A Robot Math Tutor that Gives Feedback

  • Koen V. HindriksEmail author
  • Sander Liebens
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11876)


We report on the exploratory design and study of a robot math tutor that can provide feedback on specific errors made by children solving basic addition and subtraction problems up to 100. We discuss two interaction design patterns, one for speech recognition of answers when children think aloud, and one for providing error-specific feedback. We evaluate our design patterns and whether our feedback mechanism motivates children and improves their performance at primary schools with children (\(N=41\)) aged 7–9. We did not find any motivational or learning effects of our feedback mechanism but lessons learnt include that the robot can execute our interaction design patterns autonomously, and advanced algorithms for error classification and adaptation to children’s performance levels in our feedback mechanism are needed.


  1. 1.
    Beishuizen, M.: Mental strategies and materials or models for addition and subtraction up to 100 in Dutch second grades. J. Res. Math. Educ. 24(4), 294–323 (1993)CrossRefGoogle Scholar
  2. 2.
    Belpaeme, T., Kennedy, J., Ramachandran, A., Scassellati, B., Tanaka, F.: Social robots for education: a review. Sci. Roboti. 3(21), eaat5954 (2018)CrossRefGoogle Scholar
  3. 3.
    Brown, L., Howard, A.M.: Engaging children in math education using a socially interactive humanoid robot. In: 2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids), pp. 183–188, October 2013Google Scholar
  4. 4.
    Hattie, J., Timperley, H.: Review of educational the power of feedback. Rev. Educ. Res. 77(1), 81–112 (2007)CrossRefGoogle Scholar
  5. 5.
    Janssen, J.B., van der Wal, C.C., Neerincx, M.A., Looije, R.: Motivating children to learn arithmetic with an adaptive robot game. In: Mutlu, B., Bartneck, C., Ham, J., Evers, V., Kanda, T. (eds.) ICSR 2011. LNCS (LNAI), vol. 7072, pp. 153–162. Springer, Heidelberg (2011). Scholar
  6. 6.
    Kahn, P.H., et al..: Design patterns for sociality in human-robot interaction. In: Proceedings of the International Conference on Human Robot Interaction, pp. 97–104. ACM (2008)Google Scholar
  7. 7.
    Kennedy, J., Baxter, P., Belpaeme, T.: The robot who tried too hard: social behaviour of a robot tutor can negatively affect child learning. In: Proceedings of the International Conference on Human-Robot Interaction, vol. 801, pp. 67–74 (2015)Google Scholar
  8. 8.
    Kennedy, J., et al.: Child speech recognition in human-robot interaction: evaluations and recommendations. In: Proceedings of the International Conference on Human-Robot Interaction, pp. 82–90. ACM (2017)Google Scholar
  9. 9.
    Lee, J., Corter, J.E.: Diagnosis of subtraction bugs using Bayesian networks. Appl. Psychol. Meas. 35(1), 27–47 (2011)CrossRefGoogle Scholar
  10. 10.
    Mubin, O., Stevens, C.J., Shahid, S., Al Mahmud, A., Dong, J.J.: A review of the applicability of robots in education. J. Tech. Educ. Learn. 1(209–0015), 13 (2013)Google Scholar
  11. 11.
    Norcini, J.: The power of feedback. Med. Educ. 44(1), 16–17 (2010)CrossRefGoogle Scholar
  12. 12.
    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 on Human Factors in Computing Systems (SIGCHI), pp. 1613–1622. ACM (2010)Google Scholar
  13. 13.
    Schadenberg, B.R., Neerincx, M.A., Cnossen, F., Looije, R.: Personalising game difficulty to keep children motivated to play with a social robot: a Bayesian approach. Cogn. Syst. Res. 43, 222–231 (2017)CrossRefGoogle Scholar
  14. 14.
    Singh, R., et al.: Feedback during web-based homework: the role of hints. In: Biswas, G., Bull, S., Kay, J., Mitrovic, A. (eds.) AIED 2011. LNCS (LNAI), vol. 6738, pp. 328–336. Springer, Heidelberg (2011). Scholar
  15. 15.
    Tiberius, R.G., Billson, J.M.: The social context of teaching and learning. New Dir. Teach. Learn. 1991(45), 67–86 (1991)CrossRefGoogle Scholar
  16. 16.
    Watson, D., Clark, L.A., Tellegen, A.: Development and validation of brief measures of positive and negative affect: the PANAS scales. J. Pers. Soc. Psychol. 54(6), 1063 (1988)CrossRefGoogle Scholar
  17. 17.
    Wiggins, G.: 7 Keys to Effective Feedback. Educ. leadersh. 70(1), 10–16 (2012) Google Scholar

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of ScienceVrije Universiteit AmsterdamAmsterdamThe Netherlands
  2. 2.Department of Computing ScienceDelftThe Netherlands

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