Projets de recherche en cours

ü  A Neural Control of Cognitive and Emotional Interactions for Intelligent Immersive Environments (CRSNG-RDC, PROMPT, 2018-2020)

 

ü  Methods and Tools for Active Adaptation in Serious Games Based on a Rich User Model (CRSNG, 2017-2022)

 

ü  Jeux sérieux adaptatifs utilisant l'analyse des réactions cognitives et émotionnelles pour favoriser l'apprentissage (FRQSC – Équipe de recherche, 2016-2019)

 

ü  Algorithmes d'apprentissage profond pour la classification et la prédiction de comportements à partir de données multimodales (CRSNG – BMU)

 

ü  Technologies éducatives pour l'enseignement en contexte: Systèmes tutoriels intelligents sensibles au contexte. Subvention de recherche conjointe de la France et du Québec, du programme ANR-FRQSC no 2017-QF-210862, pour 3 ans (2016-2019).

 

Publications (extrait)

 

Livres

1.       P.  Fournier-Viger, C.-W. Lin, R. Nkambou and B. Vo (2018). High-Utility Pattern Mining: Theory, Algorithms and Applications. Springer

2.       R. Nkambou, R. Azevedo, J. Vassileva (2018). Intelligent Tutoring Systems - 14th International Conference, ITS 2018, Montreal, QC, Canada, June 11-15, 2018, Proceedings. Lecture Notes in Computer Science 10858, Springer 2018, ISBN 978-3-319-91463-3

3.       J. Bourdeau, J, Hendler, R. Nkambou, I. Horrocks, B. Zhao (2016). Proceedings of the 25th International Conference on World Wide Web, WWW 2016. ACM 2016., ISBN 978-1-4503-4143-1

4.       J. Bourdeau, J, Hendler, R. Nkambou, I. Horrocks, B. Zhao (2016). Proceedings of the 25th International Conference on World Wide Web, WWW 2016, Companion Volume. ACM 2016., ISBN 978-1-4503-4144-8

5.       R. Nkambou, J. Bourdeau & R. Mizoguchi (2010). Advances in Intelligent Tutoring Systems. Springer. ISBN: 978-3-642-14362-5

6.       B.P. Woolf, E. Aïmeur, R. Nkambou & S. Lajoie (2008). Intelligent Tutoring Systems. LNCS No. 5091, Springer. ISBN 978 -3-540-69130-3

 

 

Apprentissage machine et modélisation de l’apprenant

7.       A. Tato, R. Nkambou, A. Dufresne and C.  Frasson (2018). Semi-Supervised Multimodal Deep Learning Model for Polarity Detection in Arguments. International Joint Conference on Neural Networks (IJCNN), IEEE, 8p.

8.       A. Tato, R. Nkambou and C. Frasson (2018). Predicting Emotions From Multimodal Users' Data. In Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization (UMAP'18). ACM, pp. 369-370.

9.       A. Tato, R. Nkambou, J. Brisson, S. Robert (2017). Predicting Learner's Deductive Reasoning Skills Using a Bayesian Network. Artificial Intelligence in Education, AIED 2017, pp. 381-392. Springer

10.    A.A. Nyamen Tato, R. Nkambou and A. Dufresne (2017). Convolutional Neural Network for Automatic Detection of Sociomoral Reasoning Level. In: X. Hu, T. Barnes, A. Hershkovitz, L. Paquette (Eds), Proceedings of the 10th International Conference on Educational Data Mining (EDM'17), pp. 284-289.

11.    R. Yapan Dougnon, P. Fournier-Viger, J. Chun-Wei Lin, R.  Nkambou (2016). Inferring social network user profiles using a partial social graph. J. Intell. Inf. Syst. 47(2): 313-344

12.    Y.R. Dougnon, P.  Fournier-Viger, R. Nkambou (2015). Inferring User Profiles in Social Networks using a Partial Social Graph. Proc. 28th Canadian Conference on Artificial Intelligence (AI), LNAI 9091, Springer, pp. 84-99.

13.    T. Gueniche, P. Fournier-Viger, R. Nkambou, V.S. Tseng (2014) WBPL: An Open-Source Library for Predicting Web Surfing Behaviors. Proc. 21st Inter. Symposium on Methodologies for Intelligent Systems, LNAI, pp. 524-529.

14.    Y.R. Dougnon, P.  Fournier-Viger, J.C.-W. Lin, R.  (2015). Accurate Social Network User Profiling. Proc. 38th German Conference on Artificial Intelligence (KI 2015), Springer LNAI 9324, pp 264-270

 

Extraction de connaissances et Data Mining

15.    P. Fournier-Viger, C.-W. Wu, V.S. Tseng, L., Cao, R. Nkambou, R. (2015). Mining Partially-Ordered Sequential Rules Common to Multiple Sequences. IEEE Transactions on Knowledge and Data Engineering (TKDE), 27(8): 2203-2216.

16.    E. Kenmogne, R. Nkambou, C. Tadmon, E. Mephu (2017). A heuristic to predict the optimal pattern-growth direction forthe pattern growth-based sequential pattern mining approach. Journal of Advanced Computer Science & Technology. 5(2): 20-32.

17.    E. Kenmogne, C. Tadmon, R. Nkambou (2017). A pattern growth-based sequential pattern mining algorithm called prefixSuffixSpan. EAI Endorsed Trans. Scalable Information Systems. 4(12)

 

Systèmes Tutoriels Intelligents: Contexte

18.    C. Anjou, T. Forissier, J. Bourdeau, Y. Mazabraud, R. Nkambou, F. Fournier (2017). Elaborating the Context Calculator: A Design Experiment in Geothermy. CONTEXT 2017, pp. 513-526, Springer.

19.    J. Bourdeau, T. Forissier, Y. Mazabraud, R. Nkambou (2015), Web-Based Context-Aware Science Learning. WWW (Companion Volume) 2015, pp. 1415-1418, ACM

20.    T. Forissier, J. Bourdeau, Y. Mazabraud, R.  Nkambou (2014). Computing the Context Effect for Science Learning. In Context in Computing, Springer, New York, pp. 255-269.

 

Ingénierie des connaissances, Génie-ontologique

Ontology Refactoring

21.    M. Héon, R. Nkambou, M. Gaha (2016). OntoCASE4G-OWL: Towards a modeling tool for G-OWL a visual syntax for RDF/RDFS/OWL2. The 15th International Semantic Web Conference (Posters & Demos) Proceedings, 4 pages.

22.    S. Fennouh, R. Nkambou, P. Valtchev, M. Rouane-Hacene (2015). On the Assessment of Concept Relevance in FCA-based Ontology Restructuring. Full paper to appear in the Proceedings of the 27th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2015), IEEE Press.

23.    S. Fennouh, R. Nkambou, P. Valtchev, M. Rouane-Hacene (2015). Stability-Based Filtering for Ontology Restructuring. Studia Universitatis Babes-Bolyai, Informatica, 59: 8-44.

24.    E. Tawamba, R. Nkambou, B. Batchakui, C. Tangha (2014). MS-ONTO - Model and System for Supporting Ontology Evolution. Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD 2014), pp. 319-326, SciTePress 

25.    M. Rouane Hacene, P. Valtchev, R. Nkambou (2011). Supporting ontology design through large-scale FCA-based ontology restructuring. Proc. of the 19th International Conference on Conceptual Structures (ICCS 2011), LNCS No. 6828, pp. 257-269.

26.    M. Rouane Hacene, S. Fennouh, R. Nkambou, P.  Valtchev (2010). Refactoring of Ontologies: Improving the Design of Ontological Models with Concept Analysis. IEEE  ICTAI  2010: 167-172

 

Ontology Learning from Text

27.    A. Zouaq et R. Nkambou (2009). Evaluating the Generation of Domain Ontologies in the Knowledge Puzzle Project. IEEE Transactions on Knowledge and Data Engineering, 21(11): 1559-1572.

28.    A. Zouaq & R. Nkambou (2009). Enhancing learning objects with an ontology-based memory. IEEE Transactions on Knowledge and Data Engineering, 21(6): 881-893.

29.    P. Fournier-Viger, R. Nkambou & A. Mayers (2008), "Evaluating Spatial Representations and Skills in a Simulator-Based Tutoring System," IEEE Transactions on Learning Technologies, Jan-Mar 2008, pp. 63-74. 

30.    A. Zouaq, R. Nkambou (2008), "Building Domain Ontologies from Text for Educational Purposes" IEEE Transactions on Learning Technologies, Jan-Mar 2008, pp. 49-62.  IEEE Computer Society 

31.    A. Zouaq, R. Nkambou, C. Frasson (2007). An Integrated Approach for Automatic Aggregation of Learning Knowledge Objects. Interdisciplinary Journal of Knowledge and Learning Objects, 3: 135-162.

32.    A. Zouaq, R. Nkambou and C. Frasson (2008). Bridging the Gab between ITS and eLearning: Towards Learning Knowledge Objects.   LNCS No 5091. ITS’2008, pp. 448-458, Springer.

33.    A. Zouaq, R. Nkambou and C. Frasson (2007). Building Domain Ontologies from Text for Educational Purposes. LNCS No 4753.   EC-TEL 2007, pp. 393-407, Springer

34.    A. Zouaq, R. Nkambou and C. Frasson (2007). Using a Competence Model to Aggregate Learning Knowledge Objects. In Proceedings of the 7th IEEE conference on Advanced Learning Technologies (ICALT 2007), pp. 836-840.

35.    A. Zouaq, R. Nkambou and C. Frasson (2007). Une architecture d’acquisition et d’exploitation des connaissances pour les EIAH. In Proceedings of the Third Conference on « Environnements Informatiques pour l'Apprentissage Humain » (EIAH 2007), pp. 131-136, Lausanne, Switzerland, June 27-29, 2007.

36.    Amal Zouaq, Roger Nkambou, and Claude Frasson (2007).  Towards Learning Knowledge Objects. In Proceedings of The 13th International Conference on Artificial Intelligence in Education (AIED 2007), pp. 674-676, IOS Press.

37.    A. Zouaq, R. Nkambou and C. Frasson (2007). Learning a Domain Ontology in the Knowledge Puzzle Project. In Proceedings of the Workshop on the Semantic Web for e-Learning (SWEL 2007), Marina Del Rey, USA, July 9-13, 2007.

38.    A. Zouaq, R. Nkambou and C. Frasson (2007). A Framework for the Capitalization of e-Learning Resources. In C. Montgomerie & J. Seale (Eds.), Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2007 (pp. 1241-1247). Chesapeake, VA: AACE.

39.    A. Zouaq, R. Nkambou, C. Frasson (2007). Document Semantic Annotation for Intelligent Tutoring Systems: a Concept Mapping Approach. In proceedings of The 20th International Florida Artificial Intelligence Research Society Conference (FLAIRS 2007), pp. 380-385, AAAI Press, USA

40.    A. Zouaq, R. Nkambou and C. Frasson (2006). The Knowledge Puzzle: An Integrated Approach of Intelligent Tutoring Systems and Knowledge Management, IEEE ICTAI’2006, pp. 575-582, 18th IEEE International Conference on Tools with Artificial Intelligence, IEEE press.

41.    A. Zouaq, C. Frasson, R. Nkambou (2006). An Ontology-Based Solution for Knowledge Management and E-Learning Integration. Proceedings of the 8th International Conference on Intelligent Tutoring Systems (ITS’2006). LNCS No. 4053, pp. 716-718. Springer-Verlag, Berlin.

 

Systèmes Tutoriels Intelligents : Applications

Muse-Logique  

42.    A. Tato, R. Nkambou, J. Brisson, C. Kenfack, S. Robert, S., & P. Kissok (2016). A Bayesian Network for the Cognitive Diagnosis of Deductive Reasoning. Adaptive and Adaptable Learning - 11th European Conference on Technology Enhanced Learning (EC-TEL2016), pp. 627-631. Springer International Publishing.

43.    C. Kenfack, R. Nkambou, S. Robert, A. Tato, J. Brisson, & P. Kissok (2016). A Brief Overview of Logic-Muse, an Intelligent Tutoring System for Logical Reasoning Skills. In Intelligent Tutoring Systems (ITS'2016), LNCS 9684, pp. 511–513. Springer International Publishing.

44.    R. Nkambou, A. Tato, J. Brisson, C. Kenfack, S. Robert, & P. Kissok, P. (2016). On the Evaluation of the Expert and the Learner Models of Logic-Muse Tutoring System. In Intelligent Tutoring Systems (ITS'2016), LNCS 9684, pp. 506–508. Springer International Publishing.

45.    R. Nkambou, J. Brisson, C. Kenfack, S. Robert, P. Kissok, A. Tato (2015). Towards an Intelligent Tutoring System for Logical Reasoning in Multiple Contexts. Design for Teaching and Learning in a Networked World, LNCS 9307, pp 460-466, Springer

46.    R. Nkambou, C. Kenfack, J. Brisson, S. Robert, P. Kissok, A. Tato (2015). The Participatory Design of Logic-Muse, an Intelligent Tutoring System for Logical Reasoning in Multiple Contexts. In S. Carliner, C. Fulford & N. Ostashewski (Eds.), Proceedings of EdMedia: World Conference on Educational Media and Technology 2015 (pp. 1710-1719). Association for the Advancement of Computing in Education (AACE).

47.    R. Nkambou, C. Kenfack, S. Robert, J. Brisson (2015). The Design Rationale of Logic-Muse, an ITS for Logical Reasoning in Multiple Contexts.  Artificial Intelligence in Education (AIED2015), LNAI 9112, pp. 738-742, Springer

 

ISLA

48.    A.L. Mondragon, R. Nkambou, P. Poirier. (2016). Evaluating the Effectiveness of an Affective Tutoring Agent in Specialized Education. Adaptive and Adaptable Learning - 11th European Conference on Technology Enhanced Learning (EC-TEL2016), pp. 446-452. Springer International Publishing.

49.    A.L. Mondragon, R. Nkambou, P. Poirier. (2016). Towards an Effective Affective Tutoring Agent in

Specialized Education. LNCS 9684. 13th International Conference on Intelligent Tutoring Systems, pp. 402-408. Springer

50.    A.L. Mondragon, R. Nkambou, P. Poirier (2015). Towards an Integrated Specialized Learning Application (ISLA) to Support High Functioning ASD Children in Mathematics Learning. Design for Teaching and Learning in a Networked World, LNCS 9307, pp 225-239, Springer

 

Roman & Canadarm Tutors

51.    K. Belghith, R. Nkambou, F., Kabanza and L., Hartman (2011). An Intelligent Simulator for Tele-robotics Training. IEEE Transactions on Learning Technologies (TLT) (in press).

52.    R. Nkambou, K. Belghith, F. Kabanza (2006). An Approach to Intelligent Training on a Robotic Simulator using an Innovative Path-Planner. Proceedings of the 8th International Conference on Intelligent Tutoring Systems (ITS’2006).  LNCS No.4053, pp. 645-654, Springer-Verlag, Berlin.

53.    K. Belghith, F. Kabanza, L. Hartman, R. Nkambou (2006). Anytime Dynamic Path-Planning with Flexible Probabilistic Roadmaps. Proceedings of ICRA’2006 (IEEE International Conference on Robotics and Automation), pp. 2372- 2377. IEEE press.

54.    R. Nkambou, K. Belghith, F. Kabanza (2006). Generating tutoring feedback in an intelligent training system on a Robotic Simulator. Proceedings of the 19th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert System, LNAI No 4031, pp. 838-847.

55.    F. Kabanza, R. Nkambou, K. Belghith, L. Hartman (2005). Path-Planning for Autonomous Training on Robot Manipulators in Space. Proceedings of IJCAI’2005 (International Joint Conferences on Artificial Intelligence), pp. 1729-1732.

56.    R. Nkambou, K. Belghith, F. Kabanza, M. Khan (2005). Supporting Training on Canadarm Simulator using a Flexible Path Planner. In: Artificial Intelligence in Education, IOS Press, Amsterdam, pp. 953-955 (2005).

57.    J. Roy, R. Nkambou, F. Kabanza (2004). Supporting Spatial Awareness in Training on a Telemanipulator in Space. In: J.C. Lester et al. (Eds.): ITS 2004, LNCS 3220, pp. 860-863, 2004. Springer-Verlag Berlin Heidelberg 2004

58.    R. Nkambou, F. Kabanza (2001). “Planning Agents in a Multi-agents Intelligent Tutoring System”. In: Engineering of Intelligent Systems. LNCS/LNAI no. 2070, pp. 921-930. Springer-Verlag, Berlin.

59.    R. Nkambou, F. Kabanza. Designing Intelligent Tutoring Systems: A multiagent Planning Approach. ACM SIGCUE Outlook, 27(2),  pp. 46-60. ACM Press (2001).

 

Prolog Tutor

60.    J. Pelle, R. Nkambou, J. Bourdeau (2007). Explicit Reflexion in Prolog-Tutor. International Journal of Intelligence Intelligence in Education (IJAIED). Vol. 17, No. 2, pp. 169-215. IOS.

61.    Pelle, R. Nkambou, J. Bourdeau (2005). Supporting Student Reflection in an Intelligent Tutoring System for Logic Programming. In: Proceedings of the AIED’2005 workshop on Learner Modeling for Reflection, pp. 42-51. Amsterdam.

62.    J. Tchetagni, R. Nkambou and F. Kabanza (2004). Epistemological Remediation in Intelligent Tutoring Systems. In : proceedings of the 17th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert System, pp. 955-966. LNAI 3029, Springer.

63.    R. Nkambou, J. Tchetagni (2004). Diagnosing Student Errors in E-Learning Environment Using MPE Theory. In Proceedings of the International Conference on Web-Based Education, pp. 249-254.

 

Agents cognitifs & Modèles cognitifs

 

64.    O. Larue, P. Poirier, R. Nkambou (2013). Hypothetical-thinking based on cognitive decoupling and thinking dispositions in a dual cognitive agent.  Biologically Inspired Cognitive Architectures, 6: 67-75. Elsevier.

65.    O. Larue, P. Poirier, R. Nkambou (2013). The emergence of (artificial) emotions from cognitive and neurological processes. Biologically Inspired Cognitive Architectures, 4: 54-68. Elsevier.

66.    U. Faghihi, P. Fournier-Viger & R. Nkambou (2012). A Computational Model for Causal Learning in Cognitive Agents. Knowledge-Based Systems, Elsevier. Elsevier Science (In press).

67.    U. Faghihi, P. Poirier, P., Fournier-Viger & R. Nkambou (2011). Human-Like Learning in a Cognitive Agent. Journal of Experimental & Theoretical Artificial Intelligence, Taylor & Francis (in press).

68.    U. Faghihi, P. Fournier-Viger, R. Nkambou & P. Poirier (2011). Identifying Causes Helps a Tutoring System to Better Adapt to Learners During Training Sessions. J. of Intelligent Learning Systems & Applications, 3(3).

69.    U. Faghihi, P. Fournier-Viger & R. Nkambou (2011). A Cognitive Tutoring Agent with Human-Like Learning Capabilities. Proc. of the 15th International. Conference on Artificial Intelligence and Education (AIED 2011). Springer, 8 pages

70.    R. Nkambou, P. Fournier-Viger, E. Mephu Nguifo (2009). Improving the Behavior of Intelligent Tutoring Agents with Data Mining. IEEE Intelligent Systems, 24(3):46-53.

71.    P. Fournier-Viger, R. Nkambou, A. Mayer, U. Faghihi (2008). A Framework for Evaluating Semantic Knowledge in Problem-Solving-Based Intelligent Tutoring Systems. FLAIRS’2008. AAAI press.

72.    P. Fournier-Viger, R. Nkambou, A. Mayers and D. Dubois (2007), “Automatic Evaluation of Spatial Representations for Complex Robotic Arms Manipulations”. Proceedings of the 7th IEEE International Conference on Advanced Learning Technologies (ICALT 2007), pp. 279-281.

73.    P. Fournier-Viger, M. Najjar, A. Mayers, R. Nkambou (2006). A Cognitive and Logic based Model for Building Glass-box Learning Objects. Inter.  Journal of Knowledge and Learning Objects, 2: 77-94.

74.    Faghihi, U., Dubois, D. & Nkambou, R. (2007). Learning Mechanisms for a Tutoring Cognitive Agent. In C. Montgomerie & J. Seale (Eds.), Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2007 (pp. 3106-3114). Chesapeake, VA: AACE.

75.    D. Dubois, R. Nkambou, P. Hohmeyer (2006). How ‘Consciousness’ Allows a Cognitive Tutoring Agent Make Good Diagnosis During Astronauts’ Training. Proceedings of the 8th International Conference on Intelligent Tutoring Systems (ITS’2006). LNCS No 4053, pp. 154-163, Springer-Verl.

76.    D. Dubois, R. Nkambou, P. Hohmeyer (2006). The Role of «Consciousness» for the Diagnosis Process in a Tutoring Agent. Proceedings of the Florida Artificial Intelligence Research Society (FLAIRS’2006), pp. 539-540.  AAAI press.

77.    D. Dubois, R. Nkambou, P. Hohmeyer (2006). Supporting Simulation-Based Training Using a «Conscious» Tutoring Agent. Proceedings of the IEEE-ICALT’2006, IEEE press.

78.    P. Fournier-Viger, M. Najjar, A. Mayers, R. Nkambou (2006). From Black-box Learning Objects to Glass-Box Learning Objects. Proceedings of the 8th International Conference on Intelligent Tutoring Systems (ITS’2006).  LNCS No 4053, pp. 258-267. Springer-Verlag, Berlin.

 

 

Systèmes auteurs

79.    J. Pelle, R. Nkambou, J. Bourdeau (2006). A framework to help instructional designers to specify cognitive diagnosis component in ILEs. Journal of Interactive Learning Research, 17(3): 269-293. AACE

80.    J. Pelle, R. Nkambou (2006). Elaborating the context of interactions in a tutorial dialog. Proceedings of the 19th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert System, LNAI No 4031, pp. 848-858. Springer-Verlag, Berlin.

81.    V. Psyché, J. Bourdeau, R. Nkambou, R. Mizoguchi (2005). Making Learning Design Standards Work with an Ontology of Educational Theories. In: Artificial Intelligence in Education, IOS Press, Amsterdam, pp. 725-731 (2005).

82.    J. Bourdeau, R. Mizoguchi, V. Psyché, R. Nkambou. Selecting Theories in an Ontology-Based ITS Authoring Environment (2004). In: J.C. Lester et al. (Eds.): ITS 2004, LNCS 3220, pp. 150–161, 2004. Springer-Verlag Berlin Heidelberg 2004

83.    R. Nkambou, C. Frasson and G. Gauthier (2003). “CREAM-Tools : An Authoring Environment for Knowledge Engineering in Intelligent Tutoring Systems”.  In : Murray et al.  (Eds) : Authoring Tools for Advanced Technology Learning Environments : Toward cost-effective adaptative, interactive, and intelligent educational software. Pages 93-138. Kluwer Publishers.Kluwer Publishers.

84.    R. Nkambou, C. Frasson, G. Gauthier and. Rouane. An Authoring Model and Tools for Knowledge Engineering in ITS.  Journal of Interactive Learning Research, 12(4), pp. 323-357 (2001).

 

Fouille de données et extractions de connaissances (2)          

85.    P. Fournier-Viger, U. Faghihi, R. Nkambou & E. Mephu Nguifo (2012). CMRules: Mining Sequential Rules Common to Several Sequences. Knowledge-Based Systems. 25(1): 63-76. Elsevier Science.

86.    R. Nkambou, P. Fournier-Viger & E. Mephu Nguifo (2011). Learning Task Models in Ill-defined Domain Using an Hybrid Knowledge Discovery Framework. Knowledge-Based Systems, 24(1): 176-185. Elsevier.

87.    P. Fournier-Viger, U. Faghihi, R. Nkambou & E. Mephu Nguifo (2010). Exploiting Sequential Patterns Found in Users’ Solutions and Virtual Tutor Behavior to Improve Assistance in ITS. Educational Technology & Society, 13(1): 12-24.

88.    P. Fournier-Viger, R. Nkambou & V.S. Tseng (2011). RuleGrowth: Mining Sequential Rules Common to Several Sequences by Pattern-Growth. Proceedings of the 26th ACM Symposium on Applied Computing (SAC 2011). ACM Press, pp. 954-959 .

89.    P. Fournier-Viger., R. Nkambou, E. Mephu Nguifo & A. Mayers (2010). ITS in Ill-defined Domains: Toward Hybrid Approaches. Proceedings of the 10th International Conference on Intelligent Tutoring Systems (ITS 2010), LNCS 6095, Springer, pp. 749-751.

90.    P. Fournier-Viger., R. Nkambou, E. Mephu Nguifo (2009). Exploiting Partial Problem Spaces Learned from Users' Interactions to Provide Key Tutoring Services in Procedural and Ill-Defined Domains. Proceedings of the 14th International. Conference on Artificial Intelligence and Education (AIED). IOS Press. pp. 383-390.

91.    P. Fournier-Viger, R. Nkambou,U. Faghihi & E. Mephu(2009). Mining Temporal Patterns to Improve Agents Behavior: Two Case Studies. In Cao, L.(Ed.) Data Mining and Multiagent Integration, Springer, p. 77-92.

92.    P. Fournier-Viger,  R. Nkambou & E. Mephu Nguifo (2008), A Knowledge Discovery Framework for Learning Task Models  from User Interactions in Intelligent Tutoring Systems. Proceedings of the 7th Mexican International Conference on Artificial Intelligence (MICAI 2008). LNAI 5317, pp. 765-778, Springer, Best Paper Award (1st place / 368 submissions / 25.6% acceptance rate). 

93.    R. Nkambou,  E. Mephu Nguifo, P. Fournier-Viger (2008). Using Knowledge Discovery Techniques to Support Tutoring in an Ill-Defined Domain. LNCS No 5091. ITS’2008, pp. 395-405.  Best paper award nom. (top 5 papers).

94.    R. Nkambou,  E. Mephu Nguifo, O. Couturier & P. Fournier-Viger (2007). A Framework for Problem-Solving Knowledge Mining from Users' Action. In Proceedings of The 13th International Conference on Artificial Intelligence in Education (AIED 2007), pp. 623-625, IOS Press.

95.    R. Nkambou,  E. Mephu Nguifo, O. Couturier & P. Fournier-Viger (2007). Problem-Solving Knowledge Mining from Users’ Actions in an Intelligent Tutoring System. Canadian AI’2007, LNAI No. 4509, pp. 393-404. Springer-Verlag, Berlin

96.    E. Mephu and R. Nkambou (2006). Enhancing Tutoring Intelligence Using Knowledge Discovery Techniques. Proceedings of the IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology – Workshops; pp. 7-10.

 

Informatique affective et Agents émotionnels          

97.    R. Nkambou, E. Delozanne & C. Frasson (2008). Les dimensions émotionnelles de l’interaction dans un EIAH. Sciences et Techno. de l’Information et de la Communication pour la Formation (STICEF),  14: pp. 205-216.

98.    M. Gaha, D. Dubois & R. Nkambou (2008). Proposition d'un traitement émotionnel pour un STI "conscient".  Sciences et Technologies de l’Information et de la Communication pour la Formation(STICEF), 14: 239-264

99.    R. Nkambou (2006). Managing Student Emotions in Intelligent Tutoring Systems. Proceedings of the Florida Artificial Intelligence Research Society (FLAIRS’2006), pp. 389-394. AAAI press.

100.R. Nkambou, V. Héritier, C. Frasson (2005). Plate-forme pour agents pédagogiques affectifs : expression et reconnaissance des émotions. In : Samuel Pierre (Eds). Développement, Intégration et Évaluation des Technologies de Formation et d’Apprentissage. Chap. 9, pp. 247-292. Presses Internationales Polytechniques.

101.R. Nkambou,  Y. Laporte, R. Yatchou et  G. Gouradères (2002). “Embodied Emotional Agent and Intelligent Training System”. In: Abraham, A., Jain, L., & Kacprzyk, J. (Eds), “Recent Advances in Intelligent Paradigms and Applications”.  Chapter 11, pp. 233-253. Springer-Verlag.

102.R. Nkambou (2006). Managing Student Emotions in Intelligent Tutoring Systems. Proceedings of the Florida Artificial Intelligence Research Society (FLAIRS’2006), pp. 389-394. AAAI press.

103.Y. Laporte, R. Nkambou, R. Yatchou (2004). Prototypage d’un agent émotionnel d’interface pour les laboratoires virtuels. Proceedings de TICE’2004; pp. 198-204, Compiègne (France).

104. R. Nkambou, V. Héritier (2004). Reconnaissance émotionnelle par l’analyse des expressions faciales dans un Tuteur Intelligent Affectif. Proceedings de TICE’2004; pp. 147-155, (France).

105.J. Faivre, R. Nkambou and C. Frasson (2003) “ Toward Empathetic Agents in Tutoring Systems”. In: Proceedings of the Florida Artificial Intelligence Research Society, pp. 161-165, AAAI Press.

106.R. Nkambou, Y. Laporte (2001).  “Producing Non-Verbal Output for an Embodied Agent in an Intelligent Tutoring System”. In: Proceedings of ICCS’2001, LNCS no. 2074, pp.366-376.

107. Laporte, R. Nkambou (2001). “Simulating emotional response for an Intelligent Tutoring System”. In: Artificial Intelligence in Education, pp. 568-570. IOS Press, Amsterdam.

 

Architecture de distribution de ressources d’apprentissage           

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