Towards a Synthetic Tutor Assistant: The EASEL Project and its Architecture

  • Vasiliki Vouloutsi
  • Maria Blancas
  • Riccardo Zucca
  • Pedro Omedas
  • Dennis Reidsma
  • Daniel Davison
  • Vicky Charisi
  • Frances Wijnen
  • Jan van der Meij
  • Vanessa Evers
  • David Cameron
  • Samuel Fernando
  • Roger Moore
  • Tony Prescott
  • Daniele Mazzei
  • Michael Pieroni
  • Lorenzo Cominelli
  • Roberto Garofalo
  • Danilo De Rossi
  • Paul F. M. J. Verschure
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9793)

Abstract

Robots are gradually but steadily being introduced in our daily lives. A paramount application is that of education, where robots can assume the role of a tutor, a peer or simply a tool to help learners in a specific knowledge domain. Such endeavor posits specific challenges: affective social behavior, proper modelling of the learner’s progress, discrimination of the learner’s utterances, expressions and mental states, which, in turn, require an integrated architecture combining perception, cognition and action. In this paper we present an attempt to improve the current state of robots in the educational domain by introducing the EASEL EU project. Specifically, we introduce the EASEL’s unified robot architecture, an innovative Synthetic Tutor Assistant (STA) whose goal is to interactively guide learners in a science-based learning paradigm, allowing us to achieve such rich multimodal interactions.

Keywords

Education Robotic tutor assistant Pedagogical models Cognitive architecture Distributed Adaptive Control 

References

  1. 1.
    Han, J.-H., Jo, M.-H., Jones, V., Jo, J.-H.: Comparative study on the educational use of home robots for children. J. Inf. Process. Syst. 4(4), 159–168 (2008)CrossRefGoogle Scholar
  2. 2.
    Beer, R.D., Chiel, H.J., Drushel, R.F.: Using autonomous robotics to teach science and engineering. Commun. ACM 42(6), 85–92 (1999)CrossRefGoogle Scholar
  3. 3.
    Mondada, F., Bonani, M., Raemy, X., Pugh, J., Cianci, C., Klaptocz, A., Magnenat, S., Zufferey, J.-C., Floreano, D., Martinoli, A.: The e-puck, a robot designed for education in engineering. In: Proceedings of the 9th Conference on Autonomous Robot Systems, Competitions, vol. 1, pp. 59–65. Instituto Politécnico de Castelo Branco (2009)Google Scholar
  4. 4.
    Wijnen, F., Charisi, V., Davison, D., van der Meij, J., Reidsma, D., Evers, V.: Inquiry learning with a social robot: can you explain that to me? In: Heerink, M., de Jong, M. (eds.) Proceedings of New Friends 2015: The 1st international conference on social robotics in therapy and education, pp. 24–25, Windesheim Flevoland, Almere (2015)Google Scholar
  5. 5.
    Kanda, T., Hirano, T., Eaton, D., Ishiguro, H.: Interactive robots as social partners and peer tutors for children: a field trial. Hum.-Comput. Interact. 19(1), 61–84 (2004)CrossRefGoogle Scholar
  6. 6.
    Saerbeck, M., Schut, T., Bartneck, C., Janse, M.D.: Expressive robots in education: varying the degree of social supportive behavior of a robotic tutor. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 1613–1622. ACM (2010)Google Scholar
  7. 7.
    Shin, N., Kim, S.: Learning about, from, with robots: students’ perspectives. In: The 16th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2007, pp. 1040–1045. IEEE (2007)Google Scholar
  8. 8.
    Vouloutsi, V., Munoz, M.B., Grechuta, K., Lallee, S., Duff, A., Llobet, J.-Y.P., Verschure, P.F.M.J.: A new biomimetic approach towards educational robotics: the distributed adaptive control of a synthetic tutor assistant. New Frontiers in Human-Robot Interaction, p. 22 (2015)Google Scholar
  9. 9.
    Blancas, M., Vouloutsi, V., Grechuta, K., Verschure, P.F.M.J.: Effects of the robot’s role on human-robot interaction in an educational scenario. In: Wilson, S.P., Verschure, P.F.M.J., Mura, A., Prescott, T.J. (eds.) Living Machines 2015. LNCS, vol. 9222, pp. 391–402. Springer, Heidelberg (2015)CrossRefGoogle Scholar
  10. 10.
    Balch, T., et al.: Designing personal robots for education: hardware, software and curriculum. IEEE Pervasive Comput. 7(2), 5–9 (2008)CrossRefGoogle Scholar
  11. 11.
    Highfield, K., Mulligan, J., Hedberg, J.: Early mathematics learning through exploration with programmable toys. In: Proceedings of the Joint Meeting of PME 32 and PME-NA, pp. 169–176. Citeseer (2008)Google Scholar
  12. 12.
    Mubin, O., Stevens, C.J., Shahid, S., Al Mahmud, A., Dong, J.-J.: A review of the applicability of robots in education. J. Technol. Educ. Learn. 1, 209–215 (2013)Google Scholar
  13. 13.
    Piaget, J., Inhelder, B.: The Psychology of the Child. Basic Books, New York (1972)Google Scholar
  14. 14.
    Papert, S., Harel, I.: Situating constructionism. Constructionism 36, 1–11 (1991)Google Scholar
  15. 15.
    Vygotsky, L.S.: Mind in Society: The Development of Higher Psychological Processes. Harvard University Press, Cambridge (1980)Google Scholar
  16. 16.
    Charisi, V., Davison, D., Wijnen, F., Van Der Meij, J., Reidsma, D., Prescott, T., Van Joolingen, W., Evers, V.: Towards a child-robot symbiotic co-development: a theoretical approach. In: AISB Convention 2015, The Society for the Study of Artificial Intelligence and the Simulation of Behaviour (AISB) (2015)Google Scholar
  17. 17.
    Verschure, P.F.M.J.: Distributed adaptive control: a theory of the mind, brain, body nexus. Biologically Inspired Cogn. Architectures 1, 55–72 (2012)CrossRefGoogle Scholar
  18. 18.
    Verschure, P.F.M.J., Voegtlin, T., Douglas, R.J.: Environmentally mediated synergy between perception and behaviour in mobile robots. Nature 425, 620–624 (2003)CrossRefGoogle Scholar
  19. 19.
    Verschure, P.F.M.J., Pennartz, C.M., Pezzulo, G.: The why, what, where, when and how of goal-directed choice: neuronal and computational principles. Phil. Trans. R. Soc. B 369(1655), 20130483 (2014)CrossRefGoogle Scholar
  20. 20.
    Maffei, G., Santos-Pata, D., Marcos, E., Sánchez-Fibla, M., Verschure, P.F.M.J.: An embodied biologically constrained model of foraging: from classical and operant conditioning to adaptive real-world behavior in DAC-X. Neural Netw. 72, 88–108 (2015)CrossRefGoogle Scholar
  21. 21.
    Kruger, J., Dunning, D.: Unskilled and unaware of it: how difficulties in recognizing one’s own incompetence lead to inflated self-assessments. J. Pers. Soc. Psychol. 77(6), 1121 (1999)CrossRefGoogle Scholar
  22. 22.
    Abramson, L.Y., Seligman, M.E., Teasdale, J.D.: Learned helplessness in humans: critique and reformulation. J. Abnorm. Psychol. 87(1), 49 (1978)CrossRefGoogle Scholar
  23. 23.
    Seligman, M.E.: Learned helplessness. Annu. Rev. Med. 23(1), 407–412 (1972)CrossRefGoogle Scholar
  24. 24.
    Inhelder, B., Piaget, J.: The Growth of Logical Thinking from Childhood to Adolescence: An Essay on the Construction of Formal Operational Structures. Basic Books, New York (1958)CrossRefGoogle Scholar
  25. 25.
    Siegler, R.S.: Three aspects of cognitive development. Cogn. Psychol. 8(4), 481–520 (1976)CrossRefGoogle Scholar
  26. 26.
    Siegler, R.S., Strauss, S., Levin, I.: Developmental sequences within and between concepts. Monogr. Soc. Res. Child Dev. 46, 631–683 (1981)CrossRefGoogle Scholar
  27. 27.
    Metta, G., Fitzpatrick, P., Natale, L.: Yarp: yet another robot platform. Int. J. Adv. Rob. Syst. 3(1), 43–48 (2006)Google Scholar
  28. 28.
    Povey, D., Ghoshal, A., Boulianne, G., Burget, L., Glembek, O., Goel, N., Hannemann, M., Motlicek, P., Qian, Y., Schwarz, P., et al.: The kaldi speech recognition toolkit. In: IEEE 2011 workshop on automatic speech recognition and understanding, no. EPFL-CONF-192584. IEEE Signal Processing Society (2011)Google Scholar
  29. 29.
    Zaraki, A., Mazzei, D., Giuliani, M., De Rossi, D.: Designing and evaluating a social gaze-control system for a humanoid robot. IEEE Trans. Hum.-Mach. Syst. 44(2), 157–168 (2014)CrossRefGoogle Scholar
  30. 30.
    Zaraki, A., Mazzei, D., Lazzeri, N., Pieroni, M., De Rossi, D.: Preliminary implementation of context-aware attention system for humanoid robots. In: Lepora, N.F., Mura, A., Krapp, H.G., Verschure, P.F.M.J., Prescott, T.J. (eds.) Living Machines 2013. LNCS, vol. 8064, pp. 457–459. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  31. 31.
    Reidsma, D., van Welbergen, H.: AsapRealizer in practice - a modular and extensible architecture for a bml realizer. Entertainment Comput. 4(3), 157–169 (2013)CrossRefGoogle Scholar
  32. 32.
    van Welbergen, H., Yaghoubzadeh, R., Kopp, S.: AsapRealizer 2.0: the next steps in fluent behavior realization for ECAs. In: Bickmore, T., Marsella, S., Sidner, C. (eds.) IVA 2014. LNCS, vol. 8637, pp. 449–462. Springer, Heidelberg (2014)Google Scholar
  33. 33.
    Vouloutsi, V., Lallée, S., Verschure, P.F.M.J.: Modulating behaviors using allostatic control. In: Lepora, N.F., Mura, A., Krapp, H.G., Verschure, P.F.M.J., Prescott, T.J. (eds.) Living Machines 2013. LNCS, vol. 8064, pp. 287–298. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  34. 34.
    Lallée, S., Vouloutsi, V., Wierenga, S., Pattacini, U., Verschure, P.F.M.J: Efaa: a companion emerges from integrating a layered cognitive architecture. In: Proceedings of the 2014 ACM/IEEE International Conference on Human-Robot Interaction, pp. 105–105. ACM (2014)Google Scholar
  35. 35.
    ter Maat, M., Heylen, D.: Flipper: an information state component for spoken dialogue systems. In: Vilhjálmsson, H.H., Kopp, S., Marsella, S., Thórisson, K.R. (eds.) IVA 2011. LNCS, vol. 6895, pp. 470–472. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  36. 36.
    Lazzeri, N., Mazzei, D., Zaraki, A., De Rossi, D.: Towards a believable social robot. In: Lepora, N.F., Mura, A., Krapp, H.G., Verschure, P.F.M.J., Prescott, T.J. (eds.) Living Machines 2013. LNCS, vol. 8064, pp. 393–395. Springer, Heidelberg (2013)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Vasiliki Vouloutsi
    • 1
  • Maria Blancas
    • 1
  • Riccardo Zucca
    • 1
  • Pedro Omedas
    • 1
  • Dennis Reidsma
    • 3
  • Daniel Davison
    • 3
  • Vicky Charisi
    • 3
  • Frances Wijnen
    • 3
  • Jan van der Meij
    • 3
  • Vanessa Evers
    • 3
  • David Cameron
    • 4
  • Samuel Fernando
    • 4
  • Roger Moore
    • 4
  • Tony Prescott
    • 4
  • Daniele Mazzei
    • 5
  • Michael Pieroni
    • 5
  • Lorenzo Cominelli
    • 5
  • Roberto Garofalo
    • 5
  • Danilo De Rossi
    • 5
  • Paul F. M. J. Verschure
    • 1
    • 2
  1. 1.SPECS, N-RAS, DTICUniversitat Pompeu Fabra (UPF)BarcelonaSpain
  2. 2.Catalan Institute of Advanced Studies (ICREA)BarcelonaSpain
  3. 3.Human Media Interaction/ELANUniversity of TwenteEnschedeNetherlands
  4. 4.Sheffield RoboticsUniversity of SheffieldSheffieldUK
  5. 5.University of PisaPisaItaly

Personalised recommendations