010), 386-400(15).
40. K.-Y. Jung, D.-H. Park and J.-H. Lee, PersonalizedMovieRecommender System through Hybrid 2-Way Filtering with Extracted Information, Lecture Notes in Computer Science, Flexible Query Answering Systems, Springer Berlin/Heidelberg, 2004, 473-486.
41. N.T. Nguyen, M. Rakowski, M. Rusin, J. Sobecki and L.C. Jain, Hybrid filtering methods applied in web-based movie recommendation system, in: Proceedings of the 11th international Conference, KES 2007 and XVII Italian Workshop on Neural Networks Conference on Knowledge-Based intelligent information and Engineering Systems: Part I (Vietri sul Mare, Italy, September 12-14, 2007), B. Apolloni, R.J. Howlett and L. Jain, eds, Lecture Notes In Computer Science. Springer-Verlag, Berlin, Heidelberg, 2007, pp. 206-213.
42. Y. Blanco-Fernandez, J.J. Pazos-Arias, A. Gil-Solla, M. Ramos-Cabrer, B. Barragans-Martinez and M. Lopez-Nores, A Multi-Agent Open Architecture for a TV Recommender System: A Case Study Using a Bayesian Strategy, in: Proceedings of the IEEE Sixth international Symposium on Multimedia Software Engineering (December 13-15, 2004). ISMSE. IEEE Computer Society, Washington, DC, 2004, pp. 178-185.
43. S. Velusamy, L. Gopal, S. Bhatnagar and S. Varadarajan, An efficient ad recommendation system for TVprograms, Jouranl of Multimedia Systems 14(2) (2008), 73-87.
44. Y. Blanco, J.J. Pazos, A. Gil, M. Ramos, A. Fern'andez, R.P. D'iaz, M. L'opez and B. Barrag'ans, AVATAR: an approach based on semantic reasoning to recommend personalized TV programs, in: Special Interest Tracks and Posters of the 14th International Conference on World Wide Web, WWW '05. ACM, New York, NY, (Chiba, Japan, May 10-14, 2005).
45. T. Nakahara and H. Morita, Recommender System for Music CDs Using a Graph Partitioning Method. In Proceedings of the 13th international Conference on Knowledge-Based and intelligent information and Engineering Systems: Part II (Santiago, Chile, September 28-30, 2009), Lecture Notes In Artificial Intelligence, J.D. Vel'asquez, S.A. R'ios, R.J. Howlett and L.C. Jain, eds, 5712. Springer-Verlag, Berlin, Heidelberg, 2009, pp. 259-269.
46. P.S. Lampropoulou, A.S. Lampropoulos and G.A. Tsihrintzis, A Mobile Music Recommender System based on a Two-level Genre-Rating SVM Classifier enhanced by Collaborative Filtering. New Directions in Intelligent Interactive Multimedia Systems and Services - 2, Studies in Computational Intelligence, 226/2009, Springer Berlin/Heidelberg, 2009, 361-368.
47. J. Kim, K. Jung, J. Ryu, U. Kang and J. Lee, Design of Ubiquitous Music Recommendation System Using MHMM, in: Proceedings of the 2008 Fourth International Conference on Networked Computing and Advanced Information Management - Volume 02, NCM. IEEE Computer Society, Washington, DC, (September 02-04, 2008).
48. M. Park, H. Park and S. Cho, Restaurant Recommendation for Group of People in Mobile Environments Using Probabilistic Multi-criteria Decision Making, in: Proceedings of the 8th Asia-Pacific Conference on Computer-Human interaction (Seoul, Korea, July 06-09, 2008), S. Lee, H. Choo, S. Ha and I.C. Shin, eds, Lecture Notes In Computer Science, vol. 5068. Springer-Verlag, Berlin, Heidelberg, 2008, 114-122.
49. D. Billsus and M.J. Pazzani, User Modeling for Adaptive News Access, User Modeling and User-Adapted Interaction 10(2-3) (Feb. 2000), 147-180.
50. D.-Y.Wanga, S.S.J. Linb and C.-T. Suna, A two phases grouping framework for achieving educational equality in heterogeneous group learning, Proceedings of the 1st WSEAS/IASME Int. Conf. on EDUCATIONAL TECHNOLOGIES, 2005, 169- 174.
51. O.R. Za'iane, Building a Recommender Agent for e-Learning Systems, in: Proceedings of the international Conference on Computers in Education, (December 03-06, 2002), ICCE. IEEE Computer Society, Washington, DC, 2002, 55.
52. N. Furugori, H. Sato, H. Ogata, Y. Ochi and Y. Yano, COALE: collaborative and adaptive learning environment, in: Proceedings of the Conference on Computer Support For Collaborative Learning: Foundations For A CSCL Community, (Boulder, Colorado, January 07-11, 2002), G. Stahl, ed., Computer Support for Collaborative Learning. International Society of the Learning Sciences, 2002, pp. 493-494.
53. X. Wan, F. Anma, T. Ninomiya amd T. Okamoto. CollaboeNOTE: A Hybrid Recommender System for Group Learning Support, IJCSNS International Journal of Computer Science and Network Security 8(9) (2008), 166-171.
54. M.K. Khribi, M. Jemni and O. Nasraoui, Automatic Recommendations for E-Learning Personalization Based onWeb Usage Mining Techniques and Information Retrieval, in: Proceedings of the 2008 Eighth IEEE international Conference on Advanced Learning Technologies, ICALT. IEEE Computer Society, Washington, DC, July 01-05, 2008, pp. 241-245.
55. F. Linton, D. Joy, H.P. Schaefer and A. Charron, OWL: A recommender system for organization-wide learning, Educational Technology and Society (2000), 62-76.
56. T. Tang andG.McCalla, Smart Recommendation for anEvolving E-Learning System: Architecture and Experiment, International Journal on E-Learning 4(1) (2005), 105-129.
57. M. Hsu,Apersonalized English learning recommender system for ESL students, Expert Syst Appl 34(1) (2008), 683-688.
58. C. Chen, H. Lee and Y. Chen, Personalized e-learning system using Item Response Theory, Comput Educ 44(3) (2005), 237- 255.
59. H.G. Hummel, B.V. Berg, A.J. Berlanga, H. Drachsler, J. Janssen, R. Nadolski and R. Koper, Combining social-based and information-based approaches for personalised recommendation on sequencing learning activities, Int J Learn Technol 3(2) (2007), 152-168.
60. C.E. Christodoulopoulos and K.A. Papanikolaou, A Group Formation Tool in an E-Learning Context. In Proceedings of the 19th IEEE international Conference on Tools with Artificial intelligence, 02, 2007.
61. S. Graf and R. Bekele, Forming Heterogeneous Groups for Intelligent Collaborative Learning Systems with Ant Colony Optimization. Vortrag: International Conference on Intelligent Tutoring Systems, Jhongli, Taiwan, in: Proceedings of the International Conference on Intelligent Tutoring Systems, Springer, LNCS 4053, 2006, 217-226.
62. R. Cavanaugh, M. Ellis, R. Layton and M. Ardis, Automating the Process of Assigning Students to Cooperative-Learning Teams. 2004 American Society for Engineering Education Annual Conference and Exposition, June 20-23, Salt Lake City, Utah, 2004.
63. E.S.J. de Faria, J.M. Adan-Coello and K. Yamanaka, Forming Groups for collaborative Learning in Introductory Computer Programming Courses Based on Students' Programming Styles: An Empirical Study, Proceedings of the ASEE/IEEE Frontiers in Education Conference, San Diego, CA, USA, 2006, 6-11.
64. D.Y. Wang, S.S.J. Lin and C.T. Sun, DIANA: A computersupported heterogeneous grouping system for teachers to conduct successful small learning groups, Computers in Human Behaviors 23(4) (2007), 1997-2010.
65. A. Gogoulou, G. Gouli, E. Boas, E. Liakou and M. Grigoriadou, Forming homogeneous, heterogeneous and mixed groups of learners, in: Proceedings of the Personalisation in E-Learning Environments at Individual and Group LevelWorkshop, in 11th International Conference on User Modeling, 2007, 33-40.
66. A. Ounnas, H.C. Davis and D.E. Millard, A Framework for Semantic Group Formation in Education, Educational Technology and Society 12(4) (2009), 43-55.
67. E. Martin and P. Paredes, Using Learning Styles for Dynamic Group Formation in Adaptive Collaborative Hypermedia Systems, International Workshop on Adaptive Hypermedia and Collaborative Web-Based Systems, International Conference on Web Engineering, Munich, 2004.
68. M. Ikeda, S. Go and R. Mizogucho, Oppurtunistic Group Formation, Artificial Intelligence in Education, B. du Boulay and R. Mizoguchi, eds, IOS Press, 1997, pp. 167-174.
69. S.R. Wilson and W. Cui, Applications of simulated annealing to peptides, Biopolymers 29(1) (1990), 225-235.
70. J. Czaplicki, G. Corn'elissen and F. Halberg, GOSA, a simulated annealing-based program for global optimization of nonlinear problems, also reveals transyears, J Appl Biomed 4 (2006), 87-94.
71. B. Monien, F. Ramme and H. Salmen, A Parallel Simulated Annealing Algorithm for Generating 3D Layouts of Undirected Graphs, Proc. Of the Int. Symp. On Graph Drawing (GD'95), Springer Verlag, LNCS 1027, 1995, 396-408.
72. R. Davidson and D. Harel, Drawing graphs nicely using simulated annealing, ACM Transactions on Graphics (TOG) 15(4) (1996), 301-331.
73. J. Cagan, R. Clark, P. Dastidar, S. Szykman and P. Weisser, Hvac Cad Layout Tools: A Case Study of University/Industry Collaboration, Proceedings of the Optimization in Industry Conference, 1997.
74. J.C.J.H. Aerts, M. van Herwijnen and T. Stewart, Using Simulated Annealing and Spatial Goal Programming for Solving aMulti Site Land Use Allocation Problem, Evolutionary Multi Criterion Optimization, Springer-Verlag Berlin Heidelberg, 2003, 448-463.
75. G. S'anchez-Ante, F. Ramos and J.F. Sol'is, Cooperative Simulated Annealing for Path Planning in Multi-robot Systems, in: Proceedings of the Mexican international Conference on Artificial intelligence: Advances in Artificial intelligence (April 11-14, 2000), O. Cair'o, L.E. Sucar and F.J. Cantu, eds, Lecture Notes In Computer Science, 1793, Springer-Verlag, London, 2000, 148-157.
76. E. Terzi, A. Vakali and L. Angelis, A Simulated Annealing Approach for Multimedia Data Placement, The Journal of Systems and Software 73 (2004), 467-480.
77. X.Yao and N. Kanani, Call routing by simulated annealing, in: Proceedings of the 8th international Conference on industrial and Engineering Applications of Artificial intelligence and Expert Systems (Melbourne, Australia, June 05-09, 1995), G.F. Forsyth and M. Ali, eds, International conference on Industrial and engineering applications of artificial intelligence and expert systems, Gordon and Breach Science Publishers, Newark, NJ, 1995, pp. 737-744.
78. A. Anagnostopoulos, L. Michel, P.V. Hentenryck and Y. Vergados, A simulated annealing approach to the traveling tournament problem, J of Scheduling 9(2) (2006), 177-193.
79. S. Zhou, Y. Liu and D. Jiang, A Genetic-Annealing Algorithm for Task Scheduling Based on Precedence Task Duplication, in: Proceedings of the Sixth IEEE International Conference on Computer and Information Technology (September 20-22, 2006). CIT. IEEE Computer Society, Washington, DC, 2006, 117.
80. A.A. Kazem, A.M. Rahmani and H.H. Aghdam, A Modified Simulated Annealing Algorithm for Static Task Scheduling in Grid Computing, in: Proceedings of the 2008 international Conference on Computer Science and information Technology (August 29-September 02, 2008), ICCSIT. IEEE Computer Society, Washington, DC, 2008, 623-627.
81. S. Kazarlis, Solving University Timetabling Problems Using Advanced Genetic Algorithms, 5th International Conference on Technology and Automation (ICTA 2005), 2005.
82. K. Tourtoglou and M. Virvou, User Stereotypes for Student Modelling in Collaborative Learning: Adaptive Advice to Trainers, inProceeding of the 2008 Conference onKnowledge- Based Software Engineering: Proceedings of the Eighth Joint Conference on Knowledge-Based Software Engineering, M. Virvou and T. Nakamura, eds, Frontiers in Artificial Intelligence and Applications, vol. 180, 2008, 505-514.
83. D.S. Johnson, C.R. Aragon, L.A. McGeoch and C. Schevon, Optimization by simulated annealing: an experimental evaluation. Part I, Graph Partitioning, Oper Res 37(6) (1989), 865-892.