Simulation of Affective Student-Tutor Interaction for Affective Tutoring Systems: Design of Knowledge Structure

AUTHOR(S):

TITLE

Simulation of Affective Student-Tutor Interaction for Affective Tutoring Systems: Design of Knowledge Structure

ABSTRACT

Almost half a century intelligent tutoring systems have been developed towards imitating the learning process of a student and a tutor interaction in a one-to-one tutoring situation. However, the gap for this kind of systems still exists in showing the adaptation skills possessed by human-tutors, particularly, the systems lack emotional intelligence. The paper presents conceptual architecture of agent-based affective tutoring system for the simulation of human-tutors’ and students’ interaction using multi-agent approach for representation of involved parties. Such simulation would allow assessing the effectiveness of selected teaching approach on student’s emotional state, behaviour, and learning progress. Since ontologies play an important role in the agent interaction, the design and usage of knowledge structures necessary for ITS functioning including emotion ontology are considered in this paper as well.

KEYWORDS

Intelligent Tutoring Systems, Emotions, Tutoring Adaptation, Agents, Ontologies, Simulation

REFERENCES

[1] W. Picard, Affective Computing. MIT Press, Cambridge, 1997.

[2] S. Petrovica, A. Anohina-Naumeca, “Design and Implementation of Agent Interaction Mechanisms for Emotionally Intelligent Tutoring Systems”, Scientific Journal of Riga Technical University (5. series). Applied Computer Systems, Vol.13, 2012, pp 44-53.

[3] R.M. Viccari, P.A. Jaques, R. Verdin, “Preface”, Agent-Based Tutoring Systems by Cognitive and Affective Modeling, 2008, pp. xiii-xxxiii.

[4] Y. Shoham, K. Leyton-Brown, Multiagent Systems - Algorithmic, Game-Theoretic, and Logical Foundations, Cambridge, UK: Cambridge University Press, 2009.

[5] E. Oguejiofor, R. Kicinger, E. Popovici, T. Arciszewski, K.A. de Jong, “Intelligent Tutoring Systems: An Ontology-Based Approach”, International Journal of IT in Architecture, Engineering and Construction, Vol. 2, No. 2, 2004, p. 115-128.

[6] V. Graudina, “An Overview of Ontology Usage in Computer-Based Tutoring Systems”, ICTE in Regional Development: Annual Proceedings of Vidzeme University College, 2007, pp.70-77.

[7] W.R. Murray, “Intelligent Tutoring Systems for Commercial Games: The Virtual Combat Training Center Tutor and Simulation”, Proceedings of the 2nd Artificial Intelligence and Interactive Digital Entertainment Conference, 2006, pp. 66-71.

[8] H.-S. Chung, J.-M. Kim, “Ontology Design for Creating Adaptive Learning Path in -Learning Environment”, Proceedings of the International MultiConference of Engineers and Computer Scientists, 2012, pp. 585-588.

[9] B. Vesin, M. Ivanovic, A. Klasnja-Milicevic, Z. Budimac, “Protus 2.0: Ontology-Based Semantic Recommendation in Programming Tutoring System”, Expert Systems with Applications, Vol.39, No.15, 2012, pp. 12229- 12246.

[10] R.A. Sottilare, H.K. Holden, “Motivations for a Generalized Intelligent Framework for Tutoring (GIFT) for Authoring, Instruction, and Analysis”, Recommendations for Authoring, Instructional Strategies and Analysis for Intelligent Tutoring Systems (ITS), 2013, pp. 1-9.

[11] Y. Hayashi, J. Bourdeau, R. Mizoguchi, “Using Ontological Engineering to Organize Learning/Instructional Theories and Build a Theory-Aware Authoring System”, International Journal of Artificial Intelligence in Education, Vol.19, No.2, 2009, pp. 211-252.

[12] S. Wang, “Ontology of Learning Objects Repository for Pedagogical Knowledge Sharing”, Interdisciplinary Journal of ELearning and Learning Objects, Vol.4, No.1, 2008, pp. 1–12.

[13] A. Yessad, C. Faron-Zucker, R. Dieng-Kuntz, M.T. Laskri, “Ontology-based Semantic Relatedness for Detecting the Relevance of Learning Resources”, Interactive Learning Environments, Vol.19, No.1, 2011, pp. 63-80.

[14] M.A. Abbas, W.F.W. Ahmad K.S. Kalid, “Semantic Web Technologies for Pre-School Cognitive Skills Tutoring System”, ARPN Journal of Engineering and Applied Sciences, Vol.10, No.23, 2015, pp. 17758-17765.

[15] P. Bakhtyari, “Automatic Feedback Generation – Using Ontology in an Intelligent Tutoring System for both Learner and Author Based on Student Model”, Proceedings of ICEIS 2006: Databases and Information Systems Integration, 2006, pp. 116-123.

[16] B.S. Bloom, “The 2 Sigma Problem: The Search for Methods of Group Instruction as Effective as One-to-One Tutoring”, Educational Researcher, Vol.13, No.6, 1984, pp. 4-16.

[17] N. Thompson, T.J. McGill, “Affective Tutoring Systems: Enhancing E-Learning with the Emotional Awareness of a Human Tutor”, International Journal of Information and Communication Technology Education, Vol.8, No.4, 2012, pp. 75-89.

[18] S.D. Craig, A.C. Graesser, J. Sullins, B. Gholson, “Affect and Learning: An Exploratory Look into the Role of Affect in Learning with AutoTutor”, Journal of Educational Media, Vol.29, 2004, pp. 241-250.

[19] B. Lehman, S.K. D'Mello, N. Person, “The Intricate Dance between Cognition and Emotion during Expert Tutoring”, Proceedings of 10th International Conference on Intelligent Tutoring Systems (Part II), 2010, pp. 433-442.

[20] N. Schwarz, “Emotion, Cognition, and Decision Making”, Journal of Cognition and Emotion, Vol.14, No.4, 2000, pp. 440–443.

[21] M. Ochs, C. Frasson, “Emotionally Intelligent Tutoring Systems (EITS)”, Proceedings of the FLAIRS 2004 Conference, 2004, pp. 251-256.

[22] J. Yan, D.B Bracewell, F. Ren, S. Kuroiwa, “The Creation of a Chinese Emotion Ontology Based on HowNet”, Engineering Letters, Vol. 16, No. 1, 2008, pp. 166-171.

[23] J. Hastings, W. Ceusters, B. Smith, K. Mulligan, “Dispositions and Processes in the Emotion Ontology”, ICBO: International Conference on Biomedical Ontology, 2011, pp. 71-78.

[24] M. Grassi, “Developing HEO Human Emotions Ontology”, Biometric ID Management and Multimodal Communication, 2009, pp.244-251.

[25] R. Gil, J. Virgilli-Goma, R. Garcia, C. Mason, “Emotions Ontology for Collaborative Modelling and Learning of Emotional Responses”, Computers in Human Behavior, Vol. 51, Part B, 2015, pp. 610 - 617.

[26] A. Ortony, G.L. Clores, A. Collins, “The Cognitive Structure of Emotions”, Cambridge, MA: Cambridge University Press, 1988.

[27] J.A. Russell, A. Mehrabian, “Evidence for a Three-Factor Theory of Emotions”, Journal of Research in Personality, Vol. 11, No.3, 1977, pp. 273–294.

[28] W. Eyharabide, A. Amandi, M. Courgeon, C. Clavel, C. Zakaria, J. C. Martin, “An Ontology for Predicting Student Emotions During A Quiz”, Proceedings of IEEE Workshop on Affective Computational Intelligence, 2011, pp. 76-83.

[29] K. Kaneko, Y. Okada, “Building on Japanese Emotion Ontology from Knowledge on the Web for Realistic Interactive GC Characters”, Proceedings of 7th International Conference on Complex, Intelligent, and Software Intensive Systems, 2013, pp. 735-740.

[30] P. Ekman, “Are there basic emotions?”, Psychological Review, Vol. 99, No. 3, 1992, pp. 550-553.

[31] M. Sykora, T. Jackson, A. Brien, S. Elayan, “Emotive Ontology: Extracting Fine-Grained Emotions from Terse, Informal Messages”, IADIS International Journal on Computer Science and Information Systems, Vol. 2, No. 2, 2013, pp. 106-118.

[32] K.I. Benta, A. Rarau, M. Cremene, “Ontology Based Affective Context Representation”, Proceedings of the Euro American conference on Telematics and information systems, 2007, Article No. 46.

[33] F. Berthelon, P. Sander, “Emotion Ontology for Context Awareness”, Proceedings of 4th IEEE International Conference on Cognitive Infocommunications, 2013, pp. 59-64.

[34] W3C, “Web Ontology Language”, available at https://www.w3.org/2001/sw/wiki/OWL, 2013.

[35] W3C, “Resource Description Framework”, available at https://www.w3.org/RDF/, 2014.

[36] W3C, “Emotion Markup Language (EmotionML) 1.0”, available at https://www.w3.org/TR/emotionml/, 2014.

[37] S.K. D’Mello, A.C. Graesser, “AutoTutor and Affective AutoTutor: Learning by Talking with Cognitively and Emotionally Intelligent Computers that Talk Back”, ACM Transactions on Interactive Intelligent Systems, Vol.2, No. 4, 2012, pp. 23:2-23:39.

[38] N. Jaques, C. Conati, J.M. Harley, R. Azevedo, “Predicting Affect from Gaze Data during Interaction with an Intelligent Tutoring System”, Proceedings of the 12th International Conference on Intelligent Tutoring Systems, 2014, pp. 29-38.

[39] M. Wixon, I. Arroyo, K. Muldner, W. Burleson, C. Lozano, B.P. Woolf, “The Opportunities and Limitations of Scaling Up Sensor-Free Affect Detection”, Proceedings of the 7th International Conference on Educational Data Mining, 2014, pp. 145-152.

[40] S.K. D’Mello, N. Blanchard, R. Baker, J. Ocumpaugh, K. Brawner, “I Feel Your Pain: A Selective Review of Affect-Sensitive Instructional Strategies”, Design Recommendations for Adaptive Intelligent Tutoring Systems: Volume 2 – Instructional Management, 2014, pp. 35-48.

[41] R. Sottilare., J. DeFalco, J. Connor, “A Guide to Instructional Techniques, Strategies and Tactics to Manage Learner Affect, Engagement, and Grit”, Design Recommendations for Adaptive Intelligent Tutoring Systems: Volume 2 – Instructional Management, 2014, pp. 7-33.

[42] S. Petrovica, “Adaptation of Tutoring to Students' Emotions in Emotionally Intelligent Tutoring Systems”, Proceedings of Second International Conference on e-Learning and eTechnologies in Education, 2013, pp. 131-136.

[43] S. Chaffar, C. Frasson, “Using an Emotional Intelligent Agent to Improve the Learner's Performance”, Workshop on Emotional and Social Intelligence in Learning Environments, in the 7th International Conference on Intelligent Tutoring Systems, 2004, pp. 37-43.

[44] M. Ally, P. Fahy, “Using Students’ Learning Styles to Provide Support in Distance Education”, Proceedings of the 18th Annual Conference on Distance Teaching and Learning, 2002, pp. 1-5.

[45] M. Wooldridge, An Introduction to Multi-Agent Systems, John Wiley&Sons, 2009.

[46] A.L. Baylor, Y. Kim, “Simulating Instructional Roles through Pedagogical Agents”, International Journal of Artificial Intelligence in Education, Vol.15, No.2, 2005, pp. 95-115.

[47] V. Graudina, J. Grundspenkis, “The Role of Ontologies in Agent-Based Simulation of Intelligent Tutoring Systems”, Proceedings of the 19th European Conference on Modelling and Simulation, 2005, pp. 446-451.

[48] M. Spoelstra, E. Sklar, “Agent-Based Simulation of Group Learning”, Multi-AgentBased Simulation VIII: International Workshop, MABS 2007, Revised and Invited Papers, 2008, pp 69-83.

[49] A. Adams, P. Robinson, “Automated Recognition of Complex Categorical Emotions from Facial Expressions and Head Motions”, Proceedings of International Conference on Affective Computing and Intelligent Interaction, 2015, pp. 355-361.

[50] M. Bradley, P. Lang, “Measuring Emotion: The Self-Assessment Manikin and the Semantic Differential”, Journal of Behavioral Therapy and Experimental Psychiatry, Vol. 25, No 1, 1994, pp. 49-59.

[51] J. Broekens, W.P. Brinkman, “AffectButton: A Method for Reliable and Valid Affective Self-Report”, International Journal of HumanComputer Studies archive, Vol. 71, No. 6, 2013, pp. 641-667.

[52] P. Gebhard, “ALMA – A Layered Model of Affect”, Proceedings of the 4th International Joint Conference on Autonomous Agents and Multiagent Systems, 2005, pp 29-36.

[53] R.R. McCrae, O.P. John, “An Introduction to the Five-Factor Model and Its Applications”, Journal of Personality, Vol. 60, No. 2, 1992, pp. 175–215.

[54] M. Tavakoli, M. Palhang, M. Kazemifard, “Three Levels of Information Processing: Improvement using Personality”, Proceedings of 2014 Iranian Conference on Intelligent Systems (ICIS), 2014, pp. 1–6.

[55] J.P. Oliver, “The Big Five Project Personality Test”, available at http://www.outofservice.com/bigfive/, 2015.

[56] Y. Kim, A.L. Baylor, “Research-Based Design of Pedagogical Agent Roles: A Review, Progress and Recommendations”, International Journal of Artificial Intelligence in Education, Vol. 26, No. 1, 2016, pp. 160-169. S. Petrovica, M. Pudane Intern

Cite this paper

Sintija Petrovica, Mara Pudane. (2016) Simulation of Affective Student-Tutor Interaction for Affective Tutoring Systems: Design of Knowledge Structure. International Journal of Education and Learning Systems, 1, 99-108