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Multimedia Tools and Applications

, Volume 77, Issue 20, pp 27661–27684 | Cite as

Architecture and interaction protocol for pedagogical-empathic agents in 3D virtual learning environments

  • Theodouli Terzidou
  • Τhrasyvoulos TsiatsosEmail author
  • Hippokratis Apostolidis
Article
  • 158 Downloads

Abstract

This paper proposes an interaction design architecture and an interaction protocol for the construction of pedagogical agents acting in distributed 3D learning environments. Agents designed based on the proposed architecture are able to interact verbally, non-verbally or both with the students, combining empathic and pedagogical behavioral parameters in order to support students during online educational activities. The representation of the agent results from both pedagogical and emotional factors and is related with the learning environment and its technology. The agent logic is based on three types of the learning environment’s events: (a) emotional events, (b) pedagogical events and (c) events that are triggered by the environment itself. The proposed architecture is validated through the implementation of an autonomous pedagogical-empathic agent in the virtual environment of OpenSim. The agent observes students’ anxiety during the learning process and reacts when their anxiety level is considered high.

Keywords

Pedagogical agents Empathic agents 3D virtual learning environments Agent architecture Interaction protocol Immersive learning 

Notes

Acknowledgments

We would like to thank the end users for their support in the evaluation of the presented agent implementation.

References

  1. 1.
    Aguilar RA, Antonio AD, Imbert R (2006) Pedagogical Virtual Agents to Support Training of Human Groups, Electronics, In: Proc. Of the Robotics and Automotive Mechanics Conference (CERMA'06). Cuernavaca 2006:149–154Google Scholar
  2. 2.
    Aimeur E, Frasson C (1996) Analyzing a new learning strategy according to different knowledge levels. Comput Educ 27(2):115–127Google Scholar
  3. 3.
    Arafa Y, Dionisi G, Fehin P (2000) Compaq et al. This document is a deliverable of the MAPPA project Agent-to-Human interaction - principles, a project performed within the ESPRIT programme (project identifier EP28831)Google Scholar
  4. 4.
    Association for Applied Psychophysiology and Biofeedback (2018) https://www.aapb.org. Accessed April 2018
  5. 5.
    Bellifemine F, Caire G, Greenwood D, (2007) Developing Multi-Agent Systems with JADE, John Wiley & Sons, Ltd 4 Agent Technology OverviewGoogle Scholar
  6. 6.
    Carnegie Mellon University (2018) http://www.cs.cmu.edu/~softagents/multi.html. Accessed April 2018
  7. 7.
    Chan TW, Baskin AB (1990) Learning companion systems. In: Frasson C, Gauthier G (eds) Intelligent tutoring systems at the crossroads of artificial intelligence and education. Ablex Publishing Corporation, Norwood, NJ, pp 7–33Google Scholar
  8. 8.
    Chen GD, Lee JH, Wang CY, Chao PY, Li LY, Lee TY (2012) An Empathic Avatar in a Computer-Aided Learning Program to Encourage and Persuade Learners. Educational Technology & Society 15(2):62–72Google Scholar
  9. 9.
    Chopra AK, Artikis A, Bentahar J, Colombetti M, Dignum F, Fornara N, Jones AJI, Singh MP, Yolum P (2013) Research directions in agent communication. ACM Trans. Intell. Syst. Technol. 4, 2, Article 20, 23 pages.  https://doi.org/10.1145/2438653.2438655 Google Scholar
  10. 10.
    Chou, CY, Chan T-W, Lin C-J (2003) Redefining the learning companion: the past, present and future of educational agents. Comput Educ 40(3):255–269Google Scholar
  11. 11.
    Clark R, Feldon D (2014) Ten Common but Questionable Principles of Multimedia Learning. In: Mayer R (ed) The Cambridge Handbook of Multimedia Learning. Cambridge University Press, Cambridge, pp 151–173.  https://doi.org/10.1017/CBO9781139547369.009 Google Scholar
  12. 12.
    Cook DJ (2009) Multi-agent smart environments, Journal of Ambient Intelligence and Smart Environments 1, IOS Press pp. 51–55.  https://doi.org/10.3233/AIS-2009-0007
  13. 13.
    Damasio A (1994) Descartes’ Error: Emotion, Reason, and the Human Brain. G.P. Putnam’s Sons, New YorkGoogle Scholar
  14. 14.
    De Lucia A, Francese R, Passero I, Tortora G (2009) Development and evaluation of a virtual campus on Second Life: The case of SecondDMI. Comput Educ 52:220–233Google Scholar
  15. 15.
    Dillenbourg P, Self J (1992) People power: A human-computer collaborative learning system. In: G.G. Frasson C, McCalla G (ed.) The 2nd international conference of intelligent tutoringsystems, lecture notes in computer science (Vol. 608), Springer-Verlag, pp. 651–660Google Scholar
  16. 16.
    Elliott C, Rickel J, Lester J (1999) Lifelike pedagogical agents and affective computing: An exploratory synthesis, In: Wooldridge MJ, Veloso M (eds), Artificial intelligence today. Lecture Notes In Computer Science, vol. 1600. Springer, Berlin, pp 195–211Google Scholar
  17. 17.
    FIPA ACL Message Structure Specification, Foundation for Intelligent Physical Agents, 2000, http://www.fipa.org/specs/fipa00061/, Accessed July, 24 2017
  18. 18.
    FIPA, Foundation for Intelligent Physical Agents (2018) http://www.fipa.org. Accessed April 2018
  19. 19.
    Franklin S, Graesser A (1996) Is it an Agent, or Just a Program? In: Müller JP, Wooldridge M, Jennings NR (eds), Proc. Of the Workshop on Intelligent Agents III, Agent Theories, Architectures, and Languages (ECAI '96). Springer-Verlag, London, pp 21–35Google Scholar
  20. 20.
    Gill S, Kolt GS, Keating J (2004) Examining the multi-process theory: an investigation of the effects of two relaxation techniques on state anxiety. J Bodyw Mov Ther 8(4):288–296Google Scholar
  21. 21.
    Human-Agent Communications Working Group (HAC WG) (2018) Website, http://www.fipa.org/subgroups/HAC-WG.html. Accessed April 2018
  22. 22.
    Hmelo-Silver C (2002) Collaborative Ways of Knowing: issues in facilitation. In: Stahl G (ed), Proc Of the Conf on Computer Supported Collaborative Learning: Foundations for a CSCL Community (CSCL '02), 2002. International Society of the Learning Sciences, Boulder, pp 199–208Google Scholar
  23. 23.
    Izard CE (2009) Emotion Theory and Research: Highlights, Unanswered Questions and Emerging Issues. Annu Rev Psychol 60:1–25Google Scholar
  24. 24.
    Jarmon L, Traphagan T, Mayrath M, Trivedi A (2009) Virtual world teaching, experiential learning, and assessment: An interdisciplinary communication course in Second Life. Comput Educ 53:169–182Google Scholar
  25. 25.
    Johnson WL, Rickel JW, Lester JC (2000) Animated pedagogical agents: Face-to-face interaction in interactive learning environments. Int J Artif Intell Educ 11:47–78Google Scholar
  26. 26.
    Keil D, Goldin D (2006) Indirect Interaction in Environments for Multi-agent Systems. In: Weyns D, Van Dyke Parunak H, Michel F (eds) Environments for Multi-Agent Systems II. E4MAS 2005. Lecture Notes in Computer Science, vol 3830. Springer, Berlin, HeidelbergGoogle Scholar
  27. 27.
    Kim Y, Baylor AL (2006) A social–cognitive framework for pedagogical agents as learning companions. Educ Technol Res Dev 54(6):569–590Google Scholar
  28. 28.
    Kim Y, Thayne J, Wei Q (2017) Education. Tech Research Dev 65:219.  https://doi.org/10.1007/s11423-016-9476-z Google Scholar
  29. 29.
    Konstantinidis A, Tsiatsos T, Terzidou T, Pomportsis A (2010) Fostering collaborative learning in Second Life: Metaphors and affordances. Comput Educ 55(2):603–615Google Scholar
  30. 30.
    Landowska A (2013) Affect-awareness Framework for Intelligent Tutoring Systems. In: Proc. Of the 6th International Conference on Human System Interaction (HSI) Conf., 2013. IEEE, Sopot, pp 540–547Google Scholar
  31. 31.
    Larson HA, El Ramahi MK, Conn SR, Estes LA, Ghibellini AB (2010) Reducing Test Anxiety among Third Grade Students through the Implementation of Relaxation Techniques. Journal of School Counseling 8(19):n19Google Scholar
  32. 32.
    Linnenbrink EA (2007) The role of affect in student learning: A multi-dimensional approach to considering the interaction of affect, motivation, and engagement. In: Schutz PA, Pekrun R (eds) Educational psychology series. Elsevier Academic, San Diego, pp 107–124Google Scholar
  33. 33.
    Luck M, Griffiths N, d’Invernoy M (1997) From Agent Theory to Agent Construction: A Case Study, In Intelligent Agents III: Proceedings of the Third International Workshop on Agent Theories, Architectures and Languages, Mueller, Wooldridge and Jennings (ed.), Lecture Notes in AI, 1193, pp. 49–63, Springer-VerlagGoogle Scholar
  34. 34.
    Maes P (1991) Designing Autonomous Agents: Theory and Practice from Biology to Engineering and Back. MIT Press, CambridgeGoogle Scholar
  35. 35.
    Miller RL, Benz JJ, Wysocki DK (2002) Encouraging collaborative learning: Computer-mediated conferencing or Fishbowl interaction, Available from http://files.eric.ed.gov/fulltext/ED472925.pdf. Accessed July, 24 2017
  36. 36.
    Moreno R, Mayer RE, Spires HA, Lester JC (2001) The case for social agency in computer-based teaching: Do students learn more deeply when they interact with animated pedagogical agents? Cogn Instr 19(2):177–213Google Scholar
  37. 37.
    Odell J, Parunka VDH, Fleischer M (2003) Modeling Agents and their Environment: The Communication Environment. Journal of Object Technology 2(3):39–52Google Scholar
  38. 38.
    Olafson KM, Ferraro FR (2001) Effects of emotional state on lexical decision performance. Brain Cogn 45:15–20Google Scholar
  39. 39.
    Open Metaverse Foundation (2018) http://openmetaverse.co/. Accessed April 2018
  40. 40.
    OpenSimulator (2018) Website http://opensimulator.org. Retrieved April 2018
  41. 41.
    Reeves B, Nass C (1996) The media equation. Cambridge University Press, New YorkGoogle Scholar
  42. 42.
    Russell SJ, Norvig P (2009) Artificial Intelligence: A Modern Approach, 3rd edn. Prentice Hall Press, Upper Saddle RiverzbMATHGoogle Scholar
  43. 43.
    Soliman M, Guetl C (2010) Intelligent Pedagogical Agents in Immersive Virtual Learning Environments: A Review. In: The 33rd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2010). Opatija-Croatia, pp 827–832Google Scholar
  44. 44.
    Soller A, Jermann P, Muhlenbrock M, Martinez A (2004) Designing Computational Models of Collaborative Learning Interaction. In: Proc Of the 2nd International Workshop on Designing Computational Models of Collaborative Learning Interaction (ITS 2004). Maceío, Brazil, pp 5–12Google Scholar
  45. 45.
    Takatoa R, Okamoto T (2005) A Design of Interaction Model among Pedagogical Agents in Collaborative Teaching Process. Computer Science and Information Systems 2(2):23–35Google Scholar
  46. 46.
    Terzidou T, Tsiatsos T (2015) Pedagogical Agents in 3D Learning Environments. In: Khosrow-Pour M (ed) Encyclopedia of Information Science and Technology, 3rd edn. IGI Global, Hershey, pp 2572–2581.  https://doi.org/10.4018/978-1-4666-5888-2.ch250 Google Scholar
  47. 47.
    Ur S, VanLehn K (1995) Steps: A simulated, tutorable physics student. J Artif Intell Educ 6(4):405–435Google Scholar
  48. 48.
    Vandenbos GR (2015) APA dictionary of psychology, 2nd edn. American Psychological AssociationGoogle Scholar
  49. 49.
    Veletsianos G, Miller C (2008) Conversing with Pedagogical Agents: A Phenomenological Exploration of Interacting with Digital Entities. Br J Educ Technol 39(6):969–986Google Scholar
  50. 50.
    Videira LC (2011) Hypergrid: Architecture and Protocol for Virtual World Interoperability. IEEE Internet Comput 15(5):22–29Google Scholar
  51. 51.
    Weka (2018) http://www.cs.waikato.ac.nz/ml/weka/. Accessed April 2018
  52. 52.
    Williams CK, Rasmussen CE (2006) Gaussian processes for machine learning. the MIT Press, www.GaussianProcess.org/gpml. Accessed July, 24 2017
  53. 53.
    Wooldridge M (1999) Intelligent Agents. In: Weiss G (ed) Multiagents Systems. A modern Approach to Distributed Artificial Intelligence. MIT Press, Cambridge, pp 27–77Google Scholar
  54. 54.
    Wooldridge M, Jennings N (1995) Intelligent Agents. Theory and Practice. Knowl Eng Rev 10(2):115–152Google Scholar
  55. 55.
    Apostolidis H, Stylianidis P, Tsiatsos T (2014) Anxiety awareness in education: a prototype biofeedback device. In: Karagiannidis C, Politis P, Karasavvidis I (eds) Research on e-Learning and ICT in Education. Springer, New York, pp 227–285Google Scholar
  56. 56.
    Terzidou T, Tsiatsos T, Miliou C, Sourvinou A (2016) Agent supported serious game environment. IEEE Trans Learn Technol 9(3):217–230.  https://doi.org/10.1109/TLT.2016.2521649 Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of InformaticsAristotle University of ThessalonikiThessalonikiGreece

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